Developing Cyberinfrastructure Tools and Services for Metadata Quality Evaluation

NASA Astrophysics Data System (ADS)

Mecum, B.; Gordon, S.; Habermann, T.; Jones, M. B.; Leinfelder, B.; Powers, L. A.; Slaughter, P.

2016-12-01

Metadata and data quality are at the core of reusable and reproducible science. While great progress has been made over the years, much of the metadata collected only addresses data discovery, covering concepts such as titles and keywords. Improving metadata beyond the discoverability plateau means documenting detailed concepts within the data such as sampling protocols, instrumentation used, and variables measured. Given that metadata commonly do not describe their data at this level, how might we improve the state of things? Giving scientists and data managers easy to use tools to evaluate metadata quality that utilize community-driven recommendations is the key to producing high-quality metadata. To achieve this goal, we created a set of cyberinfrastructure tools and services that integrate with existing metadata and data curation workflows which can be used to improve metadata and data quality across the sciences. These tools work across metadata dialects (e.g., ISO19115, FGDC, EML, etc.) and can be used to assess aspects of quality beyond what is internal to the metadata such as the congruence between the metadata and the data it describes. The system makes use of a user-friendly mechanism for expressing a suite of checks as code in popular data science programming languages such as Python and R. This reduces the burden on scientists and data managers to learn yet another language. We demonstrated these services and tools in three ways. First, we evaluated a large corpus of datasets in the DataONE federation of data repositories against a metadata recommendation modeled after existing recommendations such as the LTER best practices and the Attribute Convention for Dataset Discovery (ACDD). Second, we showed how this service can be used to display metadata and data quality information to data producers during the data submission and metadata creation process, and to data consumers through data catalog search and access tools. Third, we showed how the centrally deployed DataONE quality service can achieve major efficiency gains by allowing member repositories to customize and use recommendations that fit their specific needs without having to create de novo infrastructure at their site.

Online Metadata Directories: A way of preserving, sharing and discovering scientific information

NASA Technical Reports Server (NTRS)

Meaux, M.

2005-01-01

The Global Change Master Directory (GCMD) assists the scientific community in the discovery of and linkage to Earth Science data and provides data holders a means to advertise their data to the community through its portals, i.e. online customized subset metadata directories. These directories are effectively serving communities like the Joint Committee on Antarctic Data Management (JCADM), the Global Observing System Information Center (GOSIC), and the Global Ocean Ecosystems Dynamic Program (GLOBEC) by increasing the visibility of their data holding. The purpose of the Gulf of Maine Ocean Data Partnership (GoMODP) is to "promote and coordinate the sharing, linking, electronic dissemination, and use of data on the Gulf of Maine region". The participants have decided that a "coordinated effort is needed to enable users throughout the Gulf of Maine region and beyond to discover and put to use the vast and growing quantities of data in their respective databases". GoMODP members have invited the GCMD to discuss potential collaborations associated with this effort. The presentation will focus on the use of the GCMD s metadata directory as a powerful tool for data discovery and sharing. An overview of the directory and its metadata authoring tools will be given.

Metazen – metadata capture for metagenomes

DOE PAGES

Bischof, Jared; Harrison, Travis; Paczian, Tobias; ...

2014-12-08

Background: As the impact and prevalence of large-scale metagenomic surveys grow, so does the acute need for more complete and standards compliant metadata. Metadata (data describing data) provides an essential complement to experimental data, helping to answer questions about its source, mode of collection, and reliability. Metadata collection and interpretation have become vital to the genomics and metagenomics communities, but considerable challenges remain, including exchange, curation, and distribution. Currently, tools are available for capturing basic field metadata during sampling, and for storing, updating and viewing it. These tools are not specifically designed for metagenomic surveys; in particular, they lack themore » appropriate metadata collection templates, a centralized storage repository, and a unique ID linking system that can be used to easily port complete and compatible metagenomic metadata into widely used assembly and sequence analysis tools. Results: Metazen was developed as a comprehensive framework designed to enable metadata capture for metagenomic sequencing projects. Specifically, Metazen provides a rapid, easy-to-use portal to encourage early deposition of project and sample metadata. Conclusion: Metazen is an interactive tool that aids users in recording their metadata in a complete and valid format. A defined set of mandatory fields captures vital information, while the option to add fields provides flexibility.« less

Metazen – metadata capture for metagenomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bischof, Jared; Harrison, Travis; Paczian, Tobias

Background: As the impact and prevalence of large-scale metagenomic surveys grow, so does the acute need for more complete and standards compliant metadata. Metadata (data describing data) provides an essential complement to experimental data, helping to answer questions about its source, mode of collection, and reliability. Metadata collection and interpretation have become vital to the genomics and metagenomics communities, but considerable challenges remain, including exchange, curation, and distribution. Currently, tools are available for capturing basic field metadata during sampling, and for storing, updating and viewing it. These tools are not specifically designed for metagenomic surveys; in particular, they lack themore » appropriate metadata collection templates, a centralized storage repository, and a unique ID linking system that can be used to easily port complete and compatible metagenomic metadata into widely used assembly and sequence analysis tools. Results: Metazen was developed as a comprehensive framework designed to enable metadata capture for metagenomic sequencing projects. Specifically, Metazen provides a rapid, easy-to-use portal to encourage early deposition of project and sample metadata. Conclusion: Metazen is an interactive tool that aids users in recording their metadata in a complete and valid format. A defined set of mandatory fields captures vital information, while the option to add fields provides flexibility.« less

Use of a metadata documentation and search tool for large data volumes: The NGEE arctic example

DOE Office of Scientific and Technical Information (OSTI.GOV)

Devarakonda, Ranjeet; Hook, Leslie A; Killeffer, Terri S

The Online Metadata Editor (OME) is a web-based tool to help document scientific data in a well-structured, popular scientific metadata format. In this paper, we will discuss the newest tool that Oak Ridge National Laboratory (ORNL) has developed to generate, edit, and manage metadata and how it is helping data-intensive science centers and projects, such as the U.S. Department of Energy s Next Generation Ecosystem Experiments (NGEE) in the Arctic to prepare metadata and make their big data produce big science and lead to new discoveries.

New Tools to Document and Manage Data/Metadata: Example NGEE Arctic and ARM

NASA Astrophysics Data System (ADS)

Crow, M. C.; Devarakonda, R.; Killeffer, T.; Hook, L.; Boden, T.; Wullschleger, S.

2017-12-01

Tools used for documenting, archiving, cataloging, and searching data are critical pieces of informatics. This poster describes tools being used in several projects at Oak Ridge National Laboratory (ORNL), with a focus on the U.S. Department of Energy's Next Generation Ecosystem Experiment in the Arctic (NGEE Arctic) and Atmospheric Radiation Measurements (ARM) project, and their usage at different stages of the data lifecycle. The Online Metadata Editor (OME) is used for the documentation and archival stages while a Data Search tool supports indexing, cataloging, and searching. The NGEE Arctic OME Tool [1] provides a method by which researchers can upload their data and provide original metadata with each upload while adhering to standard metadata formats. The tool is built upon a Java SPRING framework to parse user input into, and from, XML output. Many aspects of the tool require use of a relational database including encrypted user-login, auto-fill functionality for predefined sites and plots, and file reference storage and sorting. The Data Search Tool conveniently displays each data record in a thumbnail containing the title, source, and date range, and features a quick view of the metadata associated with that record, as well as a direct link to the data. The search box incorporates autocomplete capabilities for search terms and sorted keyword filters are available on the side of the page, including a map for geo-searching. These tools are supported by the Mercury [2] consortium (funded by DOE, NASA, USGS, and ARM) and developed and managed at Oak Ridge National Laboratory. Mercury is a set of tools for collecting, searching, and retrieving metadata and data. Mercury collects metadata from contributing project servers, then indexes the metadata to make it searchable using Apache Solr, and provides access to retrieve it from the web page. Metadata standards that Mercury supports include: XML, Z39.50, FGDC, Dublin-Core, Darwin-Core, EML, and ISO-19115.

Data Discovery of Big and Diverse Climate Change Datasets - Options, Practices and Challenges

NASA Astrophysics Data System (ADS)

Palanisamy, G.; Boden, T.; McCord, R. A.; Frame, M. T.

2013-12-01

Developing data search tools is a very common, but often confusing, task for most of the data intensive scientific projects. These search interfaces need to be continually improved to handle the ever increasing diversity and volume of data collections. There are many aspects which determine the type of search tool a project needs to provide to their user community. These include: number of datasets, amount and consistency of discovery metadata, ancillary information such as availability of quality information and provenance, and availability of similar datasets from other distributed sources. Environmental Data Science and Systems (EDSS) group within the Environmental Science Division at the Oak Ridge National Laboratory has a long history of successfully managing diverse and big observational datasets for various scientific programs via various data centers such as DOE's Atmospheric Radiation Measurement Program (ARM), DOE's Carbon Dioxide Information and Analysis Center (CDIAC), USGS's Core Science Analytics and Synthesis (CSAS) metadata Clearinghouse and NASA's Distributed Active Archive Center (ORNL DAAC). This talk will showcase some of the recent developments for improving the data discovery within these centers The DOE ARM program recently developed a data discovery tool which allows users to search and discover over 4000 observational datasets. These datasets are key to the research efforts related to global climate change. The ARM discovery tool features many new functions such as filtered and faceted search logic, multi-pass data selection, filtering data based on data quality, graphical views of data quality and availability, direct access to data quality reports, and data plots. The ARM Archive also provides discovery metadata to other broader metadata clearinghouses such as ESGF, IASOA, and GOS. In addition to the new interface, ARM is also currently working on providing DOI metadata records to publishers such as Thomson Reuters and Elsevier. The ARM program also provides a standards based online metadata editor (OME) for PIs to submit their data to the ARM Data Archive. USGS CSAS metadata Clearinghouse aggregates metadata records from several USGS projects and other partner organizations. The Clearinghouse allows users to search and discover over 100,000 biological and ecological datasets from a single web portal. The Clearinghouse also enabled some new data discovery functions such as enhanced geo-spatial searches based on land and ocean classifications, metadata completeness rankings, data linkage via digital object identifiers (DOIs), and semantically enhanced keyword searches. The Clearinghouse also currently working on enabling a dashboard which allows the data providers to look at various statistics such as number their records accessed via the Clearinghouse, most popular keywords, metadata quality report and DOI creation service. The Clearinghouse also publishes metadata records to broader portals such as NSF DataONE and Data.gov. The author will also present how these capabilities are currently reused by the recent and upcoming data centers such as DOE's NGEE-Arctic project. References: [1] Devarakonda, R., Palanisamy, G., Wilson, B. E., & Green, J. M. (2010). Mercury: reusable metadata management, data discovery and access system. Earth Science Informatics, 3(1-2), 87-94. [2]Devarakonda, R., Shrestha, B., Palanisamy, G., Hook, L., Killeffer, T., Krassovski, M., ... & Frame, M. (2014, October). OME: Tool for generating and managing metadata to handle BigData. In BigData Conference (pp. 8-10).

Metadata improvements driving new tools and services at a NASA data center

NASA Astrophysics Data System (ADS)

Moroni, D. F.; Hausman, J.; Foti, G.; Armstrong, E. M.

2011-12-01

The NASA Physical Oceanography DAAC (PO.DAAC) is responsible for distributing and maintaining satellite derived oceanographic data from a number of NASA and non-NASA missions for the physical disciplines of ocean winds, sea surface temperature, ocean topography and gravity. Currently its holdings consist of over 600 datasets with a data archive in excess of 200 Terrabytes. The PO.DAAC has recently embarked on a metadata quality and completeness project to migrate, update and improve metadata records for over 300 public datasets. An interactive database management tool has been developed to allow data scientists to enter, update and maintain metadata records. This tool communicates directly with PO.DAAC's Data Management and Archiving System (DMAS), which serves as the new archival and distribution backbone as well as a permanent repository of dataset and granule-level metadata. Although we will briefly discuss the tool, more important ramifications are the ability to now expose, propagate and leverage the metadata in a number of ways. First, the metadata are exposed directly through a faceted and free text search interface directly from drupal-based PO.DAAC web pages allowing for quick browsing and data discovery especially by "drilling" through the various facet levels that organize datasets by time/space resolution, processing level, sensor, measurement type etc. Furthermore, the metadata can now be exposed through web services to produce metadata records in a number of different formats such as FGDC and ISO 19115, or potentially propagated to visualization and subsetting tools, and other discovery interfaces. The fundamental concept is that the metadata forms the essential bridge between the user, and the tool or discovery mechanism for a broad range of ocean earth science data records.

Dynamic publication model for neurophysiology databases.

PubMed

Gardner, D; Abato, M; Knuth, K H; DeBellis, R; Erde, S M

2001-08-29

We have implemented a pair of database projects, one serving cortical electrophysiology and the other invertebrate neurones and recordings. The design for each combines aspects of two proven schemes for information interchange. The journal article metaphor determined the type, scope, organization and quantity of data to comprise each submission. Sequence databases encouraged intuitive tools for data viewing, capture, and direct submission by authors. Neurophysiology required transcending these models with new datatypes. Time-series, histogram and bivariate datatypes, including illustration-like wrappers, were selected by their utility to the community of investigators. As interpretation of neurophysiological recordings depends on context supplied by metadata attributes, searches are via visual interfaces to sets of controlled-vocabulary metadata trees. Neurones, for example, can be specified by metadata describing functional and anatomical characteristics. Permanence is advanced by data model and data formats largely independent of contemporary technology or implementation, including Java and the XML standard. All user tools, including dynamic data viewers that serve as a virtual oscilloscope, are Java-based, free, multiplatform, and distributed by our application servers to any contemporary networked computer. Copyright is retained by submitters; viewer displays are dynamic and do not violate copyright of related journal figures. Panels of neurophysiologists view and test schemas and tools, enhancing community support.

A document centric metadata registration tool constructing earth environmental data infrastructure

NASA Astrophysics Data System (ADS)

Ichino, M.; Kinutani, H.; Ono, M.; Shimizu, T.; Yoshikawa, M.; Masuda, K.; Fukuda, K.; Kawamoto, H.

2009-12-01

DIAS (Data Integration and Analysis System) is one of GEOSS activities in Japan. It is also a leading part of the GEOSS task with the same name defined in GEOSS Ten Year Implementation Plan. The main mission of DIAS is to construct data infrastructure that can effectively integrate earth environmental data such as observation data, numerical model outputs, and socio-economic data provided from the fields of climate, water cycle, ecosystem, ocean, biodiversity and agriculture. Some of DIAS's data products are available at the following web site of http://www.jamstec.go.jp/e/medid/dias. Most of earth environmental data commonly have spatial and temporal attributes such as the covering geographic scope or the created date. The metadata standards including these common attributes are published by the geographic information technical committee (TC211) in ISO (the International Organization for Standardization) as specifications of ISO 19115:2003 and 19139:2007. Accordingly, DIAS metadata is developed with basing on ISO/TC211 metadata standards. From the viewpoint of data users, metadata is useful not only for data retrieval and analysis but also for interoperability and information sharing among experts, beginners and nonprofessionals. On the other hand, from the viewpoint of data providers, two problems were pointed out after discussions. One is that data providers prefer to minimize another tasks and spending time for creating metadata. Another is that data providers want to manage and publish documents to explain their data sets more comprehensively. Because of solving these problems, we have been developing a document centric metadata registration tool. The features of our tool are that the generated documents are available instantly and there is no extra cost for data providers to generate metadata. Also, this tool is developed as a Web application. So, this tool does not demand any software for data providers if they have a web-browser. The interface of the tool provides the section titles of the documents and by filling out the content of each section, the documents for the data sets are automatically published in PDF and HTML format. Furthermore, the metadata XML file which is compliant with ISO19115 and ISO19139 is created at the same moment. The generated metadata are managed in the metadata database of the DIAS project, and will be used in various ISO19139 compliant metadata management tools, such as GeoNetwork.

HDF-EOS Dump Tools

NASA Astrophysics Data System (ADS)

Prasad, U.; Rahabi, A.

2001-05-01

The following utilities developed for HDF-EOS format data dump are of special use for Earth science data for NASA's Earth Observation System (EOS). This poster demonstrates their use and application. The first four tools take HDF-EOS data files as input. HDF-EOS Metadata Dumper - metadmp Metadata dumper extracts metadata from EOS data granules. It operates by simply copying blocks of metadata from the file to the standard output. It does not process the metadata in any way. Since all metadata in EOS granules is encoded in the Object Description Language (ODL), the output of metadmp will be in the form of complete ODL statements. EOS data granules may contain up to three different sets of metadata (Core, Archive, and Structural Metadata). HDF-EOS Contents Dumper - heosls Heosls dumper displays the contents of HDF-EOS files. This utility provides detailed information on the POINT, SWATH, and GRID data sets. in the files. For example: it will list, the Geo-location fields, Data fields and objects. HDF-EOS ASCII Dumper - asciidmp The ASCII dump utility extracts fields from EOS data granules into plain ASCII text. The output from asciidmp should be easily human readable. With minor editing, asciidmp's output can be made ingestible by any application with ASCII import capabilities. HDF-EOS Binary Dumper - bindmp The binary dumper utility dumps HDF-EOS objects in binary format. This is useful for feeding the output of it into existing program, which does not understand HDF, for example: custom software and COTS products. HDF-EOS User Friendly Metadata - UFM The UFM utility tool is useful for viewing ECS metadata. UFM takes an EOSDIS ODL metadata file and produces an HTML report of the metadata for display using a web browser. HDF-EOS METCHECK - METCHECK METCHECK can be invoked from either Unix or Dos environment with a set of command line options that a user might use to direct the tool inputs and output . METCHECK validates the inventory metadata in (.met file) using The Descriptor file (.desc) as the reference. The tool takes (.desc), and (.met) an ODL file as inputs, and generates a simple output file contains the results of the checking process.

Improving Scientific Metadata Interoperability And Data Discoverability using OAI-PMH

NASA Astrophysics Data System (ADS)

Devarakonda, Ranjeet; Palanisamy, Giri; Green, James M.; Wilson, Bruce E.

2010-12-01

While general-purpose search engines (such as Google or Bing) are useful for finding many things on the Internet, they are often of limited usefulness for locating Earth Science data relevant (for example) to a specific spatiotemporal extent. By contrast, tools that search repositories of structured metadata can locate relevant datasets with fairly high precision, but the search is limited to that particular repository. Federated searches (such as Z39.50) have been used, but can be slow and the comprehensiveness can be limited by downtime in any search partner. An alternative approach to improve comprehensiveness is for a repository to harvest metadata from other repositories, possibly with limits based on subject matter or access permissions. Searches through harvested metadata can be extremely responsive, and the search tool can be customized with semantic augmentation appropriate to the community of practice being served. However, there are a number of different protocols for harvesting metadata, with some challenges for ensuring that updates are propagated and for collaborations with repositories using differing metadata standards. The Open Archive Initiative Protocol for Metadata Handling (OAI-PMH) is a standard that is seeing increased use as a means for exchanging structured metadata. OAI-PMH implementations must support Dublin Core as a metadata standard, with other metadata formats as optional. We have developed tools which enable our structured search tool (Mercury; http://mercury.ornl.gov) to consume metadata from OAI-PMH services in any of the metadata formats we support (Dublin Core, Darwin Core, FCDC CSDGM, GCMD DIF, EML, and ISO 19115/19137). We are also making ORNL DAAC metadata available through OAI-PMH for other metadata tools to utilize, such as the NASA Global Change Master Directory, GCMD). This paper describes Mercury capabilities with multiple metadata formats, in general, and, more specifically, the results of our OAI-PMH implementations and the lessons learned. References: [1] R. Devarakonda, G. Palanisamy, B.E. Wilson, and J.M. Green, "Mercury: reusable metadata management data discovery and access system", Earth Science Informatics, vol. 3, no. 1, pp. 87-94, May 2010. [2] R. Devarakonda, G. Palanisamy, J.M. Green, B.E. Wilson, "Data sharing and retrieval using OAI-PMH", Earth Science Informatics DOI: 10.1007/s12145-010-0073-0, (2010). [3] Devarakonda, R.; Palanisamy, G.; Green, J.; Wilson, B. E. "Mercury: An Example of Effective Software Reuse for Metadata Management Data Discovery and Access", Eos Trans. AGU, 89(53), Fall Meet. Suppl., IN11A-1019 (2008).

Creating Access Points to Instrument-Based Atmospheric Data: Perspectives from the ARM Metadata Manager

NASA Astrophysics Data System (ADS)

Troyan, D.

2016-12-01

The Atmospheric Radiation Measurement (ARM) program has been collecting data from instruments in diverse climate regions for nearly twenty-five years. These data are made available to all interested parties at no cost via specially designed tools found on the ARM website (www.arm.gov). Metadata is created and applied to the various datastreams to facilitate information retrieval using the ARM website, the ARM Data Discovery Tool, and data quality reporting tools. Over the last year, the Metadata Manager - a relatively new position within the ARM program - created two documents that summarize the state of ARM metadata processes: ARM Metadata Workflow, and ARM Metadata Standards. These documents serve as guides to the creation and management of ARM metadata. With many of ARM's data functions spread around the Department of Energy national laboratory complex and with many of the original architects of the metadata structure no longer working for ARM, there is increased importance on using these documents to resolve issues from data flow bottlenecks and inaccurate metadata to improving data discovery and organizing web pages. This presentation will provide some examples from the workflow and standards documents. The examples will illustrate the complexity of the ARM metadata processes and the efficiency by which the metadata team works towards achieving the goal of providing access to data collected under the auspices of the ARM program.

mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data.

PubMed

Larralde, Martin; Lawson, Thomas N; Weber, Ralf J M; Moreno, Pablo; Haug, Kenneth; Rocca-Serra, Philippe; Viant, Mark R; Steinbeck, Christoph; Salek, Reza M

2017-08-15

Submission to the MetaboLights repository for metabolomics data currently places the burden of reporting instrument and acquisition parameters in ISA-Tab format on users, who have to do it manually, a process that is time consuming and prone to user input error. Since the large majority of these parameters are embedded in instrument raw data files, an opportunity exists to capture this metadata more accurately. Here we report a set of Python packages that can automatically generate ISA-Tab metadata file stubs from raw XML metabolomics data files. The parsing packages are separated into mzML2ISA (encompassing mzML and imzML formats) and nmrML2ISA (nmrML format only). Overall, the use of mzML2ISA & nmrML2ISA reduces the time needed to capture metadata substantially (capturing 90% of metadata on assay and sample levels), is much less prone to user input errors, improves compliance with minimum information reporting guidelines and facilitates more finely grained data exploration and querying of datasets. mzML2ISA & nmrML2ISA are available under version 3 of the GNU General Public Licence at https://github.com/ISA-tools. Documentation is available from http://2isa.readthedocs.io/en/latest/. reza.salek@ebi.ac.uk or isatools@googlegroups.com. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Streamlining Metadata and Data Management for Evolving Digital Libraries

NASA Astrophysics Data System (ADS)

Clark, D.; Miller, S. P.; Peckman, U.; Smith, J.; Aerni, S.; Helly, J.; Sutton, D.; Chase, A.

2003-12-01

What began two years ago as an effort to stabilize the Scripps Institution of Oceanography (SIO) data archives from more than 700 cruises going back 50 years, has now become the operational fully-searchable "SIOExplorer" digital library, complete with thousands of historic photographs, images, maps, full text documents, binary data files, and 3D visualization experiences, totaling nearly 2 terabytes of digital content. Coping with data diversity and complexity has proven to be more challenging than dealing with large volumes of digital data. SIOExplorer has been built with scalability in mind, so that the addition of new data types and entire new collections may be accomplished with ease. It is a federated system, currently interoperating with three independent data-publishing authorities, each responsible for their own quality control, metadata specifications, and content selection. The IT architecture implemented at the San Diego Supercomputer Center (SDSC) streamlines the integration of additional projects in other disciplines with a suite of metadata management and collection building tools for "arbitrary digital objects." Metadata are automatically harvested from data files into domain-specific metadata blocks, and mapped into various specification standards as needed. Metadata can be browsed and objects can be viewed onscreen or downloaded for further analysis, with automatic proprietary-hold request management.

Stop the Bleeding: the Development of a Tool to Streamline NASA Earth Science Metadata Curation Efforts

NASA Astrophysics Data System (ADS)

le Roux, J.; Baker, A.; Caltagirone, S.; Bugbee, K.

2017-12-01

The Common Metadata Repository (CMR) is a high-performance, high-quality repository for Earth science metadata records, and serves as the primary way to search NASA's growing 17.5 petabytes of Earth science data holdings. Released in 2015, CMR has the capability to support several different metadata standards already being utilized by NASA's combined network of Earth science data providers, or Distributed Active Archive Centers (DAACs). The Analysis and Review of CMR (ARC) Team located at Marshall Space Flight Center is working to improve the quality of records already in CMR with the goal of making records optimal for search and discovery. This effort entails a combination of automated and manual review, where each NASA record in CMR is checked for completeness, accuracy, and consistency. This effort is highly collaborative in nature, requiring communication and transparency of findings amongst NASA personnel, DAACs, the CMR team and other metadata curation teams. Through the evolution of this project it has become apparent that there is a need to document and report findings, as well as track metadata improvements in a more efficient manner. The ARC team has collaborated with Element 84 in order to develop a metadata curation tool to meet these needs. In this presentation, we will provide an overview of this metadata curation tool and its current capabilities. Challenges and future plans for the tool will also be discussed.

Efficient processing of MPEG-21 metadata in the binary domain

NASA Astrophysics Data System (ADS)

Timmerer, Christian; Frank, Thomas; Hellwagner, Hermann; Heuer, Jörg; Hutter, Andreas

2005-10-01

XML-based metadata is widely adopted across the different communities and plenty of commercial and open source tools for processing and transforming are available on the market. However, all of these tools have one thing in common: they operate on plain text encoded metadata which may become a burden in constrained and streaming environments, i.e., when metadata needs to be processed together with multimedia content on the fly. In this paper we present an efficient approach for transforming such kind of metadata which are encoded using MPEG's Binary Format for Metadata (BiM) without additional en-/decoding overheads, i.e., within the binary domain. Therefore, we have developed an event-based push parser for BiM encoded metadata which transforms the metadata by a limited set of processing instructions - based on traditional XML transformation techniques - operating on bit patterns instead of cost-intensive string comparisons.

Metadata management for high content screening in OMERO.

PubMed

Li, Simon; Besson, Sébastien; Blackburn, Colin; Carroll, Mark; Ferguson, Richard K; Flynn, Helen; Gillen, Kenneth; Leigh, Roger; Lindner, Dominik; Linkert, Melissa; Moore, William J; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Allan, Chris; Burel, Jean-Marie; Moore, Josh; Swedlow, Jason R

2016-03-01

High content screening (HCS) experiments create a classic data management challenge-multiple, large sets of heterogeneous structured and unstructured data, that must be integrated and linked to produce a set of "final" results. These different data include images, reagents, protocols, analytic output, and phenotypes, all of which must be stored, linked and made accessible for users, scientists, collaborators and where appropriate the wider community. The OME Consortium has built several open source tools for managing, linking and sharing these different types of data. The OME Data Model is a metadata specification that supports the image data and metadata recorded in HCS experiments. Bio-Formats is a Java library that reads recorded image data and metadata and includes support for several HCS screening systems. OMERO is an enterprise data management application that integrates image data, experimental and analytic metadata and makes them accessible for visualization, mining, sharing and downstream analysis. We discuss how Bio-Formats and OMERO handle these different data types, and how they can be used to integrate, link and share HCS experiments in facilities and public data repositories. OME specifications and software are open source and are available at https://www.openmicroscopy.org. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Advancements in Large-Scale Data/Metadata Management for Scientific Data.

NASA Astrophysics Data System (ADS)

Guntupally, K.; Devarakonda, R.; Palanisamy, G.; Frame, M. T.

2017-12-01

Scientific data often comes with complex and diverse metadata which are critical for data discovery and users. The Online Metadata Editor (OME) tool, which was developed by an Oak Ridge National Laboratory team, effectively manages diverse scientific datasets across several federal data centers, such as DOE's Atmospheric Radiation Measurement (ARM) Data Center and USGS's Core Science Analytics, Synthesis, and Libraries (CSAS&L) project. This presentation will focus mainly on recent developments and future strategies for refining OME tool within these centers. The ARM OME is a standard based tool (https://www.archive.arm.gov/armome) that allows scientists to create and maintain metadata about their data products. The tool has been improved with new workflows that help metadata coordinators and submitting investigators to submit and review their data more efficiently. The ARM Data Center's newly upgraded Data Discovery Tool (http://www.archive.arm.gov/discovery) uses rich metadata generated by the OME to enable search and discovery of thousands of datasets, while also providing a citation generator and modern order-delivery techniques like Globus (using GridFTP), Dropbox and THREDDS. The Data Discovery Tool also supports incremental indexing, which allows users to find new data as and when they are added. The USGS CSAS&L search catalog employs a custom version of the OME (https://www1.usgs.gov/csas/ome), which has been upgraded with high-level Federal Geographic Data Committee (FGDC) validations and the ability to reserve and mint Digital Object Identifiers (DOIs). The USGS's Science Data Catalog (SDC) (https://data.usgs.gov/datacatalog) allows users to discover a myriad of science data holdings through a web portal. Recent major upgrades to the SDC and ARM Data Discovery Tool include improved harvesting performance and migration using new search software, such as Apache Solr 6.0 for serving up data/metadata to scientific communities. Our presentation will highlight the future enhancements of these tools which enable users to retrieve fast search results, along with parallelizing the retrieval process from online and High Performance Storage Systems. In addition, these improvements to the tools will support additional metadata formats like the Large-Eddy Simulation (LES) ARM Symbiotic and Observation (LASSO) bundle data.

Improving Metadata Compliance for Earth Science Data Records

NASA Astrophysics Data System (ADS)

Armstrong, E. M.; Chang, O.; Foster, D.

2014-12-01

One of the recurring challenges of creating earth science data records is to ensure a consistent level of metadata compliance at the granule level where important details of contents, provenance, producer, and data references are necessary to obtain a sufficient level of understanding. These details are important not just for individual data consumers but also for autonomous software systems. Two of the most popular metadata standards at the granule level are the Climate and Forecast (CF) Metadata Conventions and the Attribute Conventions for Dataset Discovery (ACDD). Many data producers have implemented one or both of these models including the Group for High Resolution Sea Surface Temperature (GHRSST) for their global SST products and the Ocean Biology Processing Group for NASA ocean color and SST products. While both the CF and ACDD models contain various level of metadata richness, the actual "required" attributes are quite small in number. Metadata at the granule level becomes much more useful when recommended or optional attributes are implemented that document spatial and temporal ranges, lineage and provenance, sources, keywords, and references etc. In this presentation we report on a new open source tool to check the compliance of netCDF and HDF5 granules to the CF and ACCD metadata models. The tool, written in Python, was originally implemented to support metadata compliance for netCDF records as part of the NOAA's Integrated Ocean Observing System. It outputs standardized scoring for metadata compliance for both CF and ACDD, produces an objective summary weight, and can be implemented for remote records via OPeNDAP calls. Originally a command-line tool, we have extended it to provide a user-friendly web interface. Reports on metadata testing are grouped in hierarchies that make it easier to track flaws and inconsistencies in the record. We have also extended it to support explicit metadata structures and semantic syntax for the GHRSST project that can be easily adapted to other satellite missions as well. Overall, we hope this tool will provide the community with a useful mechanism to improve metadata quality and consistency at the granule level by providing objective scoring and assessment, as well as encourage data producers to improve metadata quality and quantity.

New Tools to Document and Manage Data/Metadata: Example NGEE Arctic and UrbIS

NASA Astrophysics Data System (ADS)

Crow, M. C.; Devarakonda, R.; Hook, L.; Killeffer, T.; Krassovski, M.; Boden, T.; King, A. W.; Wullschleger, S. D.

2016-12-01

Tools used for documenting, archiving, cataloging, and searching data are critical pieces of informatics. This discussion describes tools being used in two different projects at Oak Ridge National Laboratory (ORNL), but at different stages of the data lifecycle. The Metadata Entry and Data Search Tool is being used for the documentation, archival, and data discovery stages for the Next Generation Ecosystem Experiment - Arctic (NGEE Arctic) project while the Urban Information Systems (UrbIS) Data Catalog is being used to support indexing, cataloging, and searching. The NGEE Arctic Online Metadata Entry Tool [1] provides a method by which researchers can upload their data and provide original metadata with each upload. The tool is built upon a Java SPRING framework to parse user input into, and from, XML output. Many aspects of the tool require use of a relational database including encrypted user-login, auto-fill functionality for predefined sites and plots, and file reference storage and sorting. The UrbIS Data Catalog is a data discovery tool supported by the Mercury cataloging framework [2] which aims to compile urban environmental data from around the world into one location, and be searchable via a user-friendly interface. Each data record conveniently displays its title, source, and date range, and features: (1) a button for a quick view of the metadata, (2) a direct link to the data and, for some data sets, (3) a button for visualizing the data. The search box incorporates autocomplete capabilities for search terms and sorted keyword filters are available on the side of the page, including a map for searching by area. References: [1] Devarakonda, Ranjeet, et al. "Use of a metadata documentation and search tool for large data volumes: The NGEE arctic example." Big Data (Big Data), 2015 IEEE International Conference on. IEEE, 2015. [2] Devarakonda, R., Palanisamy, G., Wilson, B. E., & Green, J. M. (2010). Mercury: reusable metadata management, data discovery and access system. Earth Science Informatics, 3(1-2), 87-94.

Visualization of JPEG Metadata

NASA Astrophysics Data System (ADS)

Malik Mohamad, Kamaruddin; Deris, Mustafa Mat

There are a lot of information embedded in JPEG image than just graphics. Visualization of its metadata would benefit digital forensic investigator to view embedded data including corrupted image where no graphics can be displayed in order to assist in evidence collection for cases such as child pornography or steganography. There are already available tools such as metadata readers, editors and extraction tools but mostly focusing on visualizing attribute information of JPEG Exif. However, none have been done to visualize metadata by consolidating markers summary, header structure, Huffman table and quantization table in a single program. In this paper, metadata visualization is done by developing a program that able to summarize all existing markers, header structure, Huffman table and quantization table in JPEG. The result shows that visualization of metadata helps viewing the hidden information within JPEG more easily.

Computational Unification: a Vision for Connecting Researchers

NASA Astrophysics Data System (ADS)

Troy, R. M.; Kingrey, O. J.

2002-12-01

Computational Unification of science, once only a vision, is becoming a reality. This technology is based upon a scientifically defensible, general solution for Earth Science data management and processing. The computational unification of science offers a real opportunity to foster inter and intra-discipline cooperation, and the end of 're-inventing the wheel'. As we move forward using computers as tools, it is past time to move from computationally isolating, "one-off" or discipline-specific solutions into a unified framework where research can be more easily shared, especially with researchers in other disciplines. The author will discuss how distributed meta-data, distributed processing and distributed data objects are structured to constitute a working interdisciplinary system, including how these resources lead to scientific defensibility through known lineage of all data products. Illustration of how scientific processes are encapsulated and executed illuminates how previously written processes and functions are integrated into the system efficiently and with minimal effort. Meta-data basics will illustrate how intricate relationships may easily be represented and used to good advantage. Retrieval techniques will be discussed including trade-offs of using meta-data versus embedded data, how the two may be integrated, and how simplifying assumptions may or may not help. This system is based upon the experience of the Sequoia 2000 and BigSur research projects at the University of California, Berkeley, whose goals were to find an alternative to the Hughes EOS-DIS system and is presently offered by Science Tools corporation, of which the author is a principal.

An Overview of Tools for Creating, Validating and Using PDS Metadata

NASA Astrophysics Data System (ADS)

King, T. A.; Hardman, S. H.; Padams, J.; Mafi, J. N.; Cecconi, B.

2017-12-01

NASA's Planetary Data System (PDS) has defined information models for creating metadata to describe bundles, collections and products for all the assets acquired by a planetary science projects. Version 3 of the PDS Information Model (commonly known as "PDS3") is widely used and is used to describe most of the existing planetary archive. Recently PDS has released version 4 of the Information Model (commonly known as "PDS4") which is designed to improve consistency, efficiency and discoverability of information. To aid in creating, validating and using PDS4 metadata the PDS and a few associated groups have developed a variety of tools. In addition, some commercial tools, both free and for a fee, can be used to create and work with PDS4 metadata. We present an overview of these tools, describe those tools currently under development and provide guidance as to which tools may be most useful for missions, instrument teams and the individual researcher.

Lightweight Advertising and Scalable Discovery of Services, Datasets, and Events Using Feedcasts

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Ramachandran, R.; Movva, S.

2010-12-01

Broadcast feeds (Atom or RSS) are a mechanism for advertising the existence of new data objects on the web, with metadata and links to further information. Users then subscribe to the feed to receive updates. This concept has already been used to advertise the new granules of science data as they are produced (datacasting), with browse images and metadata, and to advertise bundles of web services (service casting). Structured metadata is introduced into the XML feed format by embedding new XML tags (in defined namespaces), using typed links, and reusing built-in Atom feed elements. This “infocasting” concept can be extended to include many other science artifacts, including data collections, workflow documents, topical geophysical events (hurricanes, forest fires, etc.), natural hazard warnings, and short articles describing a new science result. The common theme is that each infocast contains machine-readable, structured metadata describing the object and enabling further manipulation. For example, service casts contain type links pointing to the service interface description (e.g., WSDL for SOAP services), service endpoint, and human-readable documentation. Our Infocasting project has three main goals: (1) define and evangelize micro-formats (metadata standards) so that providers can easily advertise their web services, datasets, and topical geophysical events by adding structured information to broadcast feeds; (2) develop authoring tools so that anyone can easily author such service advertisements, data casts, and event descriptions; and (3) provide a one-stop, Google-like search box in the browser that allows discovery of service, data and event casts visible on the web, and services & data registered in the GEOSS repository and other NASA repositories (GCMD & ECHO). To demonstrate the event casting idea, a series of micro-articles—with accompanying event casts containing links to relevant datasets, web services, and science analysis workflows--will be authored for several kinds of geophysical events, such as hurricanes, smoke plume events, tsunamis, etc. The talk will describe our progress so far, and some of the issues with leveraging existing metadata standards to define lightweight micro-formats.

Metadata Evaluation and Improvement: Evolving Analysis and Reporting

NASA Technical Reports Server (NTRS)

Habermann, Ted; Kozimor, John; Gordon, Sean

2017-01-01

ESIP Community members create and manage a large collection of environmental datasets that span multiple decades, the entire globe, and many parts of the solar system. Metadata are critical for discovering, accessing, using and understanding these data effectively and ESIP community members have successfully created large collections of metadata describing these data. As part of the White House Big Earth Data Initiative (BEDI), ESDIS has developed a suite of tools for evaluating these metadata in native dialects with respect to recommendations from many organizations. We will describe those tools and demonstrate evolving techniques for sharing results with data providers.

A model for enhancing Internet medical document retrieval with "medical core metadata".

PubMed

Malet, G; Munoz, F; Appleyard, R; Hersh, W

1999-01-01

Finding documents on the World Wide Web relevant to a specific medical information need can be difficult. The goal of this work is to define a set of document content description tags, or metadata encodings, that can be used to promote disciplined search access to Internet medical documents. The authors based their approach on a proposed metadata standard, the Dublin Core Metadata Element Set, which has recently been submitted to the Internet Engineering Task Force. Their model also incorporates the National Library of Medicine's Medical Subject Headings (MeSH) vocabulary and MEDLINE-type content descriptions. The model defines a medical core metadata set that can be used to describe the metadata for a wide variety of Internet documents. The authors propose that their medical core metadata set be used to assign metadata to medical documents to facilitate document retrieval by Internet search engines.

ASDC Collaborations and Processes to Ensure Quality Metadata and Consistent Data Availability

NASA Astrophysics Data System (ADS)

Trapasso, T. J.

2017-12-01

With the introduction of new tools, faster computing, and less expensive storage, increased volumes of data are expected to be managed with existing or fewer resources. Metadata management is becoming a heightened challenge from the increase in data volume, resulting in more metadata records needed to be curated for each product. To address metadata availability and completeness, NASA ESDIS has taken significant strides with the creation of the United Metadata Model (UMM) and Common Metadata Repository (CMR). These UMM helps address hurdles experienced by the increasing number of metadata dialects and the CMR provides a primary repository for metadata so that required metadata fields can be served through a growing number of tools and services. However, metadata quality remains an issue as metadata is not always inherent to the end-user. In response to these challenges, the NASA Atmospheric Science Data Center (ASDC) created the Collaboratory for quAlity Metadata Preservation (CAMP) and defined the Product Lifecycle Process (PLP) to work congruently. CAMP is unique in that it provides science team members a UI to directly supply metadata that is complete, compliant, and accurate for their data products. This replaces back-and-forth communication that often results in misinterpreted metadata. Upon review by ASDC staff, metadata is submitted to CMR for broader distribution through Earthdata. Further, approval of science team metadata in CAMP automatically triggers the ASDC PLP workflow to ensure appropriate services are applied throughout the product lifecycle. This presentation will review the design elements of CAMP and PLP as well as demonstrate interfaces to each. It will show the benefits that CAMP and PLP provide to the ASDC that could potentially benefit additional NASA Earth Science Data and Information System (ESDIS) Distributed Active Archive Centers (DAACs).

Documentation Resources on the ESIP Wiki

NASA Technical Reports Server (NTRS)

Habermann, Ted; Kozimor, John; Gordon, Sean

2017-01-01

The ESIP community includes data providers and users that communicate with one another through datasets and metadata that describe them. Improving this communication depends on consistent high-quality metadata. The ESIP Documentation Cluster and the wiki play an important central role in facilitating this communication. We will describe and demonstrate sections of the wiki that provide information about metadata concept definitions, metadata recommendation, metadata dialects, and guidance pages. We will also describe and demonstrate the ISO Explorer, a tool that the community is developing to help metadata creators.

Federal Data Repository Research: Recent Developments in Mercury Search System Architecture

NASA Astrophysics Data System (ADS)

Devarakonda, R.

2015-12-01

New data intensive project initiatives needs new generation data system architecture. This presentation will discuss the recent developments in Mercury System [1] including adoption, challenges, and future efforts to handle such data intensive projects. Mercury is a combination of three main tools (i) Data/Metadata registration Tool (Online Metadata Editor): The new Online Metadata Editor (OME) is a web-based tool to help document the scientific data in a well-structured, popular scientific metadata formats. (ii) Search and Visualization Tool: Provides a single portal to information contained in disparate data management systems. It facilitates distributed metadata management, data discovery, and various visuzalization capabilities. (iii) Data Citation Tool: In collaboration with Department of Energy's Oak Ridge National Laboratory (ORNL) Mercury Consortium (funded by NASA, USGS and DOE), established a Digital Object Identifier (DOI) service. Mercury is a open source system, developed and managed at Oak Ridge National Laboratory and is currently being funded by three federal agencies, including NASA, USGS and DOE. It provides access to millions of bio-geo-chemical and ecological data; 30,000 scientists use it each month. Some recent data intensive projects that are using Mercury tool: USGS Science Data Catalog (http://data.usgs.gov/), Next-Generation Ecosystem Experiments (http://ngee-arctic.ornl.gov/), Carbon Dioxide Information Analysis Center (http://cdiac.ornl.gov/), Oak Ridge National Laboratory - Distributed Active Archive Center (http://daac.ornl.gov), SoilSCAPE (http://mercury.ornl.gov/soilscape). References: [1] Devarakonda, Ranjeet, et al. "Mercury: reusable metadata management, data discovery and access system." Earth Science Informatics 3.1-2 (2010): 87-94.

Assisted editing od SensorML with EDI. A bottom-up scenario towards the definition of sensor profiles.

NASA Astrophysics Data System (ADS)

Oggioni, Alessandro; Tagliolato, Paolo; Fugazza, Cristiano; Bastianini, Mauro; Pavesi, Fabio; Pepe, Monica; Menegon, Stefano; Basoni, Anna; Carrara, Paola

2015-04-01

Sensor observation systems for environmental data have become increasingly important in the last years. The EGU's Informatics in Oceanography and Ocean Science track stressed the importance of management tools and solutions for marine infrastructures. We think that full interoperability among sensor systems is still an open issue and that the solution to this involves providing appropriate metadata. Several open source applications implement the SWE specification and, particularly, the Sensor Observation Services (SOS) standard. These applications allow for the exchange of data and metadata in XML format between computer systems. However, there is a lack of metadata editing tools supporting end users in this activity. Generally speaking, it is hard for users to provide sensor metadata in the SensorML format without dedicated tools. In particular, such a tool should ease metadata editing by providing, for standard sensors, all the invariant information to be included in sensor metadata, thus allowing the user to concentrate on the metadata items that are related to the specific deployment. RITMARE, the Italian flagship project on marine research, envisages a subproject, SP7, for the set-up of the project's spatial data infrastructure. SP7 developed EDI, a general purpose, template-driven metadata editor that is composed of a backend web service and an HTML5/javascript client. EDI can be customized for managing the creation of generic metadata encoded as XML. Once tailored to a specific metadata format, EDI presents the users a web form with advanced auto completion and validation capabilities. In the case of sensor metadata (SensorML versions 1.0.1 and 2.0), the EDI client is instructed to send an "insert sensor" request to an SOS endpoint in order to save the metadata in an SOS server. In the first phase of project RITMARE, EDI has been used to simplify the creation from scratch of SensorML metadata by the involved researchers and data managers. An interesting by-product of this ongoing work is currently constituting an archive of predefined sensor descriptions. This information is being collected in order to further ease metadata creation in the next phase of the project. Users will be able to choose among a number of sensor and sensor platform prototypes: These will be specific instances on which it will be possible to define, in a bottom-up approach, "sensor profiles". We report on the outcome of this activity.

The XML Metadata Editor of GFZ Data Services

NASA Astrophysics Data System (ADS)

Ulbricht, Damian; Elger, Kirsten; Tesei, Telemaco; Trippanera, Daniele

2017-04-01

Following the FAIR data principles, research data should be Findable, Accessible, Interoperable and Reuseable. Publishing data under these principles requires to assign persistent identifiers to the data and to generate rich machine-actionable metadata. To increase the interoperability, metadata should include shared vocabularies and crosslink the newly published (meta)data and related material. However, structured metadata formats tend to be complex and are not intended to be generated by individual scientists. Software solutions are needed that support scientists in providing metadata describing their data. To facilitate data publication activities of 'GFZ Data Services', we programmed an XML metadata editor that assists scientists to create metadata in different schemata popular in the earth sciences (ISO19115, DIF, DataCite), while being at the same time usable by and understandable for scientists. Emphasis is placed on removing barriers, in particular the editor is publicly available on the internet without registration [1] and the scientists are not requested to provide information that may be generated automatically (e.g. the URL of a specific licence or the contact information of the metadata distributor). Metadata are stored in browser cookies and a copy can be saved to the local hard disk. To improve usability, form fields are translated into the scientific language, e.g. 'creators' of the DataCite schema are called 'authors'. To assist filling in the form, we make use of drop down menus for small vocabulary lists and offer a search facility for large thesauri. Explanations to form fields and definitions of vocabulary terms are provided in pop-up windows and a full documentation is available for download via the help menu. In addition, multiple geospatial references can be entered via an interactive mapping tool, which helps to minimize problems with different conventions to provide latitudes and longitudes. Currently, we are extending the metadata editor to be reused to generate metadata for data discovery and contextual metadata developed by the 'Multi-scale Laboratories' Thematic Core Service of the European Plate Observing System (EPOS-IP). The Editor will be used to build a common repository of a large variety of geological and geophysical datasets produced by multidisciplinary laboratories throughout Europe, thus contributing to a significant step toward the integration and accessibility of earth science data. This presentation will introduce the metadata editor and show the adjustments made for EPOS-IP. [1] http://dataservices.gfz-potsdam.de/panmetaworks/metaedit

Metabolonote: A Wiki-Based Database for Managing Hierarchical Metadata of Metabolome Analyses

PubMed Central

Ara, Takeshi; Enomoto, Mitsuo; Arita, Masanori; Ikeda, Chiaki; Kera, Kota; Yamada, Manabu; Nishioka, Takaaki; Ikeda, Tasuku; Nihei, Yoshito; Shibata, Daisuke; Kanaya, Shigehiko; Sakurai, Nozomu

2015-01-01

Metabolomics – technology for comprehensive detection of small molecules in an organism – lags behind the other “omics” in terms of publication and dissemination of experimental data. Among the reasons for this are difficulty precisely recording information about complicated analytical experiments (metadata), existence of various databases with their own metadata descriptions, and low reusability of the published data, resulting in submitters (the researchers who generate the data) being insufficiently motivated. To tackle these issues, we developed Metabolonote, a Semantic MediaWiki-based database designed specifically for managing metabolomic metadata. We also defined a metadata and data description format, called “Togo Metabolome Data” (TogoMD), with an ID system that is required for unique access to each level of the tree-structured metadata such as study purpose, sample, analytical method, and data analysis. Separation of the management of metadata from that of data and permission to attach related information to the metadata provide advantages for submitters, readers, and database developers. The metadata are enriched with information such as links to comparable data, thereby functioning as a hub of related data resources. They also enhance not only readers’ understanding and use of data but also submitters’ motivation to publish the data. The metadata are computationally shared among other systems via APIs, which facilitate the construction of novel databases by database developers. A permission system that allows publication of immature metadata and feedback from readers also helps submitters to improve their metadata. Hence, this aspect of Metabolonote, as a metadata preparation tool, is complementary to high-quality and persistent data repositories such as MetaboLights. A total of 808 metadata for analyzed data obtained from 35 biological species are published currently. Metabolonote and related tools are available free of cost at http://metabolonote.kazusa.or.jp/. PMID:25905099

Metabolonote: a wiki-based database for managing hierarchical metadata of metabolome analyses.

PubMed

Ara, Takeshi; Enomoto, Mitsuo; Arita, Masanori; Ikeda, Chiaki; Kera, Kota; Yamada, Manabu; Nishioka, Takaaki; Ikeda, Tasuku; Nihei, Yoshito; Shibata, Daisuke; Kanaya, Shigehiko; Sakurai, Nozomu

2015-01-01

Metabolomics - technology for comprehensive detection of small molecules in an organism - lags behind the other "omics" in terms of publication and dissemination of experimental data. Among the reasons for this are difficulty precisely recording information about complicated analytical experiments (metadata), existence of various databases with their own metadata descriptions, and low reusability of the published data, resulting in submitters (the researchers who generate the data) being insufficiently motivated. To tackle these issues, we developed Metabolonote, a Semantic MediaWiki-based database designed specifically for managing metabolomic metadata. We also defined a metadata and data description format, called "Togo Metabolome Data" (TogoMD), with an ID system that is required for unique access to each level of the tree-structured metadata such as study purpose, sample, analytical method, and data analysis. Separation of the management of metadata from that of data and permission to attach related information to the metadata provide advantages for submitters, readers, and database developers. The metadata are enriched with information such as links to comparable data, thereby functioning as a hub of related data resources. They also enhance not only readers' understanding and use of data but also submitters' motivation to publish the data. The metadata are computationally shared among other systems via APIs, which facilitate the construction of novel databases by database developers. A permission system that allows publication of immature metadata and feedback from readers also helps submitters to improve their metadata. Hence, this aspect of Metabolonote, as a metadata preparation tool, is complementary to high-quality and persistent data repositories such as MetaboLights. A total of 808 metadata for analyzed data obtained from 35 biological species are published currently. Metabolonote and related tools are available free of cost at http://metabolonote.kazusa.or.jp/.

Explorative Analyses of Nursing Research Data.

PubMed

Kim, Hyeoneui; Jang, Imho; Quach, Jimmy; Richardson, Alex; Kim, Jaemin; Choi, Jeeyae

2016-10-26

As a first step of pursuing the vision of "big data science in nursing," we described the characteristics of nursing research data reported in 194 published nursing studies. We also explored how completely the Version 1 metadata specification of biomedical and healthCAre Data Discovery Index Ecosystem (bioCADDIE) represents these metadata. The metadata items of the nursing studies were all related to one or more of the bioCADDIE metadata entities. However, values of many metadata items of the nursing studies were not sufficiently represented through the bioCADDIE metadata. This was partly due to the differences in the scope of the content that the bioCADDIE metadata are designed to represent. The 194 nursing studies reported a total of 1,181 unique data items, the majority of which take non-numeric values. This indicates the importance of data standardization to enable the integrative analyses of these data to support big data science in nursing. © The Author(s) 2016.

A Model for Enhancing Internet Medical Document Retrieval with “Medical Core Metadata”

PubMed Central

Malet, Gary; Munoz, Felix; Appleyard, Richard; Hersh, William

1999-01-01

Objective: Finding documents on the World Wide Web relevant to a specific medical information need can be difficult. The goal of this work is to define a set of document content description tags, or metadata encodings, that can be used to promote disciplined search access to Internet medical documents. Design: The authors based their approach on a proposed metadata standard, the Dublin Core Metadata Element Set, which has recently been submitted to the Internet Engineering Task Force. Their model also incorporates the National Library of Medicine's Medical Subject Headings (MeSH) vocabulary and Medline-type content descriptions. Results: The model defines a medical core metadata set that can be used to describe the metadata for a wide variety of Internet documents. Conclusions: The authors propose that their medical core metadata set be used to assign metadata to medical documents to facilitate document retrieval by Internet search engines. PMID:10094069

Simplifying the Reuse and Interoperability of Geoscience Data Sets and Models with Semantic Metadata that is Human-Readable and Machine-actionable

NASA Astrophysics Data System (ADS)

Peckham, S. D.

2017-12-01

Standardized, deep descriptions of digital resources (e.g. data sets, computational models, software tools and publications) make it possible to develop user-friendly software systems that assist scientists with the discovery and appropriate use of these resources. Semantic metadata makes it possible for machines to take actions on behalf of humans, such as automatically identifying the resources needed to solve a given problem, retrieving them and then automatically connecting them (despite their heterogeneity) into a functioning workflow. Standardized model metadata also helps model users to understand the important details that underpin computational models and to compare the capabilities of different models. These details include simplifying assumptions on the physics, governing equations and the numerical methods used to solve them, discretization of space (the grid) and time (the time-stepping scheme), state variables (input or output), model configuration parameters. This kind of metadata provides a "deep description" of a computational model that goes well beyond other types of metadata (e.g. author, purpose, scientific domain, programming language, digital rights, provenance, execution) and captures the science that underpins a model. A carefully constructed, unambiguous and rules-based schema to address this problem, called the Geoscience Standard Names ontology will be presented that utilizes Semantic Web best practices and technologies. It has also been designed to work across science domains and to be readable by both humans and machines.

Using bio.tools to generate and annotate workbench tool descriptions

PubMed Central

Hillion, Kenzo-Hugo; Kuzmin, Ivan; Khodak, Anton; Rasche, Eric; Crusoe, Michael; Peterson, Hedi; Ison, Jon; Ménager, Hervé

2017-01-01

Workbench and workflow systems such as Galaxy, Taverna, Chipster, or Common Workflow Language (CWL)-based frameworks, facilitate the access to bioinformatics tools in a user-friendly, scalable and reproducible way. Still, the integration of tools in such environments remains a cumbersome, time consuming and error-prone process. A major consequence is the incomplete or outdated description of tools that are often missing important information, including parameters and metadata such as publication or links to documentation. ToolDog (Tool DescriptiOn Generator) facilitates the integration of tools - which have been registered in the ELIXIR tools registry (https://bio.tools) - into workbench environments by generating tool description templates. ToolDog includes two modules. The first module analyses the source code of the bioinformatics software with language-specific plugins, and generates a skeleton for a Galaxy XML or CWL tool description. The second module is dedicated to the enrichment of the generated tool description, using metadata provided by bio.tools. This last module can also be used on its own to complete or correct existing tool descriptions with missing metadata. PMID:29333231

Serving Fisheries and Ocean Metadata to Communities Around the World

NASA Technical Reports Server (NTRS)

Meaux, Melanie

2006-01-01

NASA's Global Change Master Directory (GCMD) assists the oceanographic community in the discovery, access, and sharing of scientific data by serving on-line fisheries and ocean metadata to users around the globe. As of January 2006, the directory holds more than 16,300 Earth Science data descriptions and over 1,300 services descriptions. Of these, nearly 4,000 unique ocean-related metadata records are available to the public, with many having direct links to the data. In 2005, the GCMD averaged over 5 million hits a month, with nearly a half million unique hosts for the year. Through the GCMD portal (http://qcrnd.nasa.qov/), users can search vast and growing quantities of data and services using controlled keywords, free-text searches or a combination of both. Users may now refine a search based on topic, location, instrument, platform, project, data center, spatial and temporal coverage. The directory also offers data holders a means to post and search their data through customized portals, i.e. online customized subset metadata directories. The discovery metadata standard used is the Directory Interchange Format (DIF), adopted in 1994. This format has evolved to accommodate other national and international standards such as FGDC and IS019115. Users can submit metadata through easy-to-use online and offline authoring tools. The directory, which also serves as a coordinating node of the International Directory Network (IDN), has been active at the international, regional and national level for many years through its involvement with the Committee on Earth Observation Satellites (CEOS), federal agencies (such as NASA, NOAA, and USGS), international agencies (such as IOC/IODE, UN, and JAXA) and partnerships (such as ESIP, IOOS/DMAC, GOSIC, GLOBEC, OBIS, and GoMODP), sharing experience, knowledge related to metadata and/or data management and interoperability.

Challenges to Standardization: A Case Study Using Coastal and Deep-Ocean Water Level Data

NASA Astrophysics Data System (ADS)

Sweeney, A. D.; Stroker, K. J.; Mungov, G.; McLean, S. J.

2015-12-01

Sea levels recorded at coastal stations and inferred from deep-ocean pressure observations at the seafloor are submitted for archive in multiple data and metadata formats. These formats include two forms of schema-less XML and a custom binary format accompanied by metadata in a spreadsheet. The authors report on efforts to use existing standards to make this data more discoverable and more useful beyond their initial use in detecting tsunamis. An initial review of data formats for sea level data around the globe revealed heterogeneity in presentation and content. In the absence of a widely-used domain-specific format, we adopted the general model for structuring data and metadata expressed by the Network Common Data Form (netCDF). netCDF has been endorsed by the Open Geospatial Consortium and has the advantages of small size when compared to equivalent plain text representation and provides a standard way of embedding metadata in the same file. We followed the orthogonal time-series profile of the Climate and Forecast discrete sampling geometries as the convention for structuring the data and describing metadata relevant for use. We adhered to the Attribute Convention for Data Discovery for capturing metadata to support user search. Beyond making it possible to structure data and metadata in a standard way, netCDF is supported by multiple software tools in providing programmatic cataloging, access, subsetting, and transformation to other formats. We will describe our successes and failures in adhering to existing standards and provide requirements for either augmenting existing conventions or developing new ones. Some of these enhancements are specific to sea level data, while others are applicable to time-series data in general.

Metadata Realities for Cyberinfrastructure: Data Authors as Metadata Creators

ERIC Educational Resources Information Center

Mayernik, Matthew Stephen

2011-01-01

As digital data creation technologies become more prevalent, data and metadata management are necessary to make data available, usable, sharable, and storable. Researchers in many scientific settings, however, have little experience or expertise in data and metadata management. In this dissertation, I explore the everyday data and metadata…

Making Interoperability Easier with NASA's Metadata Management Tool (MMT)

NASA Technical Reports Server (NTRS)

Shum, Dana; Reese, Mark; Pilone, Dan; Baynes, Katie

2016-01-01

While the ISO-19115 collection level metadata format meets many users' needs for interoperable metadata, it can be cumbersome to create it correctly. Through the MMT's simple UI experience, metadata curators can create and edit collections which are compliant with ISO-19115 without full knowledge of the NASA Best Practices implementation of ISO-19115 format. Users are guided through the metadata creation process through a forms-based editor, complete with field information, validation hints and picklists. Once a record is completed, users can download the metadata in any of the supported formats with just 2 clicks.

Enhancing SCORM Metadata for Assessment Authoring in E-Learning

ERIC Educational Resources Information Center

Chang, Wen-Chih; Hsu, Hui-Huang; Smith, Timothy K.; Wang, Chun-Chia

2004-01-01

With the rapid development of distance learning and the XML technology, metadata play an important role in e-Learning. Nowadays, many distance learning standards, such as SCORM, AICC CMI, IEEE LTSC LOM and IMS, use metadata to tag learning materials. However, most metadata models are used to define learning materials and test problems. Few…

EXTRACT: interactive extraction of environment metadata and term suggestion for metagenomic sample annotation.

PubMed

Pafilis, Evangelos; Buttigieg, Pier Luigi; Ferrell, Barbra; Pereira, Emiliano; Schnetzer, Julia; Arvanitidis, Christos; Jensen, Lars Juhl

2016-01-01

The microbial and molecular ecology research communities have made substantial progress on developing standards for annotating samples with environment metadata. However, sample manual annotation is a highly labor intensive process and requires familiarity with the terminologies used. We have therefore developed an interactive annotation tool, EXTRACT, which helps curators identify and extract standard-compliant terms for annotation of metagenomic records and other samples. Behind its web-based user interface, the system combines published methods for named entity recognition of environment, organism, tissue and disease terms. The evaluators in the BioCreative V Interactive Annotation Task found the system to be intuitive, useful, well documented and sufficiently accurate to be helpful in spotting relevant text passages and extracting organism and environment terms. Comparison of fully manual and text-mining-assisted curation revealed that EXTRACT speeds up annotation by 15-25% and helps curators to detect terms that would otherwise have been missed. Database URL: https://extract.hcmr.gr/. © The Author(s) 2016. Published by Oxford University Press.

Predicting structured metadata from unstructured metadata.

PubMed

Posch, Lisa; Panahiazar, Maryam; Dumontier, Michel; Gevaert, Olivier

2016-01-01

Enormous amounts of biomedical data have been and are being produced by investigators all over the world. However, one crucial and limiting factor in data reuse is accurate, structured and complete description of the data or data about the data-defined as metadata. We propose a framework to predict structured metadata terms from unstructured metadata for improving quality and quantity of metadata, using the Gene Expression Omnibus (GEO) microarray database. Our framework consists of classifiers trained using term frequency-inverse document frequency (TF-IDF) features and a second approach based on topics modeled using a Latent Dirichlet Allocation model (LDA) to reduce the dimensionality of the unstructured data. Our results on the GEO database show that structured metadata terms can be the most accurately predicted using the TF-IDF approach followed by LDA both outperforming the majority vote baseline. While some accuracy is lost by the dimensionality reduction of LDA, the difference is small for elements with few possible values, and there is a large improvement over the majority classifier baseline. Overall this is a promising approach for metadata prediction that is likely to be applicable to other datasets and has implications for researchers interested in biomedical metadata curation and metadata prediction. © The Author(s) 2016. Published by Oxford University Press.

Describing environmental public health data: implementing a descriptive metadata standard on the environmental public health tracking network.

PubMed

Patridge, Jeff; Namulanda, Gonza

2008-01-01

The Environmental Public Health Tracking (EPHT) Network provides an opportunity to bring together diverse environmental and health effects data by integrating}?> local, state, and national databases of environmental hazards, environmental exposures, and health effects. To help users locate data on the EPHT Network, the network will utilize descriptive metadata that provide critical information as to the purpose, location, content, and source of these data. Since 2003, the Centers for Disease Control and Prevention's EPHT Metadata Subgroup has been working to initiate the creation and use of descriptive metadata. Efforts undertaken by the group include the adoption of a metadata standard, creation of an EPHT-specific metadata profile, development of an open-source metadata creation tool, and promotion of the creation of descriptive metadata by changing the perception of metadata in the public health culture.

Data System Architectures: Recent Experiences from Data Intensive Projects

NASA Astrophysics Data System (ADS)

Palanisamy, G.; Frame, M. T.; Boden, T.; Devarakonda, R.; Zolly, L.; Hutchison, V.; Latysh, N.; Krassovski, M.; Killeffer, T.; Hook, L.

2014-12-01

U.S. Federal agencies are frequently trying to address new data intensive projects that require next generation of data system architectures. This presentation will focus on two new such architectures: USGS's Science Data Catalog (SDC) and DOE's Next Generation Ecological Experiments - Arctic Data System. The U.S. Geological Survey (USGS) developed a Science Data Catalog (data.usgs.gov) to include records describing datasets, data collections, and observational or remotely-sensed data. The system was built using service oriented architecture and allows USGS scientists and data providers to create and register their data using either a standards-based metadata creation form or simply to register their already-created metadata records with the USGS SDC Dashboard. This dashboard then compiles the harvested metadata records and sends them to the post processing and indexing service using the JSON format. The post processing service, with the help of various ontologies and other geo-spatial validation services, auto-enhances these harvested metadata records and creates a Lucene index using the Solr enterprise search platform. Ultimately, metadata is made available via the SDC search interface. DOE's Next Generation Ecological Experiments (NGEE) Arctic project deployed a data system that allows scientists to prepare, publish, archive, and distribute data from field collections, lab experiments, sensors, and simulated modal outputs. This architecture includes a metadata registration form, data uploading and sharing tool, a Digital Object Identifier (DOI) tool, a Drupal based content management tool (http://ngee-arctic.ornl.gov), and a data search and access tool based on ORNL's Mercury software (http://mercury.ornl.gov). The team also developed Web-metric tools and a data ingest service to visualize geo-spatial and temporal observations.

Improvements to the Ontology-based Metadata Portal for Unified Semantics (OlyMPUS)

NASA Astrophysics Data System (ADS)

Linsinbigler, M. A.; Gleason, J. L.; Huffer, E.

2016-12-01

The Ontology-based Metadata Portal for Unified Semantics (OlyMPUS), funded by the NASA Earth Science Technology Office Advanced Information Systems Technology program, is an end-to-end system designed to support Earth Science data consumers and data providers, enabling the latter to register data sets and provision them with the semantically rich metadata that drives the Ontology-Driven Interactive Search Environment for Earth Sciences (ODISEES). OlyMPUS complements the ODISEES' data discovery system with an intelligent tool to enable data producers to auto-generate semantically enhanced metadata and upload it to the metadata repository that drives ODISEES. Like ODISEES, the OlyMPUS metadata provisioning tool leverages robust semantics, a NoSQL database and query engine, an automated reasoning engine that performs first- and second-order deductive inferencing, and uses a controlled vocabulary to support data interoperability and automated analytics. The ODISEES data discovery portal leverages this metadata to provide a seamless data discovery and access experience for data consumers who are interested in comparing and contrasting the multiple Earth science data products available across NASA data centers. Olympus will support scientists' services and tools for performing complex analyses and identifying correlations and non-obvious relationships across all types of Earth System phenomena using the full spectrum of NASA Earth Science data available. By providing an intelligent discovery portal that supplies users - both human users and machines - with detailed information about data products, their contents and their structure, ODISEES will reduce the level of effort required to identify and prepare large volumes of data for analysis. This poster will explain how OlyMPUS leverages deductive reasoning and other technologies to create an integrated environment for generating and exploiting semantically rich metadata.

Sentence-Based Metadata: An Approach and Tool for Viewing Database Designs.

ERIC Educational Resources Information Center

Boyle, John M.; Gunge, Jakob; Bryden, John; Librowski, Kaz; Hanna, Hsin-Yi

2002-01-01

Describes MARS (Museum Archive Retrieval System), a research tool which enables organizations to exchange digital images and documents by means of a common thesaurus structure, and merge the descriptive data and metadata of their collections. Highlights include theoretical basis; searching the MARS database; and examples in European museums.…

Viewing and Editing Earth Science Metadata MOBE: Metadata Object Browser and Editor in Java

NASA Astrophysics Data System (ADS)

Chase, A.; Helly, J.

2002-12-01

Metadata is an important, yet often neglected aspect of successful archival efforts. However, to generate robust, useful metadata is often a time consuming and tedious task. We have been approaching this problem from two directions: first by automating metadata creation, pulling from known sources of data, and in addition, what this (paper/poster?) details, developing friendly software for human interaction with the metadata. MOBE and COBE(Metadata Object Browser and Editor, and Canonical Object Browser and Editor respectively), are Java applications for editing and viewing metadata and digital objects. MOBE has already been designed and deployed, currently being integrated into other areas of the SIOExplorer project. COBE is in the design and development stage, being created with the same considerations in mind as those for MOBE. Metadata creation, viewing, data object creation, and data object viewing, when taken on a small scale are all relatively simple tasks. Computer science however, has an infamous reputation for transforming the simple into complex. As a system scales upwards to become more robust, new features arise and additional functionality is added to the software being written to manage the system. The software that emerges from such an evolution, though powerful, is often complex and difficult to use. With MOBE the focus is on a tool that does a small number of tasks very well. The result has been an application that enables users to manipulate metadata in an intuitive and effective way. This allows for a tool that serves its purpose without introducing additional cognitive load onto the user, an end goal we continue to pursue.

A study of diverse clinical decision support rule authoring environments and requirements for integration

PubMed Central

2012-01-01

Background Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs), Software Engineers (SEs), and Subject Matter Experts (SMEs) to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE) in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. Methods The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. Results While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS) interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. Conclusions A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR) systems, testing, and reporting. PMID:23145874

Defining linkages between the GSC and NSF's LTER program: How the Ecological Metadata Language (EML) relates to GCDML and other outcomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Inigo, Gil San; Servilla, Mark; Brunt, James

2008-06-01

The Genomic Standards Consortium (GSC) invited a representative of the Long-Term Ecological Research (LTER) to its fifth workshop to present the Ecological Metadata Language (EML) metadata standard and its relationship to the Minimum Information about a Genome/Metagenome Sequence (MIGS/MIMS) and its implementation, the Genomic Contextual Data Markup Language (GCDML). The LTER is one of the top National Science Foundation (NSF) programs in biology since 1980, representing diverse ecosystems and creating long-term, interdisciplinary research, synthesis of information, and theory. The adoption of EML as the LTER network standard has been key to build network synthesis architectures based on high-quality standardized metadata.more » EML is the NSF-recognized metadata standard for LTER, and EML is a criteria used to review the LTER program progress. At the workshop, a potential crosswalk between the GCDML and EML was explored. Also, collaboration between the LTER and GSC developers was proposed to join efforts toward a common metadata cataloging designer's tool. The community adoption success of a metadata standard depends, among other factors, on the tools and trainings developed to use the standard. LTER's experience in embracing EML may help GSC to achieve similar success. A possible collaboration between LTER and GSC to provide training opportunities for GCDML and the associated tools is being explored. Finally, LTER is investigating EML enhancements to better accommodate genomics data, possibly integrating the GCDML schema into EML. All these action items have been accepted by the LTER contingent, and further collaboration between the GSC and LTER is expected.« less

Defining linkages between the GSC and NSF's LTER program: how the Ecological Metadata Language (EML) relates to GCDML and other outcomes.

PubMed

Gil, Inigo San; Sheldon, Wade; Schmidt, Tom; Servilla, Mark; Aguilar, Raul; Gries, Corinna; Gray, Tanya; Field, Dawn; Cole, James; Pan, Jerry Yun; Palanisamy, Giri; Henshaw, Donald; O'Brien, Margaret; Kinkel, Linda; McMahon, Katherine; Kottmann, Renzo; Amaral-Zettler, Linda; Hobbie, John; Goldstein, Philip; Guralnick, Robert P; Brunt, James; Michener, William K

2008-06-01

The Genomic Standards Consortium (GSC) invited a representative of the Long-Term Ecological Research (LTER) to its fifth workshop to present the Ecological Metadata Language (EML) metadata standard and its relationship to the Minimum Information about a Genome/Metagenome Sequence (MIGS/MIMS) and its implementation, the Genomic Contextual Data Markup Language (GCDML). The LTER is one of the top National Science Foundation (NSF) programs in biology since 1980, representing diverse ecosystems and creating long-term, interdisciplinary research, synthesis of information, and theory. The adoption of EML as the LTER network standard has been key to build network synthesis architectures based on high-quality standardized metadata. EML is the NSF-recognized metadata standard for LTER, and EML is a criteria used to review the LTER program progress. At the workshop, a potential crosswalk between the GCDML and EML was explored. Also, collaboration between the LTER and GSC developers was proposed to join efforts toward a common metadata cataloging designer's tool. The community adoption success of a metadata standard depends, among other factors, on the tools and trainings developed to use the standard. LTER's experience in embracing EML may help GSC to achieve similar success. A possible collaboration between LTER and GSC to provide training opportunities for GCDML and the associated tools is being explored. Finally, LTER is investigating EML enhancements to better accommodate genomics data, possibly integrating the GCDML schema into EML. All these action items have been accepted by the LTER contingent, and further collaboration between the GSC and LTER is expected.

NCPP's Use of Standard Metadata to Promote Open and Transparent Climate Modeling

NASA Astrophysics Data System (ADS)

Treshansky, A.; Barsugli, J. J.; Guentchev, G.; Rood, R. B.; DeLuca, C.

2012-12-01

The National Climate Predictions and Projections (NCPP) Platform is developing comprehensive regional and local information about the evolving climate to inform decision making and adaptation planning. This includes both creating and providing tools to create metadata about the models and processes used to create its derived data products. NCPP is using the Common Information Model (CIM), an ontology developed by a broad set of international partners in climate research, as its metadata language. This use of a standard ensures interoperability within the climate community as well as permitting access to the ecosystem of tools and services emerging alongside the CIM. The CIM itself is divided into a general-purpose (UML & XML) schema which structures metadata documents, and a project or community-specific (XML) Controlled Vocabulary (CV) which constraints the content of metadata documents. NCPP has already modified the CIM Schema to accommodate downscaling models, simulations, and experiments. NCPP is currently developing a CV for use by the downscaling community. Incorporating downscaling into the CIM will lead to several benefits: easy access to the existing CIM Documents describing CMIP5 models and simulations that are being downscaled, access to software tools that have been developed in order to search, manipulate, and visualize CIM metadata, and coordination with national and international efforts such as ES-DOC that are working to make climate model descriptions and datasets interoperable. Providing detailed metadata descriptions which include the full provenance of derived data products will contribute to making that data (and, the models and processes which generated that data) more open and transparent to the user community.

Serving Fisheries and Ocean Metadata to Communities Around the World

NASA Technical Reports Server (NTRS)

Meaux, Melanie F.

2007-01-01

NASA's Global Change Master Directory (GCMD) assists the oceanographic community in the discovery, access, and sharing of scientific data by serving on-line fisheries and ocean metadata to users around the globe. As of January 2006, the directory holds more than 16,300 Earth Science data descriptions and over 1,300 services descriptions. Of these, nearly 4,000 unique ocean-related metadata records are available to the public, with many having direct links to the data. In 2005, the GCMD averaged over 5 million hits a month, with nearly a half million unique hosts for the year. Through the GCMD portal (http://gcmd.nasa.gov/), users can search vast and growing quantities of data and services using controlled keywords, free-text searches, or a combination of both. Users may now refine a search based on topic, location, instrument, platform, project, data center, spatial and temporal coverage, and data resolution for selected datasets. The directory also offers data holders a means to advertise and search their data through customized portals, which are subset views of the directory. The discovery metadata standard used is the Directory Interchange Format (DIF), adopted in 1988. This format has evolved to accommodate other national and international standards such as FGDC and IS019115. Users can submit metadata through easy-to-use online and offline authoring tools. The directory, which also serves as the International Directory Network (IDN), has been providing its services and sharing its experience and knowledge of metadata at the international, national, regional, and local level for many years. Active partners include the Committee on Earth Observation Satellites (CEOS), federal agencies (such as NASA, NOAA, and USGS), international agencies (such as IOC/IODE, UN, and JAXA) and organizations (such as ESIP, IOOS/DMAC, GOSIC, GLOBEC, OBIS, and GoMODP).

Scientific Platform as a Service - Tools and solutions for efficient access to and analysis of oceanographic data

NASA Astrophysics Data System (ADS)

Vines, Aleksander; Hansen, Morten W.; Korosov, Anton

2017-04-01

Existing infrastructure international and Norwegian projects, e.g., NorDataNet, NMDC and NORMAP, provide open data access through the OPeNDAP protocol following the conventions for CF (Climate and Forecast) metadata, designed to promote the processing and sharing of files created with the NetCDF application programming interface (API). This approach is now also being implemented in the Norwegian Sentinel Data Hub (satellittdata.no) to provide satellite EO data to the user community. Simultaneously with providing simplified and unified data access, these projects also seek to use and establish common standards for use and discovery metadata. This then allows development of standardized tools for data search and (subset) streaming over the internet to perform actual scientific analysis. A combinnation of software tools, which we call a Scientific Platform as a Service (SPaaS), will take advantage of these opportunities to harmonize and streamline the search, retrieval and analysis of integrated satellite and auxiliary observations of the oceans in a seamless system. The SPaaS is a cloud solution for integration of analysis tools with scientific datasets via an API. The core part of the SPaaS is a distributed metadata catalog to store granular metadata describing the structure, location and content of available satellite, model, and in situ datasets. The analysis tools include software for visualization (also online), interactive in-depth analysis, and server-based processing chains. The API conveys search requests between system nodes (i.e., interactive and server tools) and provides easy access to the metadata catalog, data repositories, and the tools. The SPaaS components are integrated in virtual machines, of which provisioning and deployment are automatized using existing state-of-the-art open-source tools (e.g., Vagrant, Ansible, Docker). The open-source code for scientific tools and virtual machine configurations is under version control at https://github.com/nansencenter/, and is coupled to an online continuous integration system (e.g., Travis CI).

User's Guide and Metadata to Coastal Biodiversity Risk Analysis Tool (CBRAT): Framework for the Systemization of Life History and Biogeographic Information

EPA Science Inventory

ABSTRACTUser’s Guide & Metadata to Coastal Biodiversity Risk Analysis Tool (CBRAT): Framework for the Systemization of Life History and Biogeographic Information(EPA/601/B-15/001, 2015, 123 pages)Henry Lee II, U.S. EPA, Western Ecology DivisionKatharine Marko, U.S. EPA,...

Evaluating and Improving Metadata for Data Use and Understanding

NASA Astrophysics Data System (ADS)

Habermann, T.

2013-12-01

The last several decades have seen an extraordinary increase in the number and breadth of environmental data available to the scientific community and the general public. These increases have focused the environmental data community on creating metadata for discovering data and on the creation and population of catalogs and portals for facilitating discovery. This focus is reflected in the fields required by commonly used metadata standards and has resulted in collections populated with metadata that meet, but don't go far beyond, minimal discovery requirements. Discovery is the first step towards addressing scientific questions using data. As more data are discovered and accessed, users need metadata that 1) automates use and integration of these data in tools and 2) facilitates understanding the data when it is compared to similar datasets or as internal variations are observed. When data discovery is the primary goal, it is important to create records for as many datasets as possible. The content of these records is controlled by minimum requirements, and evaluation is generally limited to testing for required fields and counting records. As the use and understanding needs become more important, more comprehensive evaluation tools are needed. An approach is described for evaluating existing metadata in the light of these new requirements and for improving the metadata to meet them.

Inheritance rules for Hierarchical Metadata Based on ISO 19115

NASA Astrophysics Data System (ADS)

Zabala, A.; Masó, J.; Pons, X.

2012-04-01

Mainly, ISO19115 has been used to describe metadata for datasets and services. Furthermore, ISO19115 standard (as well as the new draft ISO19115-1) includes a conceptual model that allows to describe metadata at different levels of granularity structured in hierarchical levels, both in aggregated resources such as particularly series, datasets, and also in more disaggregated resources such as types of entities (feature type), types of attributes (attribute type), entities (feature instances) and attributes (attribute instances). In theory, to apply a complete metadata structure to all hierarchical levels of metadata, from the whole series to an individual feature attributes, is possible, but to store all metadata at all levels is completely impractical. An inheritance mechanism is needed to store each metadata and quality information at the optimum hierarchical level and to allow an ease and efficient documentation of metadata in both an Earth observation scenario such as a multi-satellite mission multiband imagery, as well as in a complex vector topographical map that includes several feature types separated in layers (e.g. administrative limits, contour lines, edification polygons, road lines, etc). Moreover, and due to the traditional split of maps in tiles due to map handling at detailed scales or due to the satellite characteristics, each of the previous thematic layers (e.g. 1:5000 roads for a country) or band (Landsat-5 TM cover of the Earth) are tiled on several parts (sheets or scenes respectively). According to hierarchy in ISO 19115, the definition of general metadata can be supplemented by spatially specific metadata that, when required, either inherits or overrides the general case (G.1.3). Annex H of this standard states that only metadata exceptions are defined at lower levels, so it is not necessary to generate the full registry of metadata for each level but to link particular values to the general value that they inherit. Conceptually the metadata registry is complete for each metadata hierarchical level, but at the implementation level most of the metadata elements are not stored at both levels but only at more generic one. This communication defines a metadata system that covers 4 levels, describes which metadata has to support series-layer inheritance and in which way, and how hierarchical levels are defined and stored. Metadata elements are classified according to the type of inheritance between products, series, tiles and the datasets. It explains the metadata elements classification and exemplifies it using core metadata elements. The communication also presents a metadata viewer and edition tool that uses the described model to propagate metadata elements and to show to the user a complete set of metadata for each level in a transparent way. This tool is integrated in the MiraMon GIS software.

Improving Earth Science Metadata: Modernizing ncISO

NASA Astrophysics Data System (ADS)

O'Brien, K.; Schweitzer, R.; Neufeld, D.; Burger, E. F.; Signell, R. P.; Arms, S. C.; Wilcox, K.

2016-12-01

ncISO is a package of tools developed at NOAA's National Center for Environmental Information (NCEI) that facilitates the generation of ISO 19115-2 metadata from NetCDF data sources. The tool currently exists in two iterations: a command line utility and a web-accessible service within the THREDDS Data Server (TDS). Several projects, including NOAA's Unified Access Framework (UAF), depend upon ncISO to generate the ISO-compliant metadata from their data holdings and use the resulting information to populate discovery tools such as NCEI's ESRI Geoportal and NOAA's data.noaa.gov CKAN system. In addition to generating ISO 19115-2 metadata, the tool calculates a rubric score based on how well the dataset follows the Attribute Conventions for Dataset Discovery (ACDD). The result of this rubric calculation, along with information about what has been included and what is missing is displayed in an HTML document generated by the ncISO software package. Recently ncISO has fallen behind in terms of supporting updates to conventions such updates to the ACDD. With the blessing of the original programmer, NOAA's UAF has been working to modernize the ncISO software base. In addition to upgrading ncISO to utilize version1.3 of the ACDD, we have been working with partners at Unidata and IOOS to unify the tool's code base. In essence, we are merging the command line capabilities into the same software that will now be used by the TDS service, allowing easier updates when conventions such as ACDD are updated in the future. In this presentation, we will discuss the work the UAF project has done to support updated conventions within ncISO, as well as describe how the updated tool is helping to improve metadata throughout the earth and ocean sciences.

Evolutions in Metadata Quality

NASA Astrophysics Data System (ADS)

Gilman, J.

2016-12-01

Metadata Quality is one of the chief drivers of discovery and use of NASA EOSDIS (Earth Observing System Data and Information System) data. Issues with metadata such as lack of completeness, inconsistency, and use of legacy terms directly hinder data use. As the central metadata repository for NASA Earth Science data, the Common Metadata Repository (CMR) has a responsibility to its users to ensure the quality of CMR search results. This talk will cover how we encourage metadata authors to improve the metadata through the use of integrated rubrics of metadata quality and outreach efforts. In addition we'll demonstrate Humanizers, a technique for dealing with the symptoms of metadata issues. Humanizers allow CMR administrators to identify specific metadata issues that are fixed at runtime when the data is indexed. An example Humanizer is the aliasing of processing level "Level 1" to "1" to improve consistency across collections. The CMR currently indexes 35K collections and 300M granules.

A novel framework for assessing metadata quality in epidemiological and public health research settings

PubMed Central

McMahon, Christiana; Denaxas, Spiros

2016-01-01

Metadata are critical in epidemiological and public health research. However, a lack of biomedical metadata quality frameworks and limited awareness of the implications of poor quality metadata renders data analyses problematic. In this study, we created and evaluated a novel framework to assess metadata quality of epidemiological and public health research datasets. We performed a literature review and surveyed stakeholders to enhance our understanding of biomedical metadata quality assessment. The review identified 11 studies and nine quality dimensions; none of which were specifically aimed at biomedical metadata. 96 individuals completed the survey; of those who submitted data, most only assessed metadata quality sometimes, and eight did not at all. Our framework has four sections: a) general information; b) tools and technologies; c) usability; and d) management and curation. We evaluated the framework using three test cases and sought expert feedback. The framework can assess biomedical metadata quality systematically and robustly. PMID:27570670

A novel framework for assessing metadata quality in epidemiological and public health research settings.

PubMed

McMahon, Christiana; Denaxas, Spiros

2016-01-01

Metadata are critical in epidemiological and public health research. However, a lack of biomedical metadata quality frameworks and limited awareness of the implications of poor quality metadata renders data analyses problematic. In this study, we created and evaluated a novel framework to assess metadata quality of epidemiological and public health research datasets. We performed a literature review and surveyed stakeholders to enhance our understanding of biomedical metadata quality assessment. The review identified 11 studies and nine quality dimensions; none of which were specifically aimed at biomedical metadata. 96 individuals completed the survey; of those who submitted data, most only assessed metadata quality sometimes, and eight did not at all. Our framework has four sections: a) general information; b) tools and technologies; c) usability; and d) management and curation. We evaluated the framework using three test cases and sought expert feedback. The framework can assess biomedical metadata quality systematically and robustly.

PanMetaDocs - A tool for collecting and managing the long tail of "small science data"

NASA Astrophysics Data System (ADS)

Klump, J.; Ulbricht, D.

2011-12-01

In the early days of thinking about cyberinfrastructure the focus was on "big science data". Today, the challenge is not anymore to store several terabytes of data, but to manage data objects in a way that facilitates their re-use. Key to re-use by a user as a data consumer is proper documentation of the data. Also, data consumers need discovery metadata to find the data they need and they need descriptive metadata to be able to use the data they retrieved. Thus, data documentation faces the challenge to extensively and completely describe these objects, hold the items easily accessible at a sustainable cost level. However, data curation and documentation do not rank high in the everyday work of a scientist as a data producer. Data producers are often frustrated by being asked to provide metadata on their data over and over again, information that seemed very obvious from the context of their work. A challenge to data archives is the wide variety of metadata schemata in use, which creates a number of maintenance and design challenges of its own. PanMetaDocs addresses these issues by allowing an uploaded files to be described by more than one metadata object. PanMetaDocs, which was developed from PanMetaWorks, is a PHP based web application that allow to describe data with any xml-based metadata schema. Its user interface is browser based and was developed to collect metadata and data in collaborative scientific projects situated at one or more institutions. The metadata fields can be filled with static or dynamic content to reduce the number of fields that require manual entries to a minimum and make use of contextual information in a project setting. In the development of PanMetaDocs the business logic of panMetaWorks is reused, except for the authentication and data management functions of PanMetaWorks, which are delegated to the eSciDoc framework. The eSciDoc repository framework is designed as a service oriented architecture that can be controlled through a REST interface to create version controlled items with metadata records in XML format. PanMetaDocs utilizes the eSciDoc items model to add multiple metadata records that describe uploaded files in different metadata schemata. While datasets are collected and described, shared to collaborate with other scientists and finally published, data objects are transferred from a shared data curation domain into a persistent data curation domain. Through an RSS interface for recent datasets PanMetaWorks allows project members to be informed about data uploaded by other project members. The implementation of the OAI-PMH interface can be used to syndicate data catalogs to research data portals, such as the panFMP data portal framework. Once data objects are uploaded to the eSciDoc infrastructure it is possible to drop the software instance that was used for collecting the data, while the compiled data and metadata are accessible for other authorized applications through the institution's eSciDoc middleware. This approach of "expendable data curation tools" allows for a significant reduction in costs for software maintenance as expensive data capture applications do not need to be maintained indefinitely to ensure long term access to the stored data.

iTools: a framework for classification, categorization and integration of computational biology resources.

PubMed

Dinov, Ivo D; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H V; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D Stott; Toga, Arthur W

2008-05-28

The advancement of the computational biology field hinges on progress in three fundamental directions--the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources--data, software tools and web-services. The iTools design, implementation and resource meta-data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu.

Construction of a robust, large-scale, collaborative database for raw data in computational chemistry: the Collaborative Chemistry Database Tool (CCDBT).

PubMed

Chen, Mingyang; Stott, Amanda C; Li, Shenggang; Dixon, David A

2012-04-01

A robust metadata database called the Collaborative Chemistry Database Tool (CCDBT) for massive amounts of computational chemistry raw data has been designed and implemented. It performs data synchronization and simultaneously extracts the metadata. Computational chemistry data in various formats from different computing sources, software packages, and users can be parsed into uniform metadata for storage in a MySQL database. Parsing is performed by a parsing pyramid, including parsers written for different levels of data types and sets created by the parser loader after loading parser engines and configurations. Copyright © 2011 Elsevier Inc. All rights reserved.

Digital Initiatives and Metadata Use in Thailand

ERIC Educational Resources Information Center

SuKantarat, Wichada

2008-01-01

Purpose: This paper aims to provide information about various digital initiatives in libraries in Thailand and especially use of Dublin Core metadata in cataloguing digitized objects in academic and government digital databases. Design/methodology/approach: The author began researching metadata use in Thailand in 2003 and 2004 while on sabbatical…

77 FR 22707 - Electronic Reporting Under the Toxic Substances Control Act

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-17

... completes metadata information, the web-based tool validates the submission by performing a basic error... uploading PDF attachments or other file types, such as XML, and completing metadata information would be...

CERES Search and Subset Tool

Atmospheric Science Data Center

2016-06-24

... data granules using a high resolution spatial metadata database and directly accessing the archived data granules. Subset results are ... data granules using a high resolution spatial metadata database and directly accessing the archived data granules. Subset results are ...

Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools.

PubMed

Sud, Manish; Fahy, Eoin; Cotter, Dawn; Azam, Kenan; Vadivelu, Ilango; Burant, Charles; Edison, Arthur; Fiehn, Oliver; Higashi, Richard; Nair, K Sreekumaran; Sumner, Susan; Subramaniam, Shankar

2016-01-04

The Metabolomics Workbench, available at www.metabolomicsworkbench.org, is a public repository for metabolomics metadata and experimental data spanning various species and experimental platforms, metabolite standards, metabolite structures, protocols, tutorials, and training material and other educational resources. It provides a computational platform to integrate, analyze, track, deposit and disseminate large volumes of heterogeneous data from a wide variety of metabolomics studies including mass spectrometry (MS) and nuclear magnetic resonance spectrometry (NMR) data spanning over 20 different species covering all the major taxonomic categories including humans and other mammals, plants, insects, invertebrates and microorganisms. Additionally, a number of protocols are provided for a range of metabolite classes, sample types, and both MS and NMR-based studies, along with a metabolite structure database. The metabolites characterized in the studies available on the Metabolomics Workbench are linked to chemical structures in the metabolite structure database to facilitate comparative analysis across studies. The Metabolomics Workbench, part of the data coordinating effort of the National Institute of Health (NIH) Common Fund's Metabolomics Program, provides data from the Common Fund's Metabolomics Resource Cores, metabolite standards, and analysis tools to the wider metabolomics community and seeks data depositions from metabolomics researchers across the world. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

MetaRNA-Seq: An Interactive Tool to Browse and Annotate Metadata from RNA-Seq Studies.

PubMed

Kumar, Pankaj; Halama, Anna; Hayat, Shahina; Billing, Anja M; Gupta, Manish; Yousri, Noha A; Smith, Gregory M; Suhre, Karsten

2015-01-01

The number of RNA-Seq studies has grown in recent years. The design of RNA-Seq studies varies from very simple (e.g., two-condition case-control) to very complicated (e.g., time series involving multiple samples at each time point with separate drug treatments). Most of these publically available RNA-Seq studies are deposited in NCBI databases, but their metadata are scattered throughout four different databases: Sequence Read Archive (SRA), Biosample, Bioprojects, and Gene Expression Omnibus (GEO). Although the NCBI web interface is able to provide all of the metadata information, it often requires significant effort to retrieve study- or project-level information by traversing through multiple hyperlinks and going to another page. Moreover, project- and study-level metadata lack manual or automatic curation by categories, such as disease type, time series, case-control, or replicate type, which are vital to comprehending any RNA-Seq study. Here we describe "MetaRNA-Seq," a new tool for interactively browsing, searching, and annotating RNA-Seq metadata with the capability of semiautomatic curation at the study level.

File level metadata generation and use for diverse airborne and in situ data: Experiences with Operation IceBridge and SnowEx

NASA Astrophysics Data System (ADS)

Tanner, S.; Schwab, M.; Beam, K.; Skaug, M.

2017-12-01

Operation IceBridge has been flying campaigns in the Arctic and Antarctic for nearly 10 years and will soon be a decadal mission. During that time, the generation and use of file level metadata has evolved from nearly non-existent to robust spatio-temporal support. This evolution has been difficult at times, but the results speak for themselves in the form of production tools for search, discovery, access and analysis. The lessons learned from this experience are now being incorporated into SnowEx, a new mission to measure snow cover using airborne and ground-based measurements. This presentation will focus on techniques for generating metadata for such a diverse set of measurements as well as the resulting tools that utilize this information. This includes the development and deployment of MetGen, a semi-automated metadata generation capability that relies on collaboration between data producers and data archivers, the newly deployed IceBridge data portal which incorporates data browse capabilities and limited in-line analysis, and programmatic access to metadata and data for incorporation into larger automated workflows.

Document Classification in Support of Automated Metadata Extraction Form Heterogeneous Collections

ERIC Educational Resources Information Center

Flynn, Paul K.

2014-01-01

A number of federal agencies, universities, laboratories, and companies are placing their documents online and making them searchable via metadata fields such as author, title, and publishing organization. To enable this, every document in the collection must be catalogued using the metadata fields. Though time consuming, the task of identifying…

ReGaTE: Registration of Galaxy Tools in Elixir.

PubMed

Doppelt-Azeroual, Olivia; Mareuil, Fabien; Deveaud, Eric; Kalaš, Matúš; Soranzo, Nicola; van den Beek, Marius; Grüning, Björn; Ison, Jon; Ménager, Hervé

2017-06-01

Bioinformaticians routinely use multiple software tools and data sources in their day-to-day work and have been guided in their choices by a number of cataloguing initiatives. The ELIXIR Tools and Data Services Registry (bio.tools) aims to provide a central information point, independent of any specific scientific scope within bioinformatics or technological implementation. Meanwhile, efforts to integrate bioinformatics software in workbench and workflow environments have accelerated to enable the design, automation, and reproducibility of bioinformatics experiments. One such popular environment is the Galaxy framework, with currently more than 80 publicly available Galaxy servers around the world. In the context of a generic registry for bioinformatics software, such as bio.tools, Galaxy instances constitute a major source of valuable content. Yet there has been, to date, no convenient mechanism to register such services en masse. We present ReGaTE (Registration of Galaxy Tools in Elixir), a software utility that automates the process of registering the services available in a Galaxy instance. This utility uses the BioBlend application program interface to extract service metadata from a Galaxy server, enhance the metadata with the scientific information required by bio.tools, and push it to the registry. ReGaTE provides a fast and convenient way to publish Galaxy services in bio.tools. By doing so, service providers may increase the visibility of their services while enriching the software discovery function that bio.tools provides for its users. The source code of ReGaTE is freely available on Github at https://github.com/C3BI-pasteur-fr/ReGaTE . © The Author 2017. Published by Oxford University Press.

There's Trouble in Paradise: Problems with Educational Metadata Encountered during the MALTED Project.

ERIC Educational Resources Information Center

Monthienvichienchai, Rachada; Sasse, M. Angela; Wheeldon, Richard

This paper investigates the usability of educational metadata schemas with respect to the case of the MALTED (Multimedia Authoring Language Teachers and Educational Developers) project at University College London (UCL). The project aims to facilitate authoring of multimedia materials for language learning by allowing teachers to share multimedia…

An Ontology-Enabled Natural Language Processing Pipeline for Provenance Metadata Extraction from Biomedical Text (Short Paper).

PubMed

Valdez, Joshua; Rueschman, Michael; Kim, Matthew; Redline, Susan; Sahoo, Satya S

2016-10-01

Extraction of structured information from biomedical literature is a complex and challenging problem due to the complexity of biomedical domain and lack of appropriate natural language processing (NLP) techniques. High quality domain ontologies model both data and metadata information at a fine level of granularity, which can be effectively used to accurately extract structured information from biomedical text. Extraction of provenance metadata, which describes the history or source of information, from published articles is an important task to support scientific reproducibility. Reproducibility of results reported by previous research studies is a foundational component of scientific advancement. This is highlighted by the recent initiative by the US National Institutes of Health called "Principles of Rigor and Reproducibility". In this paper, we describe an effective approach to extract provenance metadata from published biomedical research literature using an ontology-enabled NLP platform as part of the Provenance for Clinical and Healthcare Research (ProvCaRe). The ProvCaRe-NLP tool extends the clinical Text Analysis and Knowledge Extraction System (cTAKES) platform using both provenance and biomedical domain ontologies. We demonstrate the effectiveness of ProvCaRe-NLP tool using a corpus of 20 peer-reviewed publications. The results of our evaluation demonstrate that the ProvCaRe-NLP tool has significantly higher recall in extracting provenance metadata as compared to existing NLP pipelines such as MetaMap.

Collaborative Movie Annotation

NASA Astrophysics Data System (ADS)

Zad, Damon Daylamani; Agius, Harry

In this paper, we focus on metadata for self-created movies like those found on YouTube and Google Video, the duration of which are increasing in line with falling upload restrictions. While simple tags may have been sufficient for most purposes for traditionally very short video footage that contains a relatively small amount of semantic content, this is not the case for movies of longer duration which embody more intricate semantics. Creating metadata is a time-consuming process that takes a great deal of individual effort; however, this effort can be greatly reduced by harnessing the power of Web 2.0 communities to create, update and maintain it. Consequently, we consider the annotation of movies within Web 2.0 environments, such that users create and share that metadata collaboratively and propose an architecture for collaborative movie annotation. This architecture arises from the results of an empirical experiment where metadata creation tools, YouTube and an MPEG-7 modelling tool, were used by users to create movie metadata. The next section discusses related work in the areas of collaborative retrieval and tagging. Then, we describe the experiments that were undertaken on a sample of 50 users. Next, the results are presented which provide some insight into how users interact with existing tools and systems for annotating movies. Based on these results, the paper then develops an architecture for collaborative movie annotation.

Inconsistencies between Academic E-Book Platforms: A Comparison of Metadata and Search Results

ERIC Educational Resources Information Center

Wiersma, Gabrielle; Tovstiadi, Esta

2017-01-01

This article presents the results of a study of academic e-books that compared the metadata and search results from major academic e-book platforms. The authors collected data and performed a series of test searches designed to produce the same result regardless of platform. Testing, however, revealed metadata-related errors and significant…

Evaluating and Evolving Metadata in Multiple Dialects

NASA Technical Reports Server (NTRS)

Kozimore, John; Habermann, Ted; Gordon, Sean; Powers, Lindsay

2016-01-01

Despite many long-term homogenization efforts, communities continue to develop focused metadata standards along with related recommendations and (typically) XML representations (aka dialects) for sharing metadata content. Different representations easily become obstacles to sharing information because each representation generally requires a set of tools and skills that are designed, built, and maintained specifically for that representation. In contrast, community recommendations are generally described, at least initially, at a more conceptual level and are more easily shared. For example, most communities agree that dataset titles should be included in metadata records although they write the titles in different ways.

Metadata Means Communication: The Challenges of Producing Useful Metadata

NASA Astrophysics Data System (ADS)

Edwards, P. N.; Batcheller, A. L.

2010-12-01

Metadata are increasingly perceived as an important component of data sharing systems. For instance, metadata accompanying atmospheric model output may indicate the grid size, grid type, and parameter settings used in the model configuration. We conducted a case study of a data portal in the atmospheric sciences using in-depth interviews, document review, and observation. OUr analysis revealed a number of challenges in producing useful metadata. First, creating and managing metadata required considerable effort and expertise, yet responsibility for these tasks was ill-defined and diffused among many individuals, leading to errors, failure to capture metadata, and uncertainty about the quality of the primary data. Second, metadata ended up stored in many different forms and software tools, making it hard to manage versions and transfer between formats. Third, the exact meanings of metadata categories remained unsettled and misunderstood even among a small community of domain experts -- an effect we expect to be exacerbated when scientists from other disciplines wish to use these data. In practice, we found that metadata problems due to these obstacles are often overcome through informal, personal communication, such as conversations or email. We conclude that metadata serve to communicate the context of data production from the people who produce data to those who wish to use it. Thus while formal metadata systems are often public, critical elements of metadata (those embodied in informal communication) may never be recorded. Therefore, efforts to increase data sharing should include ways to facilitate inter-investigator communication. Instead of tackling metadata challenges only on the formal level, we can improve data usability for broader communities by better supporting metadata communication.

System for Earth Sample Registration SESAR: Services for IGSN Registration and Sample Metadata Management

NASA Astrophysics Data System (ADS)

Chan, S.; Lehnert, K. A.; Coleman, R. J.

2011-12-01

SESAR, the System for Earth Sample Registration, is an online registry for physical samples collected for Earth and environmental studies. SESAR generates and administers the International Geo Sample Number IGSN, a unique identifier for samples that is dramatically advancing interoperability amongst information systems for sample-based data. SESAR was developed to provide the complete range of registry services, including definition of IGSN syntax and metadata profiles, registration and validation of name spaces requested by users, tools for users to submit and manage sample metadata, validation of submitted metadata, generation and validation of the unique identifiers, archiving of sample metadata, and public or private access to the sample metadata catalog. With the development of SESAR v3, we placed particular emphasis on creating enhanced tools that make metadata submission easier and more efficient for users, and that provide superior functionality for users to manage metadata of their samples in their private workspace MySESAR. For example, SESAR v3 includes a module where users can generate custom spreadsheet templates to enter metadata for their samples, then upload these templates online for sample registration. Once the content of the template is uploaded, it is displayed online in an editable grid format. Validation rules are executed in real-time on the grid data to ensure data integrity. Other new features of SESAR v3 include the capability to transfer ownership of samples to other SESAR users, the ability to upload and store images and other files in a sample metadata profile, and the tracking of changes to sample metadata profiles. In the next version of SESAR (v3.5), we will further improve the discovery, sharing, registration of samples. For example, we are developing a more comprehensive suite of web services that will allow discovery and registration access to SESAR from external systems. Both batch and individual registrations will be possible through web services. Based on valuable feedback from the user community, we will introduce enhancements that add greater flexibility to the system to accommodate the vast diversity of metadata that users want to store. Users will be able to create custom metadata fields and use these for the samples they register. Users will also be able to group samples into 'collections' to make retrieval for research projects or publications easier. An improved interface design will allow for better workflow transition and navigation throughout the application. In keeping up with the demands of a growing community, SESAR has also made process changes to ensure efficiency in system development. For example, we have implemented a release cycle to better track enhancements and fixes to the system, and an API library that facilitates reusability of code. Usage tracking, metrics and surveys capture information to guide the direction of future developments. A new set of administrative tools allows greater control of system management.

Towards a semantic medical Web: HealthCyberMap's tool for building an RDF metadata base of health information resources based on the Qualified Dublin Core Metadata Set.

PubMed

Boulos, Maged N; Roudsari, Abdul V; Carson, Ewart R

2002-07-01

HealthCyberMap (http://healthcybermap.semanticweb.org/) aims at mapping Internet health information resources in novel ways for enhanced retrieval and navigation. This is achieved by collecting appropriate resource metadata in an unambiguous form that preserves semantics. We modelled a qualified Dublin Core (DC) metadata set ontology with extra elements for resource quality and geographical provenance in Prot g -2000. A metadata collection form helps acquiring resource instance data within Prot g . The DC subject field is populated with UMLS terms directly imported from UMLS Knowledge Source Server using UMLS tab, a Prot g -2000 plug-in. The project is saved in RDFS/RDF. The ontology and associated form serve as a free tool for building and maintaining an RDF medical resource metadata base. The UMLS tab enables browsing and searching for concepts that best describe a resource, and importing them to DC subject fields. The resultant metadata base can be used with a search and inference engine, and have textual and/or visual navigation interface(s) applied to it, to ultimately build a medical Semantic Web portal. Different ways of exploiting Prot g -2000 RDF output are discussed. By making the context and semantics of resources, not merely their raw text and formatting, amenable to computer 'understanding,' we can build a Semantic Web that is more useful to humans than the current Web. This requires proper use of metadata and ontologies. Clinical codes can reliably describe the subjects of medical resources, establish the semantic relationships (as defined by underlying coding scheme) between related resources, and automate their topical categorisation.

Science friction: data, metadata, and collaboration.

PubMed

Edwards, Paul N; Mayernik, Matthew S; Batcheller, Archer L; Bowker, Geoffrey C; Borgman, Christine L

2011-10-01

When scientists from two or more disciplines work together on related problems, they often face what we call 'science friction'. As science becomes more data-driven, collaborative, and interdisciplinary, demand increases for interoperability among data, tools, and services. Metadata--usually viewed simply as 'data about data', describing objects such as books, journal articles, or datasets--serve key roles in interoperability. Yet we find that metadata may be a source of friction between scientific collaborators, impeding data sharing. We propose an alternative view of metadata, focusing on its role in an ephemeral process of scientific communication, rather than as an enduring outcome or product. We report examples of highly useful, yet ad hoc, incomplete, loosely structured, and mutable, descriptions of data found in our ethnographic studies of several large projects in the environmental sciences. Based on this evidence, we argue that while metadata products can be powerful resources, usually they must be supplemented with metadata processes. Metadata-as-process suggests the very large role of the ad hoc, the incomplete, and the unfinished in everyday scientific work.

Principles of metadata organization at the ENCODE data coordination center.

PubMed

Hong, Eurie L; Sloan, Cricket A; Chan, Esther T; Davidson, Jean M; Malladi, Venkat S; Strattan, J Seth; Hitz, Benjamin C; Gabdank, Idan; Narayanan, Aditi K; Ho, Marcus; Lee, Brian T; Rowe, Laurence D; Dreszer, Timothy R; Roe, Greg R; Podduturi, Nikhil R; Tanaka, Forrest; Hilton, Jason A; Cherry, J Michael

2016-01-01

The Encyclopedia of DNA Elements (ENCODE) Data Coordinating Center (DCC) is responsible for organizing, describing and providing access to the diverse data generated by the ENCODE project. The description of these data, known as metadata, includes the biological sample used as input, the protocols and assays performed on these samples, the data files generated from the results and the computational methods used to analyze the data. Here, we outline the principles and philosophy used to define the ENCODE metadata in order to create a metadata standard that can be applied to diverse assays and multiple genomic projects. In addition, we present how the data are validated and used by the ENCODE DCC in creating the ENCODE Portal (https://www.encodeproject.org/). Database URL: www.encodeproject.org. © The Author(s) 2016. Published by Oxford University Press.

EXIF Custom: Automatic image metadata extraction for Scratchpads and Drupal.

PubMed

Baker, Ed

2013-01-01

Many institutions and individuals use embedded metadata to aid in the management of their image collections. Many deskop image management solutions such as Adobe Bridge and online tools such as Flickr also make use of embedded metadata to describe, categorise and license images. Until now Scratchpads (a data management system and virtual research environment for biodiversity) have not made use of these metadata, and users have had to manually re-enter this information if they have wanted to display it on their Scratchpad site. The Drupal described here allows users to map metadata embedded in their images to the associated field in the Scratchpads image form using one or more customised mappings. The module works seamlessly with the bulk image uploader used on Scratchpads and it is therefore possible to upload hundreds of images easily with automatic metadata (EXIF, XMP and IPTC) extraction and mapping.

HDF-EOS Web Server

NASA Technical Reports Server (NTRS)

Ullman, Richard; Bane, Bob; Yang, Jingli

2008-01-01

A shell script has been written as a means of automatically making HDF-EOS-formatted data sets available via the World Wide Web. ("HDF-EOS" and variants thereof are defined in the first of the two immediately preceding articles.) The shell script chains together some software tools developed by the Data Usability Group at Goddard Space Flight Center to perform the following actions: Extract metadata in Object Definition Language (ODL) from an HDF-EOS file, Convert the metadata from ODL to Extensible Markup Language (XML), Reformat the XML metadata into human-readable Hypertext Markup Language (HTML), Publish the HTML metadata and the original HDF-EOS file to a Web server and an Open-source Project for a Network Data Access Protocol (OPeN-DAP) server computer, and Reformat the XML metadata and submit the resulting file to the EOS Clearinghouse, which is a Web-based metadata clearinghouse that facilitates searching for, and exchange of, Earth-Science data.

EXIF Custom: Automatic image metadata extraction for Scratchpads and Drupal

PubMed Central

2013-01-01

Abstract Many institutions and individuals use embedded metadata to aid in the management of their image collections. Many deskop image management solutions such as Adobe Bridge and online tools such as Flickr also make use of embedded metadata to describe, categorise and license images. Until now Scratchpads (a data management system and virtual research environment for biodiversity) have not made use of these metadata, and users have had to manually re-enter this information if they have wanted to display it on their Scratchpad site. The Drupal described here allows users to map metadata embedded in their images to the associated field in the Scratchpads image form using one or more customised mappings. The module works seamlessly with the bulk image uploader used on Scratchpads and it is therefore possible to upload hundreds of images easily with automatic metadata (EXIF, XMP and IPTC) extraction and mapping. PMID:24723768

Extracting scientific articles from a large digital archive: BioStor and the Biodiversity Heritage Library.

PubMed

Page, Roderic D M

2011-05-23

The Biodiversity Heritage Library (BHL) is a large digital archive of legacy biological literature, comprising over 31 million pages scanned from books, monographs, and journals. During the digitisation process basic metadata about the scanned items is recorded, but not article-level metadata. Given that the article is the standard unit of citation, this makes it difficult to locate cited literature in BHL. Adding the ability to easily find articles in BHL would greatly enhance the value of the archive. A service was developed to locate articles in BHL based on matching article metadata to BHL metadata using approximate string matching, regular expressions, and string alignment. This article locating service is exposed as a standard OpenURL resolver on the BioStor web site http://biostor.org/openurl/. This resolver can be used on the web, or called by bibliographic tools that support OpenURL. BioStor provides tools for extracting, annotating, and visualising articles from the Biodiversity Heritage Library. BioStor is available from http://biostor.org/.

OlyMPUS - The Ontology-based Metadata Portal for Unified Semantics

NASA Astrophysics Data System (ADS)

Huffer, E.; Gleason, J. L.

2015-12-01

The Ontology-based Metadata Portal for Unified Semantics (OlyMPUS), funded by the NASA Earth Science Technology Office Advanced Information Systems Technology program, is an end-to-end system designed to support data consumers and data providers, enabling the latter to register their data sets and provision them with the semantically rich metadata that drives the Ontology-Driven Interactive Search Environment for Earth Sciences (ODISEES). OlyMPUS leverages the semantics and reasoning capabilities of ODISEES to provide data producers with a semi-automated interface for producing the semantically rich metadata needed to support ODISEES' data discovery and access services. It integrates the ODISEES metadata search system with multiple NASA data delivery tools to enable data consumers to create customized data sets for download to their computers, or for NASA Advanced Supercomputing (NAS) facility registered users, directly to NAS storage resources for access by applications running on NAS supercomputers. A core function of NASA's Earth Science Division is research and analysis that uses the full spectrum of data products available in NASA archives. Scientists need to perform complex analyses that identify correlations and non-obvious relationships across all types of Earth System phenomena. Comprehensive analytics are hindered, however, by the fact that many Earth science data products are disparate and hard to synthesize. Variations in how data are collected, processed, gridded, and stored, create challenges for data interoperability and synthesis, which are exacerbated by the sheer volume of available data. Robust, semantically rich metadata can support tools for data discovery and facilitate machine-to-machine transactions with services such as data subsetting, regridding, and reformatting. Such capabilities are critical to enabling the research activities integral to NASA's strategic plans. However, as metadata requirements increase and competing standards emerge, metadata provisioning becomes increasingly burdensome to data producers. The OlyMPUS system helps data providers produce semantically rich metadata, making their data more accessible to data consumers, and helps data consumers quickly discover and download the right data for their research.

Web Monitoring of EOS Front-End Ground Operations, Science Downlinks and Level 0 Processing

NASA Technical Reports Server (NTRS)

Cordier, Guy R.; Wilkinson, Chris; McLemore, Bruce

2008-01-01

This paper addresses the efforts undertaken and the technology deployed to aggregate and distribute the metadata characterizing the real-time operations associated with NASA Earth Observing Systems (EOS) high-rate front-end systems and the science data collected at multiple ground stations and forwarded to the Goddard Space Flight Center for level 0 processing. Station operators, mission project management personnel, spacecraft flight operations personnel and data end-users for various EOS missions can retrieve the information at any time from any location having access to the internet. The users are distributed and the EOS systems are distributed but the centralized metadata accessed via an external web server provide an effective global and detailed view of the enterprise-wide events as they are happening. The data-driven architecture and the implementation of applied middleware technology, open source database, open source monitoring tools, and external web server converge nicely to fulfill the various needs of the enterprise. The timeliness and content of the information provided are key to making timely and correct decisions which reduce project risk and enhance overall customer satisfaction. The authors discuss security measures employed to limit access of data to authorized users only.

Deploying the ATLAS Metadata Interface (AMI) on the cloud with Jenkins

NASA Astrophysics Data System (ADS)

Lambert, F.; Odier, J.; Fulachier, J.; ATLAS Collaboration

2017-10-01

The ATLAS Metadata Interface (AMI) is a mature application of more than 15 years of existence. Mainly used by the ATLAS experiment at CERN, it consists of a very generic tool ecosystem for metadata aggregation and cataloguing. AMI is used by the ATLAS production system, therefore the service must guarantee a high level of availability. We describe our monitoring and administration systems, and the Jenkins-based strategy used to dynamically test and deploy cloud OpenStack nodes on demand.

Integrated workflows for spiking neuronal network simulations

PubMed Central

Antolík, Ján; Davison, Andrew P.

2013-01-01

The increasing availability of computational resources is enabling more detailed, realistic modeling in computational neuroscience, resulting in a shift toward more heterogeneous models of neuronal circuits, and employment of complex experimental protocols. This poses a challenge for existing tool chains, as the set of tools involved in a typical modeler's workflow is expanding concomitantly, with growing complexity in the metadata flowing between them. For many parts of the workflow, a range of tools is available; however, numerous areas lack dedicated tools, while integration of existing tools is limited. This forces modelers to either handle the workflow manually, leading to errors, or to write substantial amounts of code to automate parts of the workflow, in both cases reducing their productivity. To address these issues, we have developed Mozaik: a workflow system for spiking neuronal network simulations written in Python. Mozaik integrates model, experiment and stimulation specification, simulation execution, data storage, data analysis and visualization into a single automated workflow, ensuring that all relevant metadata are available to all workflow components. It is based on several existing tools, including PyNN, Neo, and Matplotlib. It offers a declarative way to specify models and recording configurations using hierarchically organized configuration files. Mozaik automatically records all data together with all relevant metadata about the experimental context, allowing automation of the analysis and visualization stages. Mozaik has a modular architecture, and the existing modules are designed to be extensible with minimal programming effort. Mozaik increases the productivity of running virtual experiments on highly structured neuronal networks by automating the entire experimental cycle, while increasing the reliability of modeling studies by relieving the user from manual handling of the flow of metadata between the individual workflow stages. PMID:24368902

Integrated workflows for spiking neuronal network simulations.

PubMed

Antolík, Ján; Davison, Andrew P

2013-01-01

The increasing availability of computational resources is enabling more detailed, realistic modeling in computational neuroscience, resulting in a shift toward more heterogeneous models of neuronal circuits, and employment of complex experimental protocols. This poses a challenge for existing tool chains, as the set of tools involved in a typical modeler's workflow is expanding concomitantly, with growing complexity in the metadata flowing between them. For many parts of the workflow, a range of tools is available; however, numerous areas lack dedicated tools, while integration of existing tools is limited. This forces modelers to either handle the workflow manually, leading to errors, or to write substantial amounts of code to automate parts of the workflow, in both cases reducing their productivity. To address these issues, we have developed Mozaik: a workflow system for spiking neuronal network simulations written in Python. Mozaik integrates model, experiment and stimulation specification, simulation execution, data storage, data analysis and visualization into a single automated workflow, ensuring that all relevant metadata are available to all workflow components. It is based on several existing tools, including PyNN, Neo, and Matplotlib. It offers a declarative way to specify models and recording configurations using hierarchically organized configuration files. Mozaik automatically records all data together with all relevant metadata about the experimental context, allowing automation of the analysis and visualization stages. Mozaik has a modular architecture, and the existing modules are designed to be extensible with minimal programming effort. Mozaik increases the productivity of running virtual experiments on highly structured neuronal networks by automating the entire experimental cycle, while increasing the reliability of modeling studies by relieving the user from manual handling of the flow of metadata between the individual workflow stages.

A Flexible Online Metadata Editing and Management System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aguilar, Raul; Pan, Jerry Yun; Gries, Corinna

2010-01-01

A metadata editing and management system is being developed employing state of the art XML technologies. A modular and distributed design was chosen for scalability, flexibility, options for customizations, and the possibility to add more functionality at a later stage. The system consists of a desktop design tool or schema walker used to generate code for the actual online editor, a native XML database, and an online user access management application. The design tool is a Java Swing application that reads an XML schema, provides the designer with options to combine input fields into online forms and give the fieldsmore » user friendly tags. Based on design decisions, the tool generates code for the online metadata editor. The code generated is an implementation of the XForms standard using the Orbeon Framework. The design tool fulfills two requirements: First, data entry forms based on one schema may be customized at design time and second data entry applications may be generated for any valid XML schema without relying on custom information in the schema. However, the customized information generated at design time is saved in a configuration file which may be re-used and changed again in the design tool. Future developments will add functionality to the design tool to integrate help text, tool tips, project specific keyword lists, and thesaurus services. Additional styling of the finished editor is accomplished via cascading style sheets which may be further customized and different look-and-feels may be accumulated through the community process. The customized editor produces XML files in compliance with the original schema, however, data from the current page is saved into a native XML database whenever the user moves to the next screen or pushes the save button independently of validity. Currently the system uses the open source XML database eXist for storage and management, which comes with third party online and desktop management tools. However, access to metadata files in the application introduced here is managed in a custom online module, using a MySQL backend accessed by a simple Java Server Faces front end. A flexible system with three grouping options, organization, group and single editing access is provided. Three levels were chosen to distribute administrative responsibilities and handle the common situation of an information manager entering the bulk of the metadata but leave specifics to the actual data provider.« less

Interoperable Solar Data and Metadata via LISIRD 3

NASA Astrophysics Data System (ADS)

Wilson, A.; Lindholm, D. M.; Pankratz, C. K.; Snow, M. A.; Woods, T. N.

2015-12-01

LISIRD 3 is a major upgrade of the LASP Interactive Solar Irradiance Data Center (LISIRD), which serves several dozen space based solar irradiance and related data products to the public. Through interactive plots, LISIRD 3 provides data browsing supported by data subsetting and aggregation. Incorporating a semantically enabled metadata repository, LISIRD 3 users see current, vetted, consistent information about the datasets offered. Users can now also search for datasets based on metadata fields such as dataset type and/or spectral or temporal range. This semantic database enables metadata browsing, so users can discover the relationships between datasets, instruments, spacecraft, mission and PI. The database also enables creation and publication of metadata records in a variety of formats, such as SPASE or ISO, making these datasets more discoverable. The database also enables the possibility of a public SPARQL endpoint, making the metadata browsable in an automated fashion. LISIRD 3's data access middleware, LaTiS, provides dynamic, on demand reformatting of data and timestamps, subsetting and aggregation, and other server side functionality via a RESTful OPeNDAP compliant API, enabling interoperability between LASP datasets and many common tools. LISIRD 3's templated front end design, coupled with the uniform data interface offered by LaTiS, allows easy integration of new datasets. Consequently the number and variety of datasets offered by LISIRD has grown to encompass several dozen, with many more to come. This poster will discuss design and implementation of LISIRD 3, including tools used, capabilities enabled, and issues encountered.

ATLAS Metadata Infrastructure Evolution for Run 2 and Beyond

NASA Astrophysics Data System (ADS)

van Gemmeren, P.; Cranshaw, J.; Malon, D.; Vaniachine, A.

2015-12-01

ATLAS developed and employed for Run 1 of the Large Hadron Collider a sophisticated infrastructure for metadata handling in event processing jobs. This infrastructure profits from a rich feature set provided by the ATLAS execution control framework, including standardized interfaces and invocation mechanisms for tools and services, segregation of transient data stores with concomitant object lifetime management, and mechanisms for handling occurrences asynchronous to the control framework's state machine transitions. This metadata infrastructure is evolving and being extended for Run 2 to allow its use and reuse in downstream physics analyses, analyses that may or may not utilize the ATLAS control framework. At the same time, multiprocessing versions of the control framework and the requirements of future multithreaded frameworks are leading to redesign of components that use an incident-handling approach to asynchrony. The increased use of scatter-gather architectures, both local and distributed, requires further enhancement of metadata infrastructure in order to ensure semantic coherence and robust bookkeeping. This paper describes the evolution of ATLAS metadata infrastructure for Run 2 and beyond, including the transition to dual-use tools—tools that can operate inside or outside the ATLAS control framework—and the implications thereof. It further examines how the design of this infrastructure is changing to accommodate the requirements of future frameworks and emerging event processing architectures.

Effective use of metadata in the integration and analysis of multi-dimensional optical data

NASA Astrophysics Data System (ADS)

Pastorello, G. Z.; Gamon, J. A.

2012-12-01

Data discovery and integration relies on adequate metadata. However, creating and maintaining metadata is time consuming and often poorly addressed or avoided altogether, leading to problems in later data analysis and exchange. This is particularly true for research fields in which metadata standards do not yet exist or are under development, or within smaller research groups without enough resources. Vegetation monitoring using in-situ and remote optical sensing is an example of such a domain. In this area, data are inherently multi-dimensional, with spatial, temporal and spectral dimensions usually being well characterized. Other equally important aspects, however, might be inadequately translated into metadata. Examples include equipment specifications and calibrations, field/lab notes and field/lab protocols (e.g., sampling regimen, spectral calibration, atmospheric correction, sensor view angle, illumination angle), data processing choices (e.g., methods for gap filling, filtering and aggregation of data), quality assurance, and documentation of data sources, ownership and licensing. Each of these aspects can be important as metadata for search and discovery, but they can also be used as key data fields in their own right. If each of these aspects is also understood as an "extra dimension," it is possible to take advantage of them to simplify the data acquisition, integration, analysis, visualization and exchange cycle. Simple examples include selecting data sets of interest early in the integration process (e.g., only data collected according to a specific field sampling protocol) or applying appropriate data processing operations to different parts of a data set (e.g., adaptive processing for data collected under different sky conditions). More interesting scenarios involve guided navigation and visualization of data sets based on these extra dimensions, as well as partitioning data sets to highlight relevant subsets to be made available for exchange. The DAX (Data Acquisition to eXchange) Web-based tool uses a flexible metadata representation model and takes advantage of multi-dimensional data structures to translate metadata types into data dimensions, effectively reshaping data sets according to available metadata. With that, metadata is tightly integrated into the acquisition-to-exchange cycle, allowing for more focused exploration of data sets while also increasing the value of, and incentives for, keeping good metadata. The tool is being developed and tested with optical data collected in different settings, including laboratory, field, airborne, and satellite platforms.

Sequencing Data Discovery and Integration for Earth System Science with MetaSeek

NASA Astrophysics Data System (ADS)

Hoarfrost, A.; Brown, N.; Arnosti, C.

2017-12-01

Microbial communities play a central role in biogeochemical cycles. Sequencing data resources from environmental sources have grown exponentially in recent years, and represent a singular opportunity to investigate microbial interactions with Earth system processes. Carrying out such meta-analyses depends on our ability to discover and curate sequencing data into large-scale integrated datasets. However, such integration efforts are currently challenging and time-consuming, with sequencing data scattered across multiple repositories and metadata that is not easily or comprehensively searchable. MetaSeek is a sequencing data discovery tool that integrates sequencing metadata from all the major data repositories, allowing the user to search and filter on datasets in a lightweight application with an intuitive, easy-to-use web-based interface. Users can save and share curated datasets, while other users can browse these data integrations or use them as a jumping off point for their own curation. Missing and/or erroneous metadata are inferred automatically where possible, and where not possible, users are prompted to contribute to the improvement of the sequencing metadata pool by correcting and amending metadata errors. Once an integrated dataset has been curated, users can follow simple instructions to download their raw data and quickly begin their investigations. In addition to the online interface, the MetaSeek database is easily queryable via an open API, further enabling users and facilitating integrations of MetaSeek with other data curation tools. This tool lowers the barriers to curation and integration of environmental sequencing data, clearing the path forward to illuminating the ecosystem-scale interactions between biological and abiotic processes.

UAV field demonstration of social media enabled tactical data link

NASA Astrophysics Data System (ADS)

Olson, Christopher C.; Xu, Da; Martin, Sean R.; Castelli, Jonathan C.; Newman, Andrew J.

2015-05-01

This paper addresses the problem of enabling Command and Control (C2) and data exfiltration functions for missions using small, unmanned, airborne surveillance and reconnaissance platforms. The authors demonstrated the feasibility of using existing commercial wireless networks as the data transmission infrastructure to support Unmanned Aerial Vehicle (UAV) autonomy functions such as transmission of commands, imagery, metadata, and multi-vehicle coordination messages. The authors developed and integrated a C2 Android application for ground users with a common smart phone, a C2 and data exfiltration Android application deployed on-board the UAVs, and a web server with database to disseminate the collected data to distributed users using standard web browsers. The authors performed a mission-relevant field test and demonstration in which operators commanded a UAV from an Android device to search and loiter; and remote users viewed imagery, video, and metadata via web server to identify and track a vehicle on the ground. Social media served as the tactical data link for all command messages, images, videos, and metadata during the field demonstration. Imagery, video, and metadata were transmitted from the UAV to the web server via multiple Twitter, Flickr, Facebook, YouTube, and similar media accounts. The web server reassembled images and video with corresponding metadata for distributed users. The UAV autopilot communicated with the on-board Android device via on-board Bluetooth network.

EOS ODL Metadata On-line Viewer

NASA Astrophysics Data System (ADS)

Yang, J.; Rabi, M.; Bane, B.; Ullman, R.

2002-12-01

We have recently developed and deployed an EOS ODL metadata on-line viewer. The EOS ODL metadata viewer is a web server that takes: 1) an EOS metadata file in Object Description Language (ODL), 2) parameters, such as which metadata to view and what style of display to use, and returns an HTML or XML document displaying the requested metadata in the requested style. This tool is developed to address widespread complaints by science community that the EOS Data and Information System (EOSDIS) metadata files in ODL are difficult to read by allowing users to upload and view an ODL metadata file in different styles using a web browser. Users have the selection to view all the metadata or part of the metadata, such as Collection metadata, Granule metadata, or Unsupported Metadata. Choices of display styles include 1) Web: a mouseable display with tabs and turn-down menus, 2) Outline: Formatted and colored text, suitable for printing, 3) Generic: Simple indented text, a direct representation of the underlying ODL metadata, and 4) None: No stylesheet is applied and the XML generated by the converter is returned directly. Not all display styles are implemented for all the metadata choices. For example, Web style is only implemented for Collection and Granule metadata groups with known attribute fields, but not for Unsupported, Other, and All metadata. The overall strategy of the ODL viewer is to transform an ODL metadata file to a viewable HTML in two steps. The first step is to convert the ODL metadata file to an XML using a Java-based parser/translator called ODL2XML. The second step is to transform the XML to an HTML using stylesheets. Both operations are done on the server side. This allows a lot of flexibility in the final result, and is very portable cross-platform. Perl CGI behind the Apache web server is used to run the Java ODL2XML, and then run the results through an XSLT processor. The EOS ODL viewer can be accessed from either a PC or a Mac using Internet Explorer 5.0+ or Netscape 4.7+.

Progress and Plans in Support of the Polar Community

NASA Technical Reports Server (NTRS)

Olsen, Lola M.; Meaux, Melanie F.

2006-01-01

Feedback provided by the Antarctic community has proven instrumental in positively influencing the direction of the GCMD's development. For example, in response to requests for a stand alone metadata authoring tool, a new shareable software package called docBUILDER solo will be released to the public in March 2006. This tool permits researchers to document their data during experiments and observational periods in the field. The international polar community has also played a key role in encouraging support for the foreign language character set in the metadata display and tools (10% of the records in the AMD hold foreign characters). In the upcoming release, the full ISO character set, which also includes mathematical symbols, will be supported. Additional upgrades include the ability for users to search for data sets based on pre-selected temporal and spatial resolution ranges. Data providers are strongly encouraged to populate the resolution fields for their data sets, although these fields are not currently required. In prior versions, browser incompatibilities often resulted in unreliable performance for users attempting to initiate a spatial search using a map based on Java applet technology. The GCMD will offer an integrated Google map and date search, replacing the applet technology and enhancing the geospatial and temporal searches. It is estimated that 30% of the records in the AMD have direct access to data. A growing number of these records can be accessed through data service links. Related data services are therefore becoming valuable assets in facilitating the use and visualization of data. Users will gain the ability to refine services using the same options as those available for data set searches. Data providers are encouraged to describe available data-related services through the directory. Future plans include offering web services through a SOAP interface and extending semantic queries for the polar regions through the use of ontologies. The Open Archives Initiative's (OAI) Protocol for Metadata Harvesting (PMH) has been successfully tested with several organizations and appears to be a prime candidate for sharing metadata within the community. The GCMD anticipates contributing to the design of the data management system for the International Polar Year and to the ongoing efforts in the years to come. Further enhancements will be discussed at the meeting.

ODISEES: A New Paradigm in Data Access

NASA Astrophysics Data System (ADS)

Huffer, E.; Little, M. M.; Kusterer, J.

2013-12-01

As part of its ongoing efforts to improve access to data, the Atmospheric Science Data Center has developed a high-precision Earth Science domain ontology (the 'ES Ontology') implemented in a graph database ('the Semantic Metadata Repository') that is used to store detailed, semantically-enhanced, parameter-level metadata for ASDC data products. The ES Ontology provides the semantic infrastructure needed to drive the ASDC's Ontology-Driven Interactive Search Environment for Earth Science ('ODISEES'), a data discovery and access tool, and will support additional data services such as analytics and visualization. The ES ontology is designed on the premise that naming conventions alone are not adequate to provide the information needed by prospective data consumers to assess the suitability of a given dataset for their research requirements; nor are current metadata conventions adequate to support seamless machine-to-machine interactions between file servers and end-user applications. Data consumers need information not only about what two data elements have in common, but also about how they are different. End-user applications need consistent, detailed metadata to support real-time data interoperability. The ES ontology is a highly precise, bottom-up, queriable model of the Earth Science domain that focuses on critical details about the measurable phenomena, instrument techniques, data processing methods, and data file structures. Earth Science parameters are described in detail in the ES Ontology and mapped to the corresponding variables that occur in ASDC datasets. Variables are in turn mapped to well-annotated representations of the datasets that they occur in, the instrument(s) used to create them, the instrument platforms, the processing methods, etc., creating a linked-data structure that allows both human and machine users to access a wealth of information critical to understanding and manipulating the data. The mappings are recorded in the Semantic Metadata Repository as RDF-triples. An off-the-shelf Ontology Development Environment and a custom Metadata Conversion Tool comprise a human-machine/machine-machine hybrid tool that partially automates the creation of metadata as RDF-triples by interfacing with existing metadata repositories and providing a user interface that solicits input from a human user, when needed. RDF-triples are pushed to the Ontology Development Environment, where a reasoning engine executes a series of inference rules whose antecedent conditions can be satisfied by the initial set of RDF-triples, thereby generating the additional detailed metadata that is missing in existing repositories. A SPARQL Endpoint, a web-based query service and a Graphical User Interface allow prospective data consumers - even those with no familiarity with NASA data products - to search the metadata repository to find and order data products that meet their exact specifications. A web-based API will provide an interface for machine-to-machine transactions.

Combined use of semantics and metadata to manage Research Data Life Cycle in Environmental Sciences

NASA Astrophysics Data System (ADS)

Aguilar Gómez, Fernando; de Lucas, Jesús Marco; Pertinez, Esther; Palacio, Aida

2017-04-01

The use of metadata to contextualize datasets is quite extended in Earth System Sciences. There are some initiatives and available tools to help data managers to choose the best metadata standard that fit their use cases, like the DCC Metadata Directory (http://www.dcc.ac.uk/resources/metadata-standards). In our use case, we have been gathering physical, chemical and biological data from a water reservoir since 2010. A well metadata definition is crucial not only to contextualize our own data but also to integrate datasets from other sources like satellites or meteorological agencies. That is why we have chosen EML (Ecological Metadata Language), which integrates many different elements to define a dataset, including the project context, instrumentation and parameters definition, and the software used to process, provide quality controls and include the publication details. Those metadata elements can contribute to help both human and machines to understand and process the dataset. However, the use of metadata is not enough to fully support the data life cycle, from the Data Management Plan definition to the Publication and Re-use. To do so, we need to define not only metadata and attributes but also the relationships between them, so semantics are needed. Ontologies, being a knowledge representation, can contribute to define the elements of a research data life cycle, including DMP, datasets, software, etc. They also can define how the different elements are related between them and how they interact. The first advantage of developing an ontology of a knowledge domain is that they provide a common vocabulary hierarchy (i.e. a conceptual schema) that can be used and standardized by all the agents interested in the domain (either humans or machines). This way of using ontologies is one of the basis of the Semantic Web, where ontologies are set to play a key role in establishing a common terminology between agents. To develop an ontology we are using a graphical tool Protégé, which is a graphical ontology-development tool that supports a rich knowledge model and it is open-source and freely available. To process and manage the ontology, we are using Semantic MediaWiki, which is able to process queries. Semantic MediaWiki is an extension of MediaWiki where we can do semantic search and export data in RDF. Our final goal is integrating our data repository portal and semantic processing engine in order to have a complete system to manage the data life cycle stages and their relationships, including machine-actionable DMP solution, datasets and software management, computing resources for processing and analysis and publication features (DOI mint). This way we will be able to reproduce the full data life cycle chain warranting the FAIR+R principles.

Comprehensive Optimal Manpower and Personnel Analytic Simulation System (COMPASS)

DTIC Science & Technology

2009-10-01

4 The EDB consists of 4 major components (some of which are re-usable): 1. Metadata Editor ( MDE ): Also considered a leaf node, the metadata...end-user queries via the QB. The EDB supports multiple instances of the MDE , although currently, only a single instance is recommended. 2 Query...the MSB is a central collection of web services, responsible for the authentication and authorization of users, maintenance of the EDB metadata

Engaging a community towards marine cyberinfrastructure: Lessons Learned from The Marine Metadata Interoperability initiative

NASA Astrophysics Data System (ADS)

Galbraith, N. R.; Graybeal, J.; Bermudez, L. E.; Wright, D.

2005-12-01

The Marine Metadata Interoperability (MMI) initiative promotes the exchange, integration and use of marine data through enhanced data publishing, discovery, documentation and accessibility. The project, operating since late 2004, presents several cultural organizational challenges because of the diversity of participants: scientists, technical experts, and data managers from around the world, all working in organizations with different corporate cultures, funding structures, and systems of decision-making. MMI provides educational resources at several levels. For instance, short introductions to metadata concepts are available, as well as guides and "cookbooks" for the quick and efficient preparation of marine metadata. For those who are building major marine data systems, including ocean-observing capabilities, there are training materials, marine metadata content examples, and resources for mapping elements between different metadata standards. The MMI also provides examples of good metadata practices in existing data systems, including the EU's Marine XML project, and functioning ocean/coastal clearinghouses and atlases developed by MMI team members. Communication tools that help build community: 1) Website, used to introduce the initiative to new visitors, and to provide in-depth guidance and resources to members and visitors. The site is built using Plone, an open source web content management system. Plone allows the site to serve as a wiki, to which every user can contribute material. This keeps the membership engaged and spreads the responsibility for the tasks of updating and expanding the site. 2) Email-lists, to engage the broad ocean sciences community. The discussion forums "news," "ask," and "site-help" are available for receiving regular updates on MMI activities, seeking advice or support on projects and standards, or for assistance with using the MMI site. Internal email lists are provided for the Technical Team, the Steering Committee and Executive Committee, and for several content-centered teams. These lists help keep committee members connected, and have been very successful in building consensus and momentum. 3) Regularly scheduled telecons, to provide the chance for interaction between members without the need to physically attend meetings. Both the steering committee and the technical team convene via phone every month. Discussions are guided by agendas published in advance, and minutes are kept on-line for reference. These telecons have been an important tool in moving the MMI project forward; they give members an opportunity for informal discussion and provide a timeframe for accomplishing tasks. 4) Workshops, to make progress towards community agreement, such as the technical workshop "Advancing Domain Vocabularies" August 9-11, 2005, in Boulder, Colorado, where featured domain and metadata experts developed mappings between existing marine metadata vocabularies. Most of the work of the meeting was performed in six small, carefully organized breakout teams, oriented around specific domains. 5) Calendar of events, to keep update the users and where any event related to marine metadata and interoperability can be posted. 6) Specific tools to reach agreements among distributed communities. For example, we developed a tool called Vocabulary Integration Environment (VINE), that allows formalized agreements of mappings across different vocabularies.

Metadata Mapper: a web service for mapping data between independent visual analysis components, guided by perceptual rules

NASA Astrophysics Data System (ADS)

Rogowitz, Bernice E.; Matasci, Naim

2011-03-01

The explosion of online scientific data from experiments, simulations, and observations has given rise to an avalanche of algorithmic, visualization and imaging methods. There has also been enormous growth in the introduction of tools that provide interactive interfaces for exploring these data dynamically. Most systems, however, do not support the realtime exploration of patterns and relationships across tools and do not provide guidance on which colors, colormaps or visual metaphors will be most effective. In this paper, we introduce a general architecture for sharing metadata between applications and a "Metadata Mapper" component that allows the analyst to decide how metadata from one component should be represented in another, guided by perceptual rules. This system is designed to support "brushing [1]," in which highlighting a region of interest in one application automatically highlights corresponding values in another, allowing the scientist to develop insights from multiple sources. Our work builds on the component-based iPlant Cyberinfrastructure [2] and provides a general approach to supporting interactive, exploration across independent visualization and visual analysis components.

Extracting scientific articles from a large digital archive: BioStor and the Biodiversity Heritage Library

PubMed Central

2011-01-01

Background The Biodiversity Heritage Library (BHL) is a large digital archive of legacy biological literature, comprising over 31 million pages scanned from books, monographs, and journals. During the digitisation process basic metadata about the scanned items is recorded, but not article-level metadata. Given that the article is the standard unit of citation, this makes it difficult to locate cited literature in BHL. Adding the ability to easily find articles in BHL would greatly enhance the value of the archive. Description A service was developed to locate articles in BHL based on matching article metadata to BHL metadata using approximate string matching, regular expressions, and string alignment. This article locating service is exposed as a standard OpenURL resolver on the BioStor web site http://biostor.org/openurl/. This resolver can be used on the web, or called by bibliographic tools that support OpenURL. Conclusions BioStor provides tools for extracting, annotating, and visualising articles from the Biodiversity Heritage Library. BioStor is available from http://biostor.org/. PMID:21605356

Metadata-Driven SOA-Based Application for Facilitation of Real-Time Data Warehousing

NASA Astrophysics Data System (ADS)

Pintar, Damir; Vranić, Mihaela; Skočir, Zoran

Service-oriented architecture (SOA) has already been widely recognized as an effective paradigm for achieving integration of diverse information systems. SOA-based applications can cross boundaries of platforms, operation systems and proprietary data standards, commonly through the usage of Web Services technology. On the other side, metadata is also commonly referred to as a potential integration tool given the fact that standardized metadata objects can provide useful information about specifics of unknown information systems with which one has interest in communicating with, using an approach commonly called "model-based integration". This paper presents the result of research regarding possible synergy between those two integration facilitators. This is accomplished with a vertical example of a metadata-driven SOA-based business process that provides ETL (Extraction, Transformation and Loading) and metadata services to a data warehousing system in need of a real-time ETL support.

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis.

PubMed

Simonyan, Vahan; Mazumder, Raja

2014-09-30

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis.

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis

PubMed Central

Simonyan, Vahan; Mazumder, Raja

2014-01-01

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis. PMID:25271953

The PDS4 Data Dictionary Tool - Metadata Design for Data Preparers

NASA Astrophysics Data System (ADS)

Raugh, A.; Hughes, J. S.

2017-12-01

One of the major design goals of the PDS4 development effort was to create an extendable Information Model (IM) for the archive, and to allow mission data designers/preparers to create extensions for metadata definitions specific to their own contexts. This capability is critical for the Planetary Data System - an archive that deals with a data collection that is diverse along virtually every conceivable axis. Amid such diversity in the data itself, it is in the best interests of the PDS archive and its users that all extensions to the IM follow the same design techniques, conventions, and restrictions as the core implementation itself. But it is unrealistic to expect mission data designers to acquire expertise in information modeling, model-driven design, ontology, schema formulation, and PDS4 design conventions and philosophy in order to define their own metadata. To bridge that expertise gap and bring the power of information modeling to the data label designer, the PDS Engineering Node has developed the data dictionary creation tool known as "LDDTool". This tool incorporates the same software used to maintain and extend the core IM, packaged with an interface that enables a developer to create his extension to the IM using the same, standards-based metadata framework PDS itself uses. Through this interface, the novice dictionary developer has immediate access to the common set of data types and unit classes for defining attributes, and a straight-forward method for constructing classes. The more experienced developer, using the same tool, has access to more sophisticated modeling methods like abstraction and extension, and can define context-specific validation rules. We present the key features of the PDS Local Data Dictionary Tool, which both supports the development of extensions to the PDS4 IM, and ensures their compatibility with the IM.

Mercury Toolset for Spatiotemporal Metadata

NASA Technical Reports Server (NTRS)

Wilson, Bruce E.; Palanisamy, Giri; Devarakonda, Ranjeet; Rhyne, B. Timothy; Lindsley, Chris; Green, James

2010-01-01

Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily) harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.

Mercury Toolset for Spatiotemporal Metadata

NASA Astrophysics Data System (ADS)

Devarakonda, Ranjeet; Palanisamy, Giri; Green, James; Wilson, Bruce; Rhyne, B. Timothy; Lindsley, Chris

2010-06-01

Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily)harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.

Command Center Training Tool (C2T2)

NASA Technical Reports Server (NTRS)

Jones, Phillip; Drucker, Nich; Mathews, Reejo; Stanton, Laura; Merkle, Ed

2012-01-01

This abstract presents the training approach taken to create a management-centered, experiential learning solution for the Virginia Port Authority's Port Command Center. The resultant tool, called the Command Center Training Tool (C2T2), follows a holistic approach integrated across the training management cycle and within a single environment. The approach allows a single training manager to progress from training design through execution and AAR. The approach starts with modeling the training organization, identifying the organizational elements and their individual and collective performance requirements, including organizational-specific performance scoring ontologies. Next, the developer specifies conditions, the problems, and constructs that compose exercises and drive experiential learning. These conditions are defined by incidents, which denote a single, multi-media datum, and scenarios, which are stories told by incidents. To these layered, modular components, previously developed meta-data is attached, including associated performance requirements. The components are then stored in a searchable library An event developer can create a training event by searching the library based on metadata and then selecting and loading the resultant modular pieces. This loading process brings into the training event all the previously associated task and teamwork material as well as AAR preparation materials. The approach includes tools within an integrated management environment that places these materials at the fingertips of the event facilitator such that, in real time, the facilitator can track training audience performance and resultantly modify the training event. The approach also supports the concentrated knowledge management requirements for rapid preparation of an extensive AAR. This approach supports the integrated training cycle and allows a management-based perspective and advanced tools, through which a complex, thorough training event can be developed.

Achieving Sub-Second Search in the CMR

NASA Astrophysics Data System (ADS)

Gilman, J.; Baynes, K.; Pilone, D.; Mitchell, A. E.; Murphy, K. J.

2014-12-01

The Common Metadata Repository (CMR) is the next generation Earth Science Metadata catalog for NASA's Earth Observing data. It joins together the holdings from the EOS Clearing House (ECHO) and the Global Change Master Directory (GCMD), creating a unified, authoritative source for EOSDIS metadata. The CMR allows ingest in many different formats while providing consistent search behavior and retrieval in any supported format. Performance is a critical component of the CMR, ensuring improved data discovery and client interactivity. The CMR delivers sub-second search performance for any of the common query conditions (including spatial) across hundreds of millions of metadata granules. It also allows the addition of new metadata concepts such as visualizations, parameter metadata, and documentation. The CMR's goals presented many challenges. This talk will describe the CMR architecture, design, and innovations that were made to achieve its goals. This includes: * Architectural features like immutability and backpressure. * Data management techniques such as caching and parallel loading that give big performance gains. * Open Source and COTS tools like Elasticsearch search engine. * Adoption of Clojure, a functional programming language for the Java Virtual Machine. * Development of a custom spatial search plugin for Elasticsearch and why it was necessary. * Introduction of a unified model for metadata that maps every supported metadata format to a consistent domain model.

CHARMe Commentary metadata for Climate Science: collecting, linking and sharing user feedback on climate datasets

NASA Astrophysics Data System (ADS)

Blower, Jon; Lawrence, Bryan; Kershaw, Philip; Nagni, Maurizio

2014-05-01

The research process can be thought of as an iterative activity, initiated based on prior domain knowledge, as well on a number of external inputs, and producing a range of outputs including datasets, studies and peer reviewed publications. These outputs may describe the problem under study, the methodology used, the results obtained, etc. In any new publication, the author may cite or comment other papers or datasets in order to support their research hypothesis. However, as their work progresses, the researcher may draw from many other latent channels of information. These could include for example, a private conversation following a lecture or during a social dinner; an opinion expressed concerning some significant event such as an earthquake or for example a satellite failure. In addition, other sources of information of grey literature are important public such as informal papers such as the arxiv deposit, reports and studies. The climate science community is not an exception to this pattern; the CHARMe project, funded under the European FP7 framework, is developing an online system for collecting and sharing user feedback on climate datasets. This is to help users judge how suitable such climate data are for an intended application. The user feedback could be comments about assessments, citations, or provenance of the dataset, or other information such as descriptions of uncertainty or data quality. We define this as a distinct category of metadata called Commentary or C-metadata. We link C-metadata with target climate datasets using a Linked Data approach via the Open Annotation data model. In the context of Linked Data, C-metadata plays the role of a resource which, depending on its nature, may be accessed as simple text or as more structured content. The project is implementing a range of software tools to create, search or visualize C-metadata including a JavaScript plugin enabling this functionality to be integrated in situ with data provider portals. Since commentary metadata may originate from a range of sources, moderation of this information will become a crucial issue. If the project is successful, expert human moderation (analogous to peer-review) will become impracticable as annotation numbers increase, and some combination of algorithmic and crowd-sourced evaluation of commentary metadata will be necessary. To that end, future work will need to extend work under development to enable access control and checking of inputs, to deal with scale.

SIOExplorer: Modern IT Methods and Tools for Digital Library Management

NASA Astrophysics Data System (ADS)

Sutton, D. W.; Helly, J.; Miller, S.; Chase, A.; Clarck, D.

2003-12-01

With more geoscience disciplines becoming data-driven it is increasingly important to utilize modern techniques for data, information and knowledge management. SIOExplorer is a new digital library project with 2 terabytes of oceanographic data collected over the last 50 years on 700 cruises by the Scripps Institution of Oceanography. It is built using a suite of information technology tools and methods that allow for an efficient and effective digital library management system. The library consists of a number of independent collections, each with corresponding metadata formats. The system architecture allows each collection to be built and uploaded based on a collection dependent metadata template file (MTF). This file is used to create the hierarchical structure of the collection, create metadata tables in a relational database, and to populate object metadata files and the collection as a whole. Collections are comprised of arbitrary digital objects stored at the San Diego Supercomputer Center (SDSC) High Performance Storage System (HPSS) and managed using the Storage Resource Broker (SRB), data handling middle ware developed at SDSC. SIOExplorer interoperates with other collections as a data provider through the Open Archives Initiative (OAI) protocol. The user services for SIOExplorer are accessed from CruiseViewer, a Java application served using Java Web Start from the SIOExplorer home page. CruiseViewer is an advanced tool for data discovery and access. It implements general keyword and interactive geospatial search methods for the collections. It uses a basemap to georeference search results on user selected basemaps such as global topography or crustal age. User services include metadata viewing, opening of selective mime type digital objects (such as images, documents and grid files), and downloading of objects (including the brokering of proprietary hold restrictions).

Omics Metadata Management Software (OMMS).

PubMed

Perez-Arriaga, Martha O; Wilson, Susan; Williams, Kelly P; Schoeniger, Joseph; Waymire, Russel L; Powell, Amy Jo

2015-01-01

Next-generation sequencing projects have underappreciated information management tasks requiring detailed attention to specimen curation, nucleic acid sample preparation and sequence production methods required for downstream data processing, comparison, interpretation, sharing and reuse. The few existing metadata management tools for genome-based studies provide weak curatorial frameworks for experimentalists to store and manage idiosyncratic, project-specific information, typically offering no automation supporting unified naming and numbering conventions for sequencing production environments that routinely deal with hundreds, if not thousands of samples at a time. Moreover, existing tools are not readily interfaced with bioinformatics executables, (e.g., BLAST, Bowtie2, custom pipelines). Our application, the Omics Metadata Management Software (OMMS), answers both needs, empowering experimentalists to generate intuitive, consistent metadata, and perform analyses and information management tasks via an intuitive web-based interface. Several use cases with short-read sequence datasets are provided to validate installation and integrated function, and suggest possible methodological road maps for prospective users. Provided examples highlight possible OMMS workflows for metadata curation, multistep analyses, and results management and downloading. The OMMS can be implemented as a stand alone-package for individual laboratories, or can be configured for webbased deployment supporting geographically-dispersed projects. The OMMS was developed using an open-source software base, is flexible, extensible and easily installed and executed. The OMMS can be obtained at http://omms.sandia.gov. The OMMS can be obtained at http://omms.sandia.gov.

Omics Metadata Management Software (OMMS)

PubMed Central

Perez-Arriaga, Martha O; Wilson, Susan; Williams, Kelly P; Schoeniger, Joseph; Waymire, Russel L; Powell, Amy Jo

2015-01-01

Next-generation sequencing projects have underappreciated information management tasks requiring detailed attention to specimen curation, nucleic acid sample preparation and sequence production methods required for downstream data processing, comparison, interpretation, sharing and reuse. The few existing metadata management tools for genome-based studies provide weak curatorial frameworks for experimentalists to store and manage idiosyncratic, project-specific information, typically offering no automation supporting unified naming and numbering conventions for sequencing production environments that routinely deal with hundreds, if not thousands of samples at a time. Moreover, existing tools are not readily interfaced with bioinformatics executables, (e.g., BLAST, Bowtie2, custom pipelines). Our application, the Omics Metadata Management Software (OMMS), answers both needs, empowering experimentalists to generate intuitive, consistent metadata, and perform analyses and information management tasks via an intuitive web-based interface. Several use cases with short-read sequence datasets are provided to validate installation and integrated function, and suggest possible methodological road maps for prospective users. Provided examples highlight possible OMMS workflows for metadata curation, multistep analyses, and results management and downloading. The OMMS can be implemented as a stand alone-package for individual laboratories, or can be configured for webbased deployment supporting geographically-dispersed projects. The OMMS was developed using an open-source software base, is flexible, extensible and easily installed and executed. The OMMS can be obtained at http://omms.sandia.gov. Availability The OMMS can be obtained at http://omms.sandia.gov PMID:26124554

Metadata Exporter for Scientific Photography Management

NASA Astrophysics Data System (ADS)

Staudigel, D.; English, B.; Delaney, R.; Staudigel, H.; Koppers, A.; Hart, S.

2005-12-01

Photographs have become an increasingly important medium, especially with the advent of digital cameras. It has become inexpensive to take photographs and quickly post them on a website. However informative photos may be, they still need to be displayed in a convenient way, and be cataloged in such a manner that makes them easily locatable. Managing the great number of photographs that digital cameras allow and creating a format for efficient dissemination of the information related to the photos is a tedious task. Products such as Apple's iPhoto have greatly eased the task of managing photographs, However, they often have limitations. Un-customizable metadata fields and poor metadata extraction tools limit their scientific usefulness. A solution to this persistent problem is a customizable metadata exporter. On the ALIA expedition, we successfully managed the thousands of digital photos we took. We did this with iPhoto and a version of the exporter that is now available to the public under the name "CustomHTMLExport" (http://www.versiontracker.com/dyn/moreinfo/macosx/27777), currently undergoing formal beta testing This software allows the use of customized metadata fields (including description, time, date, GPS data, etc.), which is exported along with the photo. It can also produce webpages with this data straight from iPhoto, in a much more flexible way than is already allowed. With this tool it becomes very easy to manage and distribute scientific photos.

Towards structured sharing of raw and derived neuroimaging data across existing resources

PubMed Central

Keator, D.B.; Helmer, K.; Steffener, J.; Turner, J.A.; Van Erp, T.G.M.; Gadde, S.; Ashish, N.; Burns, G.A.; Nichols, B.N.

2013-01-01

Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is currently no integrated access mechanism nor an accepted format for the critically important meta-data that is necessary for making use of the combined, available neuroimaging data. In this manuscript, we present work from the Derived Data Working Group, an open-access group sponsored by the Biomedical Informatics Research Network (BIRN) and the International Neuroimaging Coordinating Facility (INCF) focused on practical tools for distributed access to neuroimaging data. The working group develops models and tools facilitating the structured interchange of neuroimaging meta-data and is making progress towards a unified set of tools for such data and meta-data exchange. We report on the key components required for integrated access to raw and derived neuroimaging data as well as associated meta-data and provenance across neuroimaging resources. The components include (1) a structured terminology that provides semantic context to data, (2) a formal data model for neuroimaging with robust tracking of data provenance, (3) a web service-based application programming interface (API) that provides a consistent mechanism to access and query the data model, and (4) a provenance library that can be used for the extraction of provenance data by image analysts and imaging software developers. We believe that the framework and set of tools outlined in this manuscript have great potential for solving many of the issues the neuroimaging community faces when sharing raw and derived neuroimaging data across the various existing database systems for the purpose of accelerating scientific discovery. PMID:23727024

IMG/VR: a database of cultured and uncultured DNA Viruses and retroviruses.

PubMed

Paez-Espino, David; Chen, I-Min A; Palaniappan, Krishna; Ratner, Anna; Chu, Ken; Szeto, Ernest; Pillay, Manoj; Huang, Jinghua; Markowitz, Victor M; Nielsen, Torben; Huntemann, Marcel; K Reddy, T B; Pavlopoulos, Georgios A; Sullivan, Matthew B; Campbell, Barbara J; Chen, Feng; McMahon, Katherine; Hallam, Steve J; Denef, Vincent; Cavicchioli, Ricardo; Caffrey, Sean M; Streit, Wolfgang R; Webster, John; Handley, Kim M; Salekdeh, Ghasem H; Tsesmetzis, Nicolas; Setubal, Joao C; Pope, Phillip B; Liu, Wen-Tso; Rivers, Adam R; Ivanova, Natalia N; Kyrpides, Nikos C

2017-01-04

Viruses represent the most abundant life forms on the planet. Recent experimental and computational improvements have led to a dramatic increase in the number of viral genome sequences identified primarily from metagenomic samples. As a result of the expanding catalog of metagenomic viral sequences, there exists a need for a comprehensive computational platform integrating all these sequences with associated metadata and analytical tools. Here we present IMG/VR (https://img.jgi.doe.gov/vr/), the largest publicly available database of 3908 isolate reference DNA viruses with 264 413 computationally identified viral contigs from >6000 ecologically diverse metagenomic samples. Approximately half of the viral contigs are grouped into genetically distinct quasi-species clusters. Microbial hosts are predicted for 20 000 viral sequences, revealing nine microbial phyla previously unreported to be infected by viruses. Viral sequences can be queried using a variety of associated metadata, including habitat type and geographic location of the samples, or taxonomic classification according to hallmark viral genes. IMG/VR has a user-friendly interface that allows users to interrogate all integrated data and interact by comparing with external sequences, thus serving as an essential resource in the viral genomics community. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

panMetaDocs, eSciDoc, and DOIDB - an infrastructure for the curation and publication of file-based datasets for 'GFZ Data Services'

NASA Astrophysics Data System (ADS)

Ulbricht, Damian; Elger, Kirsten; Bertelmann, Roland; Klump, Jens

2016-04-01

With the foundation of DataCite in 2009 and the technical infrastructure installed in the last six years it has become very easy to create citable dataset DOIs. Nowadays, dataset DOIs are increasingly accepted and required by journals in reference lists of manuscripts. In addition, DataCite provides usage statistics [1] of assigned DOIs and offers a public search API to make research data count. By linking related information to the data, they become more useful for future generations of scientists. For this purpose, several identifier systems, as ISBN for books, ISSN for journals, DOI for articles or related data, Orcid for authors, and IGSN for physical samples can be attached to DOIs using the DataCite metadata schema [2]. While these are good preconditions to publish data, free and open solutions that help with the curation of data, the publication of research data, and the assignment of DOIs in one software seem to be rare. At GFZ Potsdam we built a modular software stack that is made of several free and open software solutions and we established 'GFZ Data Services'. 'GFZ Data Services' provides storage, a metadata editor for publication and a facility to moderate minted DOIs. All software solutions are connected through web APIs, which makes it possible to reuse and integrate established software. Core component of 'GFZ Data Services' is an eSciDoc [3] middleware that is used as central storage, and has been designed along the OAIS reference model for digital preservation. Thus, data are stored in self-contained packages that are made of binary file-based data and XML-based metadata. The eSciDoc infrastructure provides access control to data and it is able to handle half-open datasets, which is useful in embargo situations when a subset of the research data are released after an adequate period. The data exchange platform panMetaDocs [4] makes use of eSciDoc's REST API to upload file-based data into eSciDoc and uses a metadata editor [5] to annotate the files with metadata. The metadata editor has a user-friendly interface with nominal lists, extensive explanations, and an interactive mapping tool to provide assistance to scientists describing the data. It is possible to deposit metadata templates to fill certain fields with default values. The metadata editor generates metadata in the schemas ISO19139, NASA GCMD DIF, and DataCite and could be extended for other schemas. panMetaDocs is able to mint dataset DOIs through DOIDB, which is our component to moderate dataset DOIs issued through 'GFZ Data Services'. DOIDB accepts metadata in the schemas ISO19139, DIF, and DataCite. In addition, DOIDB provides an OAI-PMH interface to disseminate all deposited metadata to data portals. The presentation of datasets on DOI landing pages is done though XSLT stylesheet transformation of the XML-based metadata. The landing pages have been designed to meet needs of scientists. We are able to render the metadata to different layouts. Furthermore, additional information about datasets and publications is assembled into the webpage by querying public databases on the internet. The work presented here will focus on technical details of the software stack. [1] http://stats.datacite.org [2] http://www.dlib.org/dlib/january11/starr/01starr.html [3] http://www.escidoc.org [4] http://panmetadocs.sf.net [5] http://github.com/ulbricht

panMetaDocs and DataSync - providing a convenient way to share and publish research data

NASA Astrophysics Data System (ADS)

Ulbricht, D.; Klump, J. F.

2013-12-01

In recent years research institutions, geological surveys and funding organizations started to build infrastructures to facilitate the re-use of research data from previous work. At present, several intermeshed activities are coordinated to make data systems of the earth sciences interoperable and recorded data discoverable. Driven by governmental authorities, ISO19115/19139 emerged as metadata standards for discovery of data and services. Established metadata transport protocols like OAI-PMH and OGC-CSW are used to disseminate metadata to data portals. With the persistent identifiers like DOI and IGSN research data and corresponding physical samples can be given unambiguous names and thus become citable. In summary, these activities focus primarily on 'ready to give away'-data, already stored in an institutional repository and described with appropriate metadata. Many datasets are not 'born' in this state but are produced in small and federated research projects. To make access and reuse of these 'small data' easier, these data should be centrally stored and version controlled from the very beginning of activities. We developed DataSync [1] as supplemental application to the panMetaDocs [2] data exchange platform as a data management tool for small science projects. DataSync is a JAVA-application that runs on a local computer and synchronizes directory trees into an eSciDoc-repository [3] by creating eSciDoc-objects via eSciDocs' REST API. DataSync can be installed on multiple computers and is in this way able to synchronize files of a research team over the internet. XML Metadata can be added as separate files that are managed together with data files as versioned eSciDoc-objects. A project-customized instance of panMetaDocs is provided to show a web-based overview of the previously uploaded file collection and to allow further annotation with metadata inside the eSciDoc-repository. PanMetaDocs is a PHP based web application to assist the creation of metadata in any XML-based metadata schema. To reduce manual entries of metadata to a minimum and make use of contextual information in a project setting, metadata fields can be populated with static or dynamic content. Access rights can be defined to control visibility and access to stored objects. Notifications about recently updated datasets are available by RSS and e-mail and the entire inventory can be harvested via OAI-PMH. panMetaDocs is optimized to be harvested by panFMP [4]. panMetaDocs is able to mint dataset DOIs though DataCite and uses eSciDocs' REST API to transfer eSciDoc-objects from a non-public 'pending'-status to the published status 'released', which makes data and metadata of the published object available worldwide through the internet. The application scenario presented here shows the adoption of open source applications to data sharing and publication of data. An eSciDoc-repository is used as storage for data and metadata. DataSync serves as a file ingester and distributor, whereas panMetaDocs' main function is to annotate the dataset files with metadata to make them ready for publication and sharing with your own team, or with the scientific community.

Atmospheric Radiation Measurement's Data Management Facility captures metadata and uses visualization tools to assist in routine data management.

NASA Astrophysics Data System (ADS)

Keck, N. N.; Macduff, M.; Martin, T.

2017-12-01

The Atmospheric Radiation Measurement's (ARM) Data Management Facility (DMF) plays a critical support role in processing and curating data generated by the Department of Energy's ARM Program. Data are collected near real time from hundreds of observational instruments spread out all over the globe. Data are then ingested hourly to provide time series data in NetCDF (network Common Data Format) and includes standardized metadata. Based on automated processes and a variety of user reviews the data may need to be reprocessed. Final data sets are then stored and accessed by users through the ARM Archive. Over the course of 20 years, a suite of data visualization tools have been developed to facilitate the operational processes to manage and maintain the more than 18,000 real time events, that move 1.3 TB of data each day through the various stages of the DMF's data system. This poster will present the resources and methodology used to capture metadata and the tools that assist in routine data management and discoverability.

Specialist Bibliographic Databases

PubMed Central

2016-01-01

Specialist bibliographic databases offer essential online tools for researchers and authors who work on specific subjects and perform comprehensive and systematic syntheses of evidence. This article presents examples of the established specialist databases, which may be of interest to those engaged in multidisciplinary science communication. Access to most specialist databases is through subscription schemes and membership in professional associations. Several aggregators of information and database vendors, such as EBSCOhost and ProQuest, facilitate advanced searches supported by specialist keyword thesauri. Searches of items through specialist databases are complementary to those through multidisciplinary research platforms, such as PubMed, Web of Science, and Google Scholar. Familiarizing with the functional characteristics of biomedical and nonbiomedical bibliographic search tools is mandatory for researchers, authors, editors, and publishers. The database users are offered updates of the indexed journal lists, abstracts, author profiles, and links to other metadata. Editors and publishers may find particularly useful source selection criteria and apply for coverage of their peer-reviewed journals and grey literature sources. These criteria are aimed at accepting relevant sources with established editorial policies and quality controls. PMID:27134485

Specialist Bibliographic Databases.

PubMed

Gasparyan, Armen Yuri; Yessirkepov, Marlen; Voronov, Alexander A; Trukhachev, Vladimir I; Kostyukova, Elena I; Gerasimov, Alexey N; Kitas, George D

2016-05-01

Specialist bibliographic databases offer essential online tools for researchers and authors who work on specific subjects and perform comprehensive and systematic syntheses of evidence. This article presents examples of the established specialist databases, which may be of interest to those engaged in multidisciplinary science communication. Access to most specialist databases is through subscription schemes and membership in professional associations. Several aggregators of information and database vendors, such as EBSCOhost and ProQuest, facilitate advanced searches supported by specialist keyword thesauri. Searches of items through specialist databases are complementary to those through multidisciplinary research platforms, such as PubMed, Web of Science, and Google Scholar. Familiarizing with the functional characteristics of biomedical and nonbiomedical bibliographic search tools is mandatory for researchers, authors, editors, and publishers. The database users are offered updates of the indexed journal lists, abstracts, author profiles, and links to other metadata. Editors and publishers may find particularly useful source selection criteria and apply for coverage of their peer-reviewed journals and grey literature sources. These criteria are aimed at accepting relevant sources with established editorial policies and quality controls.

Representing Hydrologic Models as HydroShare Resources to Facilitate Model Sharing and Collaboration

NASA Astrophysics Data System (ADS)

Castronova, A. M.; Goodall, J. L.; Mbewe, P.

2013-12-01

The CUAHSI HydroShare project is a collaborative effort that aims to provide software for sharing data and models within the hydrologic science community. One of the early focuses of this work has been establishing metadata standards for describing models and model-related data as HydroShare resources. By leveraging this metadata definition, a prototype extension has been developed to create model resources that can be shared within the community using the HydroShare system. The extension uses a general model metadata definition to create resource objects, and was designed so that model-specific parsing routines can extract and populate metadata fields from model input and output files. The long term goal is to establish a library of supported models where, for each model, the system has the ability to extract key metadata fields automatically, thereby establishing standardized model metadata that will serve as the foundation for model sharing and collaboration within HydroShare. The Soil Water & Assessment Tool (SWAT) is used to demonstrate this concept through a case study application.

NASA Reverb: Standards-Driven Earth Science Data and Service Discovery

NASA Astrophysics Data System (ADS)

Cechini, M. F.; Mitchell, A.; Pilone, D.

2011-12-01

NASA's Earth Observing System Data and Information System (EOSDIS) is a core capability in NASA's Earth Science Data Systems Program. NASA's EOS ClearingHOuse (ECHO) is a metadata catalog for the EOSDIS, providing a centralized catalog of data products and registry of related data services. Working closely with the EOSDIS community, the ECHO team identified a need to develop the next generation EOS data and service discovery tool. This development effort relied on the following principles: + Metadata Driven User Interface - Users should be presented with data and service discovery capabilities based on dynamic processing of metadata describing the targeted data. + Integrated Data & Service Discovery - Users should be able to discovery data and associated data services that facilitate their research objectives. + Leverage Common Standards - Users should be able to discover and invoke services that utilize common interface standards. Metadata plays a vital role facilitating data discovery and access. As data providers enhance their metadata, more advanced search capabilities become available enriching a user's search experience. Maturing metadata formats such as ISO 19115 provide the necessary depth of metadata that facilitates advanced data discovery capabilities. Data discovery and access is not limited to simply the retrieval of data granules, but is growing into the more complex discovery of data services. These services include, but are not limited to, services facilitating additional data discovery, subsetting, reformatting, and re-projecting. The discovery and invocation of these data services is made significantly simpler through the use of consistent and interoperable standards. By utilizing an adopted standard, developing standard-specific adapters can be utilized to communicate with multiple services implementing a specific protocol. The emergence of metadata standards such as ISO 19119 plays a similarly important role in discovery as the 19115 standard. After a yearlong design, development, and testing process, the ECHO team successfully released "Reverb - The Next Generation Earth Science Discovery Tool." Reverb relies heavily on the information contained in dataset and granule metadata, such as ISO 19115, to provide a dynamic experience to users based on identified search facet values extracted from science metadata. Such an approach allows users to perform cross-dataset correlation and searches, discovering additional data that they may not previously have been aware of. In addition to data discovery, Reverb users may discover services associated with their data of interest. When services utilize supported standards and/or protocols, Reverb can facilitate the invocation of both synchronous and asynchronous data processing services. This greatly enhances a users ability to discover data of interest and accomplish their research goals. Extrapolating on the current movement towards interoperable standards and an increase in available services, data service invocation and chaining will become a natural part of data discovery. Reverb is one example of a discovery tool that provides a mechanism for transforming the earth science data discovery paradigm.

"CanCore": In Canada and around the World

ERIC Educational Resources Information Center

Friesen, Norm

2005-01-01

In this article, the author discusses "CanCore," a learning resource metadata initiative funded by Industry Canada and supported by Athabasca University, Alberta, and TeleUniversite du Quebec, and describes the increasing range of international uses of the "CanCore" metadata for the indexing of learning objects.…

PIMMS tools for capturing metadata about simulations

NASA Astrophysics Data System (ADS)

Pascoe, Charlotte; Devine, Gerard; Tourte, Gregory; Pascoe, Stephen; Lawrence, Bryan; Barjat, Hannah

2013-04-01

PIMMS (Portable Infrastructure for the Metafor Metadata System) provides a method for consistent and comprehensive documentation of modelling activities that enables the sharing of simulation data and model configuration information. The aim of PIMMS is to package the metadata infrastructure developed by Metafor for CMIP5 so that it can be used by climate modelling groups in UK Universities. PIMMS tools capture information about simulations from the design of experiments to the implementation of experiments via simulations that run models. PIMMS uses the Metafor methodology which consists of a Common Information Model (CIM), Controlled Vocabularies (CV) and software tools. PIMMS software tools provide for the creation and consumption of CIM content via a web services infrastructure and portal developed by the ES-DOC community. PIMMS metadata integrates with the ESGF data infrastructure via the mapping of vocabularies onto ESGF facets. There are three paradigms of PIMMS metadata collection: Model Intercomparision Projects (MIPs) where a standard set of questions is asked of all models which perform standard sets of experiments. Disciplinary level metadata collection where a standard set of questions is asked of all models but experiments are specified by users. Bespoke metadata creation where the users define questions about both models and experiments. Examples will be shown of how PIMMS has been configured to suit each of these three paradigms. In each case PIMMS allows users to provide additional metadata beyond that which is asked for in an initial deployment. The primary target for PIMMS is the UK climate modelling community where it is common practice to reuse model configurations from other researchers. This culture of collaboration exists in part because climate models are very complex with many variables that can be modified. Therefore it has become common practice to begin a series of experiments by using another climate model configuration as a starting point. Usually this other configuration is provided by a researcher in the same research group or by a previous collaborator with whom there is an existing scientific relationship. Some efforts have been made at the university department level to create documentation but there is a wide diversity in the scope and purpose of this information. The consistent and comprehensive documentation enabled by PIMMS will enable the wider sharing of climate model data and configuration information. The PIMMS methodology assumes an initial effort to document standard model configurations. Once these descriptions have been created users need only describe the specific way in which their model configuration is different from the standard. Thus the documentation burden on the user is specific to the experiment they are performing and fits easily into the workflow of doing their science. PIMMS metadata is independent of data and as such is ideally suited for documenting model development. PIMMS provides a framework for sharing information about failed model configurations for which data are not kept, the negative results that don't appear in scientific literature. PIMMS is a UK project funded by JISC, The University of Reading, The University of Bristol and STFC.

The center for expanded data annotation and retrieval

PubMed Central

Bean, Carol A; Cheung, Kei-Hoi; Dumontier, Michel; Durante, Kim A; Gevaert, Olivier; Gonzalez-Beltran, Alejandra; Khatri, Purvesh; Kleinstein, Steven H; O’Connor, Martin J; Pouliot, Yannick; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Wiser, Jeffrey A

2015-01-01

The Center for Expanded Data Annotation and Retrieval is studying the creation of comprehensive and expressive metadata for biomedical datasets to facilitate data discovery, data interpretation, and data reuse. We take advantage of emerging community-based standard templates for describing different kinds of biomedical datasets, and we investigate the use of computational techniques to help investigators to assemble templates and to fill in their values. We are creating a repository of metadata from which we plan to identify metadata patterns that will drive predictive data entry when filling in metadata templates. The metadata repository not only will capture annotations specified when experimental datasets are initially created, but also will incorporate links to the published literature, including secondary analyses and possible refinements or retractions of experimental interpretations. By working initially with the Human Immunology Project Consortium and the developers of the ImmPort data repository, we are developing and evaluating an end-to-end solution to the problems of metadata authoring and management that will generalize to other data-management environments. PMID:26112029

Metadata Sets for e-Government Resources: The Extended e-Government Metadata Schema (eGMS+)

NASA Astrophysics Data System (ADS)

Charalabidis, Yannis; Lampathaki, Fenareti; Askounis, Dimitris

In the dawn of the Semantic Web era, metadata appear as a key enabler that assists management of the e-Government resources related to the provision of personalized, efficient and proactive services oriented towards the real citizens’ needs. As different authorities typically use different terms to describe their resources and publish them in various e-Government Registries that may enhance the access to and delivery of governmental knowledge, but also need to communicate seamlessly at a national and pan-European level, the need for a unified e-Government metadata standard emerges. This paper presents the creation of an ontology-based extended metadata set for e-Government Resources that embraces services, documents, XML Schemas, code lists, public bodies and information systems. Such a metadata set formalizes the exchange of information between portals and registries and assists the service transformation and simplification efforts, while it can be further taken into consideration when applying Web 2.0 techniques in e-Government.

eScience for molecular-scale simulations and the eMinerals project.

PubMed

Salje, E K H; Artacho, E; Austen, K F; Bruin, R P; Calleja, M; Chappell, H F; Chiang, G-T; Dove, M T; Frame, I; Goodwin, A L; Kleese van Dam, K; Marmier, A; Parker, S C; Pruneda, J M; Todorov, I T; Trachenko, K; Tyer, R P; Walker, A M; White, T O H

2009-03-13

We review the work carried out within the eMinerals project to develop eScience solutions that facilitate a new generation of molecular-scale simulation work. Technological developments include integration of compute and data systems, developing of collaborative frameworks and new researcher-friendly tools for grid job submission, XML data representation, information delivery, metadata harvesting and metadata management. A number of diverse science applications will illustrate how these tools are being used for large parameter-sweep studies, an emerging type of study for which the integration of computing, data and collaboration is essential.

The Master Archive Collection Inventory (MACI)

NASA Astrophysics Data System (ADS)

Lief, C. J.; Arnfield, J.; Sprain, M.

2014-12-01

The Master Archive Collection Inventory (MACI) project at the NOAA National Climatic Data Center (NCDC) is an effort to re-inventory all digital holdings to streamline data set and product titles and update documentation to discovery level ISO 199115-2. Subject Matter Experts (SME) are being identified for each of the holdings and will be responsible for creating and maintaining metadata records. New user-friendly tools are available for the SMEs to easily create and update this documentation. Updated metadata will be available for retrieval by other aggregators and discovery tools, increasing the usability of NCDC data and products.

The New Online Metadata Editor for Generating Structured Metadata

NASA Astrophysics Data System (ADS)

Devarakonda, R.; Shrestha, B.; Palanisamy, G.; Hook, L.; Killeffer, T.; Boden, T.; Cook, R. B.; Zolly, L.; Hutchison, V.; Frame, M. T.; Cialella, A. T.; Lazer, K.

2014-12-01

Nobody is better suited to "describe" data than the scientist who created it. This "description" about a data is called Metadata. In general terms, Metadata represents the who, what, when, where, why and how of the dataset. eXtensible Markup Language (XML) is the preferred output format for metadata, as it makes it portable and, more importantly, suitable for system discoverability. The newly developed ORNL Metadata Editor (OME) is a Web-based tool that allows users to create and maintain XML files containing key information, or metadata, about the research. Metadata include information about the specific projects, parameters, time periods, and locations associated with the data. Such information helps put the research findings in context. In addition, the metadata produced using OME will allow other researchers to find these data via Metadata clearinghouses like Mercury [1] [2]. Researchers simply use the ORNL Metadata Editor to enter relevant metadata into a Web-based form. How is OME helping Big Data Centers like ORNL DAAC? The ORNL DAAC is one of NASA's Earth Observing System Data and Information System (EOSDIS) data centers managed by the ESDIS Project. The ORNL DAAC archives data produced by NASA's Terrestrial Ecology Program. The DAAC provides data and information relevant to biogeochemical dynamics, ecological data, and environmental processes, critical for understanding the dynamics relating to the biological components of the Earth's environment. Typically data produced, archived and analyzed is at a scale of multiple petabytes, which makes the discoverability of the data very challenging. Without proper metadata associated with the data, it is difficult to find the data you are looking for and equally difficult to use and understand the data. OME will allow data centers like the ORNL DAAC to produce meaningful, high quality, standards-based, descriptive information about their data products in-turn helping with the data discoverability and interoperability.References:[1] Devarakonda, Ranjeet, et al. "Mercury: reusable metadata management, data discovery and access system." Earth Science Informatics 3.1-2 (2010): 87-94. [2] Wilson, Bruce E., et al. "Mercury Toolset for Spatiotemporal Metadata." NASA Technical Reports Server (NTRS) (2010).

iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources

PubMed Central

Dinov, Ivo D.; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H. V.; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D. Stott; Toga, Arthur W.

2008-01-01

The advancement of the computational biology field hinges on progress in three fundamental directions – the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources–data, software tools and web-services. The iTools design, implementation and resource meta - data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu. PMID:18509477

GCE Data Toolbox for MATLAB - a software framework for automating environmental data processing, quality control and documentation

NASA Astrophysics Data System (ADS)

Sheldon, W.; Chamblee, J.; Cary, R. H.

2013-12-01

Environmental scientists are under increasing pressure from funding agencies and journal publishers to release quality-controlled data in a timely manner, as well as to produce comprehensive metadata for submitting data to long-term archives (e.g. DataONE, Dryad and BCO-DMO). At the same time, the volume of digital data that researchers collect and manage is increasing rapidly due to advances in high frequency electronic data collection from flux towers, instrumented moorings and sensor networks. However, few pre-built software tools are available to meet these data management needs, and those tools that do exist typically focus on part of the data management lifecycle or one class of data. The GCE Data Toolbox has proven to be both a generalized and effective software solution for environmental data management in the Long Term Ecological Research Network (LTER). This open source MATLAB software library, developed by the Georgia Coastal Ecosystems LTER program, integrates metadata capture, creation and management with data processing, quality control and analysis to support the entire data lifecycle. Raw data can be imported directly from common data logger formats (e.g. SeaBird, Campbell Scientific, YSI, Hobo), as well as delimited text files, MATLAB files and relational database queries. Basic metadata are derived from the data source itself (e.g. parsed from file headers) and by value inspection, and then augmented using editable metadata templates containing boilerplate documentation, attribute descriptors, code definitions and quality control rules. Data and metadata content, quality control rules and qualifier flags are then managed together in a robust data structure that supports database functionality and ensures data validity throughout processing. A growing suite of metadata-aware editing, quality control, analysis and synthesis tools are provided with the software to support managing data using graphical forms and command-line functions, as well as developing automated workflows for unattended processing. Finalized data and structured metadata can be exported in a wide variety of text and MATLAB formats or uploaded to a relational database for long-term archiving and distribution. The GCE Data Toolbox can be used as a complete, light-weight solution for environmental data and metadata management, but it can also be used in conjunction with other cyber infrastructure to provide a more comprehensive solution. For example, newly acquired data can be retrieved from a Data Turbine or Campbell LoggerNet Database server for quality control and processing, then transformed to CUAHSI Observations Data Model format and uploaded to a HydroServer for distribution through the CUAHSI Hydrologic Information System. The GCE Data Toolbox can also be leveraged in analytical workflows developed using Kepler or other systems that support MATLAB integration or tool chaining. This software can therefore be leveraged in many ways to help researchers manage, analyze and distribute the data they collect.

Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO).

PubMed

Panahiazar, Maryam; Dumontier, Michel; Gevaert, Olivier

2017-08-01

A crucial and limiting factor in data reuse is the lack of accurate, structured, and complete descriptions of data, known as metadata. Towards improving the quantity and quality of metadata, we propose a novel metadata prediction framework to learn associations from existing metadata that can be used to predict metadata values. We evaluate our framework in the context of experimental metadata from the Gene Expression Omnibus (GEO). We applied four rule mining algorithms to the most common structured metadata elements (sample type, molecular type, platform, label type and organism) from over 1.3million GEO records. We examined the quality of well supported rules from each algorithm and visualized the dependencies among metadata elements. Finally, we evaluated the performance of the algorithms in terms of accuracy, precision, recall, and F-measure. We found that PART is the best algorithm outperforming Apriori, Predictive Apriori, and Decision Table. All algorithms perform significantly better in predicting class values than the majority vote classifier. We found that the performance of the algorithms is related to the dimensionality of the GEO elements. The average performance of all algorithm increases due of the decreasing of dimensionality of the unique values of these elements (2697 platforms, 537 organisms, 454 labels, 9 molecules, and 5 types). Our work suggests that experimental metadata such as present in GEO can be accurately predicted using rule mining algorithms. Our work has implications for both prospective and retrospective augmentation of metadata quality, which are geared towards making data easier to find and reuse. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

DichroMatch at the protein circular dichroism data bank (DM@PCDDB): A web-based tool for identifying protein nearest neighbors using circular dichroism spectroscopy.

PubMed

Whitmore, Lee; Mavridis, Lazaros; Wallace, B A; Janes, Robert W

2018-01-01

Circular dichroism spectroscopy is a well-used, but simple method in structural biology for providing information on the secondary structure and folds of proteins. DichroMatch (DM@PCDDB) is an online tool that is newly available in the Protein Circular Dichroism Data Bank (PCDDB), which takes advantage of the wealth of spectral and metadata deposited therein, to enable identification of spectral nearest neighbors of a query protein based on four different methods of spectral matching. DM@PCDDB can potentially provide novel information about structural relationships between proteins and can be used in comparison studies of protein homologs and orthologs. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Dataworks for GNSS: Software for Supporting Data Sharing and Federation of Geodetic Networks

NASA Astrophysics Data System (ADS)

Boler, F. M.; Meertens, C. M.; Miller, M. M.; Wier, S.; Rost, M.; Matykiewicz, J.

2015-12-01

Continuously-operating Global Navigation Satellite System (GNSS) networks are increasingly being installed globally for a wide variety of science and societal applications. GNSS enables Earth science research in areas including tectonic plate interactions, crustal deformation in response to loading by tectonics, magmatism, water and ice, and the dynamics of water - and thereby energy transfer - in the atmosphere at regional scale. The many individual scientists and organizations that set up GNSS stations globally are often open to sharing data, but lack the resources or expertise to deploy systems and software to manage and curate data and metadata and provide user tools that would support data sharing. UNAVCO previously gained experience in facilitating data sharing through the NASA-supported development of the Geodesy Seamless Archive Centers (GSAC) open source software. GSAC provides web interfaces and simple web services for data and metadata discovery and access, supports federation of multiple data centers, and simplifies transfer of data and metadata to long-term archives. The NSF supported the dissemination of GSAC to multiple European data centers forming the European Plate Observing System. To expand upon GSAC to provide end-to-end, instrument-to-distribution capability, UNAVCO developed Dataworks for GNSS with NSF funding to the COCONet project, and deployed this software on systems that are now operating as Regional GNSS Data Centers as part of the NSF-funded TLALOCNet and COCONet projects. Dataworks consists of software modules written in Python and Java for data acquisition, management and sharing. There are modules for GNSS receiver control and data download, a database schema for metadata, tools for metadata handling, ingest software to manage file metadata, data file management scripts, GSAC, scripts for mirroring station data and metadata from partner GSACs, and extensive software and operator documentation. UNAVCO plans to provide a cloud VM image of Dataworks that would allow standing up a Dataworks-enabled GNSS data center without requiring upfront investment in server hardware. By enabling data creators to organize their data and metadata for sharing, Dataworks helps scientists expand their data curation awareness and responsibility, and enhances data access for all.

Next-Generation Search Engines for Information Retrieval

DOE Office of Scientific and Technical Information (OSTI.GOV)

Devarakonda, Ranjeet; Hook, Leslie A; Palanisamy, Giri

In the recent years, there have been significant advancements in the areas of scientific data management and retrieval techniques, particularly in terms of standards and protocols for archiving data and metadata. Scientific data is rich, and spread across different places. In order to integrate these pieces together, a data archive and associated metadata should be generated. Data should be stored in a format that can be retrievable and more importantly it should be in a format that will continue to be accessible as technology changes, such as XML. While general-purpose search engines (such as Google or Bing) are useful formore » finding many things on the Internet, they are often of limited usefulness for locating Earth Science data relevant (for example) to a specific spatiotemporal extent. By contrast, tools that search repositories of structured metadata can locate relevant datasets with fairly high precision, but the search is limited to that particular repository. Federated searches (such as Z39.50) have been used, but can be slow and the comprehensiveness can be limited by downtime in any search partner. An alternative approach to improve comprehensiveness is for a repository to harvest metadata from other repositories, possibly with limits based on subject matter or access permissions. Searches through harvested metadata can be extremely responsive, and the search tool can be customized with semantic augmentation appropriate to the community of practice being served. One such system, Mercury, a metadata harvesting, data discovery, and access system, built for researchers to search to, share and obtain spatiotemporal data used across a range of climate and ecological sciences. Mercury is open-source toolset, backend built on Java and search capability is supported by the some popular open source search libraries such as SOLR and LUCENE. Mercury harvests the structured metadata and key data from several data providing servers around the world and builds a centralized index. The harvested files are indexed against SOLR search API consistently, so that it can render search capabilities such as simple, fielded, spatial and temporal searches across a span of projects ranging from land, atmosphere, and ocean ecology. Mercury also provides data sharing capabilities using Open Archive Initiatives Protocol for Metadata Handling (OAI-PMH). In this paper we will discuss about the best practices for archiving data and metadata, new searching techniques, efficient ways of data retrieval and information display.« less

A standard for measuring metadata quality in spectral libraries

NASA Astrophysics Data System (ADS)

Rasaiah, B.; Jones, S. D.; Bellman, C.

2013-12-01

A standard for measuring metadata quality in spectral libraries Barbara Rasaiah, Simon Jones, Chris Bellman RMIT University Melbourne, Australia barbara.rasaiah@rmit.edu.au, simon.jones@rmit.edu.au, chris.bellman@rmit.edu.au ABSTRACT There is an urgent need within the international remote sensing community to establish a metadata standard for field spectroscopy that ensures high quality, interoperable metadata sets that can be archived and shared efficiently within Earth observation data sharing systems. Metadata are an important component in the cataloguing and analysis of in situ spectroscopy datasets because of their central role in identifying and quantifying the quality and reliability of spectral data and the products derived from them. This paper presents approaches to measuring metadata completeness and quality in spectral libraries to determine reliability, interoperability, and re-useability of a dataset. Explored are quality parameters that meet the unique requirements of in situ spectroscopy datasets, across many campaigns. Examined are the challenges presented by ensuring that data creators, owners, and data users ensure a high level of data integrity throughout the lifecycle of a dataset. Issues such as field measurement methods, instrument calibration, and data representativeness are investigated. The proposed metadata standard incorporates expert recommendations that include metadata protocols critical to all campaigns, and those that are restricted to campaigns for specific target measurements. The implication of semantics and syntax for a robust and flexible metadata standard are also considered. Approaches towards an operational and logistically viable implementation of a quality standard are discussed. This paper also proposes a way forward for adapting and enhancing current geospatial metadata standards to the unique requirements of field spectroscopy metadata quality. [0430] BIOGEOSCIENCES / Computational methods and data processing [0480] BIOGEOSCIENCES / Remote sensing [1904] INFORMATICS / Community standards [1912] INFORMATICS / Data management, preservation, rescue [1926] INFORMATICS / Geospatial [1930] INFORMATICS / Data and information governance [1946] INFORMATICS / Metadata [1952] INFORMATICS / Modeling [1976] INFORMATICS / Software tools and services [9810] GENERAL OR MISCELLANEOUS / New fields

The Role of Evaluative Metadata in an Online Teacher Resource Exchange

ERIC Educational Resources Information Center

Abramovich, Samuel; Schunn, Christian D.; Correnti, Richard J.

2013-01-01

A large-scale online teacher resource exchange is studied to examine the ways in which metadata influence teachers' selection of resources. A hierarchical linear modeling approach was used to tease apart the simultaneous effects of resource features and author features. From a decision heuristics theoretical perspective, teachers appear to…

BioSharing: curated and crowd-sourced metadata standards, databases and data policies in the life sciences.

PubMed

McQuilton, Peter; Gonzalez-Beltran, Alejandra; Rocca-Serra, Philippe; Thurston, Milo; Lister, Allyson; Maguire, Eamonn; Sansone, Susanna-Assunta

2016-01-01

BioSharing (http://www.biosharing.org) is a manually curated, searchable portal of three linked registries. These resources cover standards (terminologies, formats and models, and reporting guidelines), databases, and data policies in the life sciences, broadly encompassing the biological, environmental and biomedical sciences. Launched in 2011 and built by the same core team as the successful MIBBI portal, BioSharing harnesses community curation to collate and cross-reference resources across the life sciences from around the world. BioSharing makes these resources findable and accessible (the core of the FAIR principle). Every record is designed to be interlinked, providing a detailed description not only on the resource itself, but also on its relations with other life science infrastructures. Serving a variety of stakeholders, BioSharing cultivates a growing community, to which it offers diverse benefits. It is a resource for funding bodies and journal publishers to navigate the metadata landscape of the biological sciences; an educational resource for librarians and information advisors; a publicising platform for standard and database developers/curators; and a research tool for bench and computer scientists to plan their work. BioSharing is working with an increasing number of journals and other registries, for example linking standards and databases to training material and tools. Driven by an international Advisory Board, the BioSharing user-base has grown by over 40% (by unique IP address), in the last year thanks to successful engagement with researchers, publishers, librarians, developers and other stakeholders via several routes, including a joint RDA/Force11 working group and a collaboration with the International Society for Biocuration. In this article, we describe BioSharing, with a particular focus on community-led curation.Database URL: https://www.biosharing.org. © The Author(s) 2016. Published by Oxford University Press.

High-performance metadata indexing and search in petascale data storage systems

NASA Astrophysics Data System (ADS)

Leung, A. W.; Shao, M.; Bisson, T.; Pasupathy, S.; Miller, E. L.

2008-07-01

Large-scale storage systems used for scientific applications can store petabytes of data and billions of files, making the organization and management of data in these systems a difficult, time-consuming task. The ability to search file metadata in a storage system can address this problem by allowing scientists to quickly navigate experiment data and code while allowing storage administrators to gather the information they need to properly manage the system. In this paper, we present Spyglass, a file metadata search system that achieves scalability by exploiting storage system properties, providing the scalability that existing file metadata search tools lack. In doing so, Spyglass can achieve search performance up to several thousand times faster than existing database solutions. We show that Spyglass enables important functionality that can aid data management for scientists and storage administrators.

Utilizing Linked Open Data Sources for Automatic Generation of Semantic Metadata

NASA Astrophysics Data System (ADS)

Nummiaho, Antti; Vainikainen, Sari; Melin, Magnus

In this paper we present an application that can be used to automatically generate semantic metadata for tags given as simple keywords. The application that we have implemented in Java programming language creates the semantic metadata by linking the tags to concepts in different semantic knowledge bases (CrunchBase, DBpedia, Freebase, KOKO, Opencyc, Umbel and/or WordNet). The steps that our application takes in doing so include detecting possible languages, finding spelling suggestions and finding meanings from amongst the proper nouns and common nouns separately. Currently, our application supports English, Finnish and Swedish words, but other languages could be included easily if the required lexical tools (spellcheckers, etc.) are available. The created semantic metadata can be of great use in, e.g., finding and combining similar contents, creating recommendations and targeting advertisements.

Enriching the trustworthiness of health-related web pages.

PubMed

Gaudinat, Arnaud; Cruchet, Sarah; Boyer, Celia; Chrawdhry, Pravir

2011-06-01

We present an experimental mechanism for enriching web content with quality metadata. This mechanism is based on a simple and well-known initiative in the field of the health-related web, the HONcode. The Resource Description Framework (RDF) format and the Dublin Core Metadata Element Set were used to formalize these metadata. The model of trust proposed is based on a quality model for health-related web pages that has been tested in practice over a period of thirteen years. Our model has been explored in the context of a project to develop a research tool that automatically detects the occurrence of quality criteria in health-related web pages.

Information Discovery and Retrieval Tools

DTIC Science & Technology

2004-12-01

information. This session will focus on the various Internet search engines , directories, and how to improve the user experience through the use of...such techniques as metadata, meta- search engines , subject specific search tools, and other developing technologies.

Information Discovery and Retrieval Tools

DTIC Science & Technology

2003-04-01

information. This session will focus on the various Internet search engines , directories, and how to improve the user experience through the use of...such techniques as metadata, meta- search engines , subject specific search tools, and other developing technologies.

Development of an open metadata schema for prospective clinical research (openPCR) in China.

PubMed

Xu, W; Guan, Z; Sun, J; Wang, Z; Geng, Y

2014-01-01

In China, deployment of electronic data capture (EDC) and clinical data management system (CDMS) for clinical research (CR) is in its very early stage, and about 90% of clinical studies collected and submitted clinical data manually. This work aims to build an open metadata schema for Prospective Clinical Research (openPCR) in China based on openEHR archetypes, in order to help Chinese researchers easily create specific data entry templates for registration, study design and clinical data collection. Singapore Framework for Dublin Core Application Profiles (DCAP) is used to develop openPCR and four steps such as defining the core functional requirements and deducing the core metadata items, developing archetype models, defining metadata terms and creating archetype records, and finally developing implementation syntax are followed. The core functional requirements are divided into three categories: requirements for research registration, requirements for trial design, and requirements for case report form (CRF). 74 metadata items are identified and their Chinese authority names are created. The minimum metadata set of openPCR includes 3 documents, 6 sections, 26 top level data groups, 32 lower data groups and 74 data elements. The top level container in openPCR is composed of public document, internal document and clinical document archetypes. A hierarchical structure of openPCR is established according to Data Structure of Electronic Health Record Architecture and Data Standard of China (Chinese EHR Standard). Metadata attributes are grouped into six parts: identification, definition, representation, relation, usage guides, and administration. OpenPCR is an open metadata schema based on research registration standards, standards of the Clinical Data Interchange Standards Consortium (CDISC) and Chinese healthcare related standards, and is to be publicly available throughout China. It considers future integration of EHR and CR by adopting data structure and data terms in Chinese EHR Standard. Archetypes in openPCR are modularity models and can be separated, recombined, and reused. The authors recommend that the method to develop openPCR can be referenced by other countries when designing metadata schema of clinical research. In the next steps, openPCR should be used in a number of CR projects to test its applicability and to continuously improve its coverage. Besides, metadata schema for research protocol can be developed to structurize and standardize protocol, and syntactical interoperability of openPCR with other related standards can be considered.

The CMIP5 Model Documentation Questionnaire: Development of a Metadata Retrieval System for the METAFOR Common Information Model

NASA Astrophysics Data System (ADS)

Pascoe, Charlotte; Lawrence, Bryan; Moine, Marie-Pierre; Ford, Rupert; Devine, Gerry

2010-05-01

The EU METAFOR Project (http://metaforclimate.eu) has created a web-based model documentation questionnaire to collect metadata from the modelling groups that are running simulations in support of the Coupled Model Intercomparison Project - 5 (CMIP5). The CMIP5 model documentation questionnaire will retrieve information about the details of the models used, how the simulations were carried out, how the simulations conformed to the CMIP5 experiment requirements and details of the hardware used to perform the simulations. The metadata collected by the CMIP5 questionnaire will allow CMIP5 data to be compared in a scientifically meaningful way. This paper describes the life-cycle of the CMIP5 questionnaire development which starts with relatively unstructured input from domain specialists and ends with formal XML documents that comply with the METAFOR Common Information Model (CIM). Each development step is associated with a specific tool. (1) Mind maps are used to capture information requirements from domain experts and build a controlled vocabulary, (2) a python parser processes the XML files generated by the mind maps, (3) Django (python) is used to generate the dynamic structure and content of the web based questionnaire from processed xml and the METAFOR CIM, (4) Python parsers ensure that information entered into the CMIP5 questionnaire is output as CIM compliant xml, (5) CIM compliant output allows automatic information capture tools to harvest questionnaire content into databases such as the Earth System Grid (ESG) metadata catalogue. This paper will focus on how Django (python) and XML input files are used to generate the structure and content of the CMIP5 questionnaire. It will also address how the choice of development tools listed above provided a framework that enabled working scientists (who we would never ordinarily get to interact with UML and XML) to be part the iterative development process and ensure that the CMIP5 model documentation questionnaire reflects what scientists want to know about the models. Keywords: metadata, CMIP5, automatic information capture, tool development

OntoCheck: verifying ontology naming conventions and metadata completeness in Protégé 4.

PubMed

Schober, Daniel; Tudose, Ilinca; Svatek, Vojtech; Boeker, Martin

2012-09-21

Although policy providers have outlined minimal metadata guidelines and naming conventions, ontologies of today still display inter- and intra-ontology heterogeneities in class labelling schemes and metadata completeness. This fact is at least partially due to missing or inappropriate tools. Software support can ease this situation and contribute to overall ontology consistency and quality by helping to enforce such conventions. We provide a plugin for the Protégé Ontology editor to allow for easy checks on compliance towards ontology naming conventions and metadata completeness, as well as curation in case of found violations. In a requirement analysis, derived from a prior standardization approach carried out within the OBO Foundry, we investigate the needed capabilities for software tools to check, curate and maintain class naming conventions. A Protégé tab plugin was implemented accordingly using the Protégé 4.1 libraries. The plugin was tested on six different ontologies. Based on these test results, the plugin could be refined, also by the integration of new functionalities. The new Protégé plugin, OntoCheck, allows for ontology tests to be carried out on OWL ontologies. In particular the OntoCheck plugin helps to clean up an ontology with regard to lexical heterogeneity, i.e. enforcing naming conventions and metadata completeness, meeting most of the requirements outlined for such a tool. Found test violations can be corrected to foster consistency in entity naming and meta-annotation within an artefact. Once specified, check constraints like name patterns can be stored and exchanged for later re-use. Here we describe a first version of the software, illustrate its capabilities and use within running ontology development efforts and briefly outline improvements resulting from its application. Further, we discuss OntoChecks capabilities in the context of related tools and highlight potential future expansions. The OntoCheck plugin facilitates labelling error detection and curation, contributing to lexical quality assurance in OWL ontologies. Ultimately, we hope this Protégé extension will ease ontology alignments as well as lexical post-processing of annotated data and hence can increase overall secondary data usage by humans and computers.

Quality Metadata Management for Geospatial Scientific Workflows: from Retrieving to Assessing with Online Tools

NASA Astrophysics Data System (ADS)

Leibovici, D. G.; Pourabdollah, A.; Jackson, M.

2011-12-01

Experts and decision-makers use or develop models to monitor global and local changes of the environment. Their activities require the combination of data and processing services in a flow of operations and spatial data computations: a geospatial scientific workflow. The seamless ability to generate, re-use and modify a geospatial scientific workflow is an important requirement but the quality of outcomes is equally much important [1]. Metadata information attached to the data and processes, and particularly their quality, is essential to assess the reliability of the scientific model that represents a workflow [2]. Managing tools, dealing with qualitative and quantitative metadata measures of the quality associated with a workflow, are, therefore, required for the modellers. To ensure interoperability, ISO and OGC standards [3] are to be adopted, allowing for example one to define metadata profiles and to retrieve them via web service interfaces. However these standards need a few extensions when looking at workflows, particularly in the context of geoprocesses metadata. We propose to fill this gap (i) at first through the provision of a metadata profile for the quality of processes, and (ii) through providing a framework, based on XPDL [4], to manage the quality information. Web Processing Services are used to implement a range of metadata analyses on the workflow in order to evaluate and present quality information at different levels of the workflow. This generates the metadata quality, stored in the XPDL file. The focus is (a) on the visual representations of the quality, summarizing the retrieved quality information either from the standardized metadata profiles of the components or from non-standard quality information e.g., Web 2.0 information, and (b) on the estimated qualities of the outputs derived from meta-propagation of uncertainties (a principle that we have introduced [5]). An a priori validation of the future decision-making supported by the outputs of the workflow once run, is then provided using the meta-propagated qualities, obtained without running the workflow [6], together with the visualization pointing out the need to improve the workflow with better data or better processes on the workflow graph itself. [1] Leibovici, DG, Hobona, G Stock, K Jackson, M (2009) Qualifying geospatial workfow models for adaptive controlled validity and accuracy. In: IEEE 17th GeoInformatics, 1-5 [2] Leibovici, DG, Pourabdollah, A (2010a) Workflow Uncertainty using a Metamodel Framework and Metadata for Data and Processes. OGC TC/PC Meetings, September 2010, Toulouse, France [3] OGC (2011) www.opengeospatial.org [4] XPDL (2008) Workflow Process Definition Interface - XML Process Definition Language.Workflow Management Coalition, Document WfMC-TC-1025, 2008 [5] Leibovici, DG Pourabdollah, A Jackson, M (2011) Meta-propagation of Uncertainties for Scientific Workflow Management in Interoperable Spatial Data Infrastructures. In: Proceedings of the European Geosciences Union (EGU2011), April 2011, Austria [6] Pourabdollah, A Leibovici, DG Jackson, M (2011) MetaPunT: an Open Source tool for Meta-Propagation of uncerTainties in Geospatial Processing. In: Proceedings of OSGIS2011, June 2011, Nottingham, UK

Handling Metadata in a Neurophysiology Laboratory

PubMed Central

Zehl, Lyuba; Jaillet, Florent; Stoewer, Adrian; Grewe, Jan; Sobolev, Andrey; Wachtler, Thomas; Brochier, Thomas G.; Riehle, Alexa; Denker, Michael; Grün, Sonja

2016-01-01

To date, non-reproducibility of neurophysiological research is a matter of intense discussion in the scientific community. A crucial component to enhance reproducibility is to comprehensively collect and store metadata, that is, all information about the experiment, the data, and the applied preprocessing steps on the data, such that they can be accessed and shared in a consistent and simple manner. However, the complexity of experiments, the highly specialized analysis workflows and a lack of knowledge on how to make use of supporting software tools often overburden researchers to perform such a detailed documentation. For this reason, the collected metadata are often incomplete, incomprehensible for outsiders or ambiguous. Based on our research experience in dealing with diverse datasets, we here provide conceptual and technical guidance to overcome the challenges associated with the collection, organization, and storage of metadata in a neurophysiology laboratory. Through the concrete example of managing the metadata of a complex experiment that yields multi-channel recordings from monkeys performing a behavioral motor task, we practically demonstrate the implementation of these approaches and solutions with the intention that they may be generalized to other projects. Moreover, we detail five use cases that demonstrate the resulting benefits of constructing a well-organized metadata collection when processing or analyzing the recorded data, in particular when these are shared between laboratories in a modern scientific collaboration. Finally, we suggest an adaptable workflow to accumulate, structure and store metadata from different sources using, by way of example, the odML metadata framework. PMID:27486397

Handling Metadata in a Neurophysiology Laboratory.

PubMed

Zehl, Lyuba; Jaillet, Florent; Stoewer, Adrian; Grewe, Jan; Sobolev, Andrey; Wachtler, Thomas; Brochier, Thomas G; Riehle, Alexa; Denker, Michael; Grün, Sonja

2016-01-01

To date, non-reproducibility of neurophysiological research is a matter of intense discussion in the scientific community. A crucial component to enhance reproducibility is to comprehensively collect and store metadata, that is, all information about the experiment, the data, and the applied preprocessing steps on the data, such that they can be accessed and shared in a consistent and simple manner. However, the complexity of experiments, the highly specialized analysis workflows and a lack of knowledge on how to make use of supporting software tools often overburden researchers to perform such a detailed documentation. For this reason, the collected metadata are often incomplete, incomprehensible for outsiders or ambiguous. Based on our research experience in dealing with diverse datasets, we here provide conceptual and technical guidance to overcome the challenges associated with the collection, organization, and storage of metadata in a neurophysiology laboratory. Through the concrete example of managing the metadata of a complex experiment that yields multi-channel recordings from monkeys performing a behavioral motor task, we practically demonstrate the implementation of these approaches and solutions with the intention that they may be generalized to other projects. Moreover, we detail five use cases that demonstrate the resulting benefits of constructing a well-organized metadata collection when processing or analyzing the recorded data, in particular when these are shared between laboratories in a modern scientific collaboration. Finally, we suggest an adaptable workflow to accumulate, structure and store metadata from different sources using, by way of example, the odML metadata framework.

Data Management Rubric for Video Data in Organismal Biology.

PubMed

Brainerd, Elizabeth L; Blob, Richard W; Hedrick, Tyson L; Creamer, Andrew T; Müller, Ulrike K

2017-07-01

Standards-based data management facilitates data preservation, discoverability, and access for effective data reuse within research groups and across communities of researchers. Data sharing requires community consensus on standards for data management, such as storage and formats for digital data preservation, metadata (i.e., contextual data about the data) that should be recorded and stored, and data access. Video imaging is a valuable tool for measuring time-varying phenotypes in organismal biology, with particular application for research in functional morphology, comparative biomechanics, and animal behavior. The raw data are the videos, but videos alone are not sufficient for scientific analysis. Nearly endless videos of animals can be found on YouTube and elsewhere on the web, but these videos have little value for scientific analysis because essential metadata such as true frame rate, spatial calibration, genus and species, weight, age, etc. of organisms, are generally unknown. We have embarked on a project to build community consensus on video data management and metadata standards for organismal biology research. We collected input from colleagues at early stages, organized an open workshop, "Establishing Standards for Video Data Management," at the Society for Integrative and Comparative Biology meeting in January 2017, and then collected two more rounds of input on revised versions of the standards. The result we present here is a rubric consisting of nine standards for video data management, with three levels within each standard: good, better, and best practices. The nine standards are: (1) data storage; (2) video file formats; (3) metadata linkage; (4) video data and metadata access; (5) contact information and acceptable use; (6) camera settings; (7) organism(s); (8) recording conditions; and (9) subject matter/topic. The first four standards address data preservation and interoperability for sharing, whereas standards 5-9 establish minimum metadata standards for organismal biology video, and suggest additional metadata that may be useful for some studies. This rubric was developed with substantial input from researchers and students, but still should be viewed as a living document that should be further refined and updated as technology and research practices change. The audience for these standards includes researchers, journals, and granting agencies, and also the developers and curators of databases that may contribute to video data sharing efforts. We offer this project as an example of building community consensus for data management, preservation, and sharing standards, which may be useful for future efforts by the organismal biology research community. © The Author 2017. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology.

MPEG-7-based description infrastructure for an audiovisual content analysis and retrieval system

NASA Astrophysics Data System (ADS)

Bailer, Werner; Schallauer, Peter; Hausenblas, Michael; Thallinger, Georg

2005-01-01

We present a case study of establishing a description infrastructure for an audiovisual content-analysis and retrieval system. The description infrastructure consists of an internal metadata model and access tool for using it. Based on an analysis of requirements, we have selected, out of a set of candidates, MPEG-7 as the basis of our metadata model. The openness and generality of MPEG-7 allow using it in broad range of applications, but increase complexity and hinder interoperability. Profiling has been proposed as a solution, with the focus on selecting and constraining description tools. Semantic constraints are currently only described in textual form. Conformance in terms of semantics can thus not be evaluated automatically and mappings between different profiles can only be defined manually. As a solution, we propose an approach to formalize the semantic constraints of an MPEG-7 profile using a formal vocabulary expressed in OWL, which allows automated processing of semantic constraints. We have defined the Detailed Audiovisual Profile as the profile to be used in our metadata model and we show how some of the semantic constraints of this profile can be formulated using ontologies. To work practically with the metadata model, we have implemented a MPEG-7 library and a client/server document access infrastructure.

A Meta-Relational Approach for the Definition and Management of Hybrid Learning Objects

ERIC Educational Resources Information Center

Navarro, Antonio; Fernandez-Pampillon, Ana Ma.; Fernandez-Chamizo, Carmen; Fernandez-Valmayor, Alfredo

2013-01-01

Electronic learning objects (LOs) are commonly conceived of as digital units of information used for teaching and learning. To facilitate their classification for pedagogical planning and retrieval purposes, LOs are complemented with metadata (e.g., the author). These metadata are usually restricted by a set of predetermined tags to which the…

PDS4: Harnessing the Power of Generate and Apache Velocity

NASA Astrophysics Data System (ADS)

Padams, J.; Cayanan, M.; Hardman, S.

2018-04-01

The PDS4 Generate Tool is a Java-based command-line tool developed by the Cartography and Imaging Sciences Nodes (PDSIMG) for generating PDS4 XML labels, from Apache Velocity templates and input metadata.

Finding Atmospheric Composition (AC) Metadata

NASA Technical Reports Server (NTRS)

Strub, Richard F..; Falke, Stefan; Fiakowski, Ed; Kempler, Steve; Lynnes, Chris; Goussev, Oleg

2015-01-01

The Atmospheric Composition Portal (ACP) is an aggregator and curator of information related to remotely sensed atmospheric composition data and analysis. It uses existing tools and technologies and, where needed, enhances those capabilities to provide interoperable access, tools, and contextual guidance for scientists and value-adding organizations using remotely sensed atmospheric composition data. The initial focus is on Essential Climate Variables identified by the Global Climate Observing System CH4, CO, CO2, NO2, O3, SO2 and aerosols. This poster addresses our efforts in building the ACP Data Table, an interface to help discover and understand remotely sensed data that are related to atmospheric composition science and applications. We harvested GCMD, CWIC, GEOSS metadata catalogs using machine to machine technologies - OpenSearch, Web Services. We also manually investigated the plethora of CEOS data providers portals and other catalogs where that data might be aggregated. This poster is our experience of the excellence, variety, and challenges we encountered.Conclusions:1.The significant benefits that the major catalogs provide are their machine to machine tools like OpenSearch and Web Services rather than any GUI usability improvements due to the large amount of data in their catalog.2.There is a trend at the large catalogs towards simulating small data provider portals through advanced services. 3.Populating metadata catalogs using ISO19115 is too complex for users to do in a consistent way, difficult to parse visually or with XML libraries, and too complex for Java XML binders like CASTOR.4.The ability to search for Ids first and then for data (GCMD and ECHO) is better for machine to machine operations rather than the timeouts experienced when returning the entire metadata entry at once. 5.Metadata harvest and export activities between the major catalogs has led to a significant amount of duplication. (This is currently being addressed) 6.Most (if not all) Earth science atmospheric composition data providers store a reference to their data at GCMD.

Automated Atmospheric Composition Dataset Level Metadata Discovery. Difficulties and Surprises

NASA Astrophysics Data System (ADS)

Strub, R. F.; Falke, S. R.; Kempler, S.; Fialkowski, E.; Goussev, O.; Lynnes, C.

2015-12-01

The Atmospheric Composition Portal (ACP) is an aggregator and curator of information related to remotely sensed atmospheric composition data and analysis. It uses existing tools and technologies and, where needed, enhances those capabilities to provide interoperable access, tools, and contextual guidance for scientists and value-adding organizations using remotely sensed atmospheric composition data. The initial focus is on Essential Climate Variables identified by the Global Climate Observing System - CH4, CO, CO2, NO2, O3, SO2 and aerosols. This poster addresses our efforts in building the ACP Data Table, an interface to help discover and understand remotely sensed data that are related to atmospheric composition science and applications. We harvested GCMD, CWIC, GEOSS metadata catalogs using machine to machine technologies - OpenSearch, Web Services. We also manually investigated the plethora of CEOS data providers portals and other catalogs where that data might be aggregated. This poster is our experience of the excellence, variety, and challenges we encountered.Conclusions:1.The significant benefits that the major catalogs provide are their machine to machine tools like OpenSearch and Web Services rather than any GUI usability improvements due to the large amount of data in their catalog.2.There is a trend at the large catalogs towards simulating small data provider portals through advanced services. 3.Populating metadata catalogs using ISO19115 is too complex for users to do in a consistent way, difficult to parse visually or with XML libraries, and too complex for Java XML binders like CASTOR.4.The ability to search for Ids first and then for data (GCMD and ECHO) is better for machine to machine operations rather than the timeouts experienced when returning the entire metadata entry at once. 5.Metadata harvest and export activities between the major catalogs has led to a significant amount of duplication. (This is currently being addressed) 6.Most (if not all) Earth science atmospheric composition data providers store a reference to their data at GCMD.

Migrating the Dawn Data Archive to the PDS4 Standard

NASA Astrophysics Data System (ADS)

Joy, S. P.; Mafi, J. N.; King, T. A.; Raymond, C. A.; Russell, C. T.

2017-12-01

The Dawn mission was proposed prior to the development of the PDS4 standard and all of its data are archived at the PDS Small Bodies Node (SBN) using the older PDS3 standard. Plans to migrate the existing PDS archives to PDS4 have been discussed within PDS for some time, and have been reemphasized in the PDS Roadmap Study for 2017 - 2026 (https://pds.nasa.gov/roadmap/PlanetaryDataSystemRMS17-26_20jun17.pdf). Updating the Dawn metadata to PDS4 would enable users of those data to take advantage of new capabilities offered by PDS4, and insure the full compatibility of past archives with current and future PDS4 tools and services. The Dawn data themselves will not require any reformatting during the migration to PDS4. The data and documentation will need to be reorganized and the metadata enhanced to fill in the gaps in the PDS3 metadata. The planned migration to PDS4 would be primarily carried out at the Dawn Science Center (DSC) at UCLA but the activity will require close coordination with the PDS-SBN. The PDS4 standard allows individual nodes to customize the metadata through the use of optional parameters and local data dictionaries to satisfy discipline and mission specific search and retrieval requirements and support node tools and services. The DSC shares much of its staff with the Planetary Plasma Interactions (PPI) Node of the PDS. This sharing of personnel means that the DSC staff are well versed in the PDS4 standard, have actively participated in the development of this standard, and are fully trained in the use of PPI tools for PDS4 metadata migration and/or generation. The combination of PDS4 training and detailed understanding of the Dawn mission, instruments, and datasets makes the DSC the most cost-effective organization to migrate these data to PDS4.

Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database.

PubMed

Winsor, Geoffrey L; Griffiths, Emma J; Lo, Raymond; Dhillon, Bhavjinder K; Shay, Julie A; Brinkman, Fiona S L

2016-01-04

The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Introducing the PRIDE Archive RESTful web services.

PubMed

Reisinger, Florian; del-Toro, Noemi; Ternent, Tobias; Hermjakob, Henning; Vizcaíno, Juan Antonio

2015-07-01

The PRIDE (PRoteomics IDEntifications) database is one of the world-leading public repositories of mass spectrometry (MS)-based proteomics data and it is a founding member of the ProteomeXchange Consortium of proteomics resources. In the original PRIDE database system, users could access data programmatically by accessing the web services provided by the PRIDE BioMart interface. New REST (REpresentational State Transfer) web services have been developed to serve the most popular functionality provided by BioMart (now discontinued due to data scalability issues) and address the data access requirements of the newly developed PRIDE Archive. Using the API (Application Programming Interface) it is now possible to programmatically query for and retrieve peptide and protein identifications, project and assay metadata and the originally submitted files. Searching and filtering is also possible by metadata information, such as sample details (e.g. species and tissues), instrumentation (mass spectrometer), keywords and other provided annotations. The PRIDE Archive web services were first made available in April 2014. The API has already been adopted by a few applications and standalone tools such as PeptideShaker, PRIDE Inspector, the Unipept web application and the Python-based BioServices package. This application is free and open to all users with no login requirement and can be accessed at http://www.ebi.ac.uk/pride/ws/archive/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Influenza Research Database: An integrated bioinformatics resource for influenza virus research.

PubMed

Zhang, Yun; Aevermann, Brian D; Anderson, Tavis K; Burke, David F; Dauphin, Gwenaelle; Gu, Zhiping; He, Sherry; Kumar, Sanjeev; Larsen, Christopher N; Lee, Alexandra J; Li, Xiaomei; Macken, Catherine; Mahaffey, Colin; Pickett, Brett E; Reardon, Brian; Smith, Thomas; Stewart, Lucy; Suloway, Christian; Sun, Guangyu; Tong, Lei; Vincent, Amy L; Walters, Bryan; Zaremba, Sam; Zhao, Hongtao; Zhou, Liwei; Zmasek, Christian; Klem, Edward B; Scheuermann, Richard H

2017-01-04

The Influenza Research Database (IRD) is a U.S. National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Bioinformatics Resource Center dedicated to providing bioinformatics support for influenza virus research. IRD facilitates the research and development of vaccines, diagnostics and therapeutics against influenza virus by providing a comprehensive collection of influenza-related data integrated from various sources, a growing suite of analysis and visualization tools for data mining and hypothesis generation, personal workbench spaces for data storage and sharing, and active user community support. Here, we describe the recent improvements in IRD including the use of cloud and high performance computing resources, analysis and visualization of user-provided sequence data with associated metadata, predictions of novel variant proteins, annotations of phenotype-associated sequence markers and their predicted phenotypic effects, hemagglutinin (HA) clade classifications, an automated tool for HA subtype numbering conversion, linkouts to disease event data and the addition of host factor and antiviral drug components. All data and tools are freely available without restriction from the IRD website at https://www.fludb.org. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Rapid Response to Decision Making for Complex Issues - How Technologies of Cooperation Can Help

DTIC Science & Technology

2005-11-01

creating bottom–up taxonomies—called folksonomies —using metadata tools like del.icio.us (in which users create their own tags for bookmarking Web...tools such as RSS, tagging (and the consequent development of folksonomies ), wikis, and group visualization tools all help multiply the individual

Extension modules for storage, visualization and querying of genomic, genetic and breeding data in Tripal databases

PubMed Central

Lee, Taein; Cheng, Chun-Huai; Ficklin, Stephen; Yu, Jing; Humann, Jodi; Main, Dorrie

2017-01-01

Abstract Tripal is an open-source database platform primarily used for development of genomic, genetic and breeding databases. We report here on the release of the Chado Loader, Chado Data Display and Chado Search modules to extend the functionality of the core Tripal modules. These new extension modules provide additional tools for (1) data loading, (2) customized visualization and (3) advanced search functions for supported data types such as organism, marker, QTL/Mendelian Trait Loci, germplasm, map, project, phenotype, genotype and their respective metadata. The Chado Loader module provides data collection templates in Excel with defined metadata and data loaders with front end forms. The Chado Data Display module contains tools to visualize each data type and the metadata which can be used as is or customized as desired. The Chado Search module provides search and download functionality for the supported data types. Also included are the tools to visualize map and species summary. The use of materialized views in the Chado Search module enables better performance as well as flexibility of data modeling in Chado, allowing existing Tripal databases with different metadata types to utilize the module. These Tripal Extension modules are implemented in the Genome Database for Rosaceae (rosaceae.org), CottonGen (cottongen.org), Citrus Genome Database (citrusgenomedb.org), Genome Database for Vaccinium (vaccinium.org) and the Cool Season Food Legume Database (coolseasonfoodlegume.org). Database URL: https://www.citrusgenomedb.org/, https://www.coolseasonfoodlegume.org/, https://www.cottongen.org/, https://www.rosaceae.org/, https://www.vaccinium.org/

OntoStudyEdit: a new approach for ontology-based representation and management of metadata in clinical and epidemiological research.

PubMed

Uciteli, Alexandr; Herre, Heinrich

2015-01-01

The specification of metadata in clinical and epidemiological study projects absorbs significant expense. The validity and quality of the collected data depend heavily on the precise and semantical correct representation of their metadata. In various research organizations, which are planning and coordinating studies, the required metadata are specified differently, depending on many conditions, e.g., on the used study management software. The latter does not always meet the needs of a particular research organization, e.g., with respect to the relevant metadata attributes and structuring possibilities. The objective of the research, set forth in this paper, is the development of a new approach for ontology-based representation and management of metadata. The basic features of this approach are demonstrated by the software tool OntoStudyEdit (OSE). The OSE is designed and developed according to the three ontology method. This method for developing software is based on the interactions of three different kinds of ontologies: a task ontology, a domain ontology and a top-level ontology. The OSE can be easily adapted to different requirements, and it supports an ontologically founded representation and efficient management of metadata. The metadata specifications can by imported from various sources; they can be edited with the OSE, and they can be exported in/to several formats, which are used, e.g., by different study management software. Advantages of this approach are the adaptability of the OSE by integrating suitable domain ontologies, the ontological specification of mappings between the import/export formats and the DO, the specification of the study metadata in a uniform manner and its reuse in different research projects, and an intuitive data entry for non-expert users.

Geospatial resources for supporting data standards, guidance and best practice in health informatics

PubMed Central

2011-01-01

Background The 1980s marked the occasion when Geographical Information System (GIS) technology was broadly introduced into the geo-spatial community through the establishment of a strong GIS industry. This technology quickly disseminated across many countries, and has now become established as an important research, planning and commercial tool for a wider community that includes organisations in the public and private health sectors. The broad acceptance of GIS technology and the nature of its functionality have meant that numerous datasets have been created over the past three decades. Most of these datasets have been created independently, and without any structured documentation systems in place. However, search and retrieval systems can only work if there is a mechanism for datasets existence to be discovered and this is where proper metadata creation and management can greatly help. This situation must be addressed through support mechanisms such as Web-based portal technologies, metadata editor tools, automation, metadata standards and guidelines and collaborative efforts with relevant individuals and organisations. Engagement with data developers or administrators should also include a strategy of identifying the benefits associated with metadata creation and publication. Findings The establishment of numerous Spatial Data Infrastructures (SDIs), and other Internet resources, is a testament to the recognition of the importance of supporting good data management and sharing practices across the geographic information community. These resources extend to health informatics in support of research, public services and teaching and learning. This paper identifies many of these resources available to the UK academic health informatics community. It also reveals the reluctance of many spatial data creators across the wider UK academic community to use these resources to create and publish metadata, or deposit their data in repositories for sharing. The Go-Geo! service is introduced as an SDI developed to provide UK academia with the necessary resources to address the concerns surrounding metadata creation and data sharing. The Go-Geo! portal, Geodoc metadata editor tool, ShareGeo spatial data repository, and a range of other support resources, are described in detail. Conclusions This paper describes a variety of resources available for the health research and public health sector to use for managing and sharing their data. The Go-Geo! service is one resource which offers an SDI for the eclectic range of disciplines using GIS in UK academia, including health informatics. The benefits of data management and sharing are immense, and in these times of cost restraints, these resources can be seen as solutions to find cost savings which can be reinvested in more research. PMID:21269487

Annotation of rule-based models with formal semantics to enable creation, analysis, reuse and visualization.

PubMed

Misirli, Goksel; Cavaliere, Matteo; Waites, William; Pocock, Matthew; Madsen, Curtis; Gilfellon, Owen; Honorato-Zimmer, Ricardo; Zuliani, Paolo; Danos, Vincent; Wipat, Anil

2016-03-15

Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling framework to represent the complexity of biological systems. Annotation approaches have been widely used for reaction-based formalisms such as SBML. However, rule-based languages still lack a rich annotation framework to add semantic information, such as machine-readable descriptions, to the components of a model. We present an annotation framework and guidelines for annotating rule-based models, encoded in the commonly used Kappa and BioNetGen languages. We adapt widely adopted annotation approaches to rule-based models. We initially propose a syntax to store machine-readable annotations and describe a mapping between rule-based modelling entities, such as agents and rules, and their annotations. We then describe an ontology to both annotate these models and capture the information contained therein, and demonstrate annotating these models using examples. Finally, we present a proof of concept tool for extracting annotations from a model that can be queried and analyzed in a uniform way. The uniform representation of the annotations can be used to facilitate the creation, analysis, reuse and visualization of rule-based models. Although examples are given, using specific implementations the proposed techniques can be applied to rule-based models in general. The annotation ontology for rule-based models can be found at http://purl.org/rbm/rbmo The krdf tool and associated executable examples are available at http://purl.org/rbm/rbmo/krdf anil.wipat@newcastle.ac.uk or vdanos@inf.ed.ac.uk. © The Author 2015. Published by Oxford University Press.

Tools for proactive collection and use of quality metadata in GEOSS

NASA Astrophysics Data System (ADS)

Bastin, L.; Thum, S.; Maso, J.; Yang, K. X.; Nüst, D.; Van den Broek, M.; Lush, V.; Papeschi, F.; Riverola, A.

2012-12-01

The GEOSS Common Infrastructure allows interactive evaluation and selection of Earth Observation datasets by the scientific community and decision makers, but the data quality information needed to assess fitness for use is often patchy and hard to visualise when comparing candidate datasets. In a number of studies over the past decade, users repeatedly identified the same types of gaps in quality metadata, specifying the need for enhancements such as peer and expert review, better traceability and provenance information, information on citations and usage of a dataset, warning about problems identified with a dataset and potential workarounds, and 'soft knowledge' from data producers (e.g. recommendations for use which are not easily encoded using the existing standards). Despite clear identification of these issues in a number of recommendations, the gaps persist in practice and are highlighted once more in our own, more recent, surveys. This continuing deficit may well be the result of a historic paucity of tools to support the easy documentation and continual review of dataset quality. However, more recent developments in tools and standards, as well as more general technological advances, present the opportunity for a community of scientific users to adopt a more proactive attitude by commenting on their uses of data, and for that feedback to be federated with more traditional and static forms of metadata, allowing a user to more accurately assess the suitability of a dataset for their own specific context and reliability thresholds. The EU FP7 GeoViQua project aims to develop this opportunity by adding data quality representations to the existing search and visualisation functionalities of the Geo Portal. Subsequently we will help to close the gap by providing tools to easily create quality information, and to permit user-friendly exploration of that information as the ultimate incentive for improved data quality documentation. Quality information is derived from producer metadata, from the data themselves, from validation of in-situ sensor data, from provenance information and from user feedback, and will be aggregated to produce clear and useful summaries of quality, including a GEO Label. GeoViQua's conceptual quality information models for users and producers are specifically described and illustrated in this presentation. These models (which have been encoded as XML schemas and can be accessed at http://schemas.geoviqua.org/) are designed to satisfy the identified user needs while remaining consistent with current standards such as ISO 19115 and advanced drafts such as ISO 19157. The resulting components being developed for the GEO Portal are designed to lower the entry barrier to users who wish to help to generate and explore rich and useful metadata. This metadata will include reviews, comments and ratings, reports of usage in specific domains and specification of datasets used for benchmarking, as well as rich quantitative information encoded in more traditional data quality elements such as thematic correctness and positional accuracy. The value of the enriched metadata will also be enhanced by graphical tools for visualizing spatially distributed uncertainties. We demonstrate practical example applications in selected environmental application domains.

Metadata Design in the New PDS4 Standards - Something for Everybody

NASA Astrophysics Data System (ADS)

Raugh, Anne C.; Hughes, John S.

2015-11-01

The Planetary Data System (PDS) archives, supports, and distributes data of diverse targets, from diverse sources, to diverse users. One of the core problems addressed by the PDS4 data standard redesign was that of metadata - how to accommodate the increasingly sophisticated demands of search interfaces, analytical software, and observational documentation into label standards without imposing limits and constraints that would impinge on the quality or quantity of metadata that any particular observer or team could supply. And yet, as an archive, PDS must have detailed documentation for the metadata in the labels it supports, or the institutional knowledge encoded into those attributes will be lost - putting the data at risk.The PDS4 metadata solution is based on a three-step approach. First, it is built on two key ISO standards: ISO 11179 "Information Technology - Metadata Registries", which provides a common framework and vocabulary for defining metadata attributes; and ISO 14721 "Space Data and Information Transfer Systems - Open Archival Information System (OAIS) Reference Model", which provides the framework for the information architecture that enforces the object-oriented paradigm for metadata modeling. Second, PDS has defined a hierarchical system that allows it to divide its metadata universe into namespaces ("data dictionaries", conceptually), and more importantly to delegate stewardship for a single namespace to a local authority. This means that a mission can develop its own data model with a high degree of autonomy and effectively extend the PDS model to accommodate its own metadata needs within the common ISO 11179 framework. Finally, within a single namespace - even the core PDS namespace - existing metadata structures can be extended and new structures added to the model as new needs are identifiedThis poster illustrates the PDS4 approach to metadata management and highlights the expected return on the development investment for PDS, users and data preparers.

Standard formatted data units-control authority operations

NASA Technical Reports Server (NTRS)

1991-01-01

The purpose of this document is to illustrate a Control Authority's (CA) possible operation. The document is an interpretation and expansion of the concept found in the CA Procedures Recommendation. The CA is described in terms of the functions it performs for the management and control of data descriptions (metadata). Functions pertaining to the organization of Member Agency Control Authority Offices (MACAOs) (e.g., creating and disbanding) are not discussed. The document also provides an illustrative operational view of a CA through scenarios describing interaction between those roles involved in collecting, controlling, and accessing registered metadata. The roles interacting with the CA are identified by their actions in requesting and responding to requests for metadata, and by the type of information exchanged. The scenarios and examples presented in this document are illustrative only. They represent possible interactions supported by either a manual or automated system. These scenarios identify requirements for an automated system. These requirements are expressed by identifying the information to be exchanged and the services that may be provided by a CA for that exchange.

Mercury: An Example of Effective Software Reuse for Metadata Management, Data Discovery and Access

NASA Astrophysics Data System (ADS)

Devarakonda, Ranjeet; Palanisamy, Giri; Green, James; Wilson, Bruce E.

2008-12-01

Mercury is a federated metadata harvesting, data discovery and access tool based on both open source packages and custom developed software. Though originally developed for NASA, the Mercury development consortium now includes funding from NASA, USGS, and DOE. Mercury supports the reuse of metadata by enabling searching across a range of metadata specification and standards including XML, Z39.50, FGDC, Dublin-Core, Darwin-Core, EML, and ISO-19115. Mercury provides a single portal to information contained in distributed data management systems. It collects metadata and key data from contributing project servers distributed around the world and builds a centralized index. The Mercury search interfaces then allow the users to perform simple, fielded, spatial and temporal searches across these metadata sources. One of the major goals of the recent redesign of Mercury was to improve the software reusability across the 12 projects which currently fund the continuing development of Mercury. These projects span a range of land, atmosphere, and ocean ecological communities and have a number of common needs for metadata searches, but they also have a number of needs specific to one or a few projects. To balance these common and project-specific needs, Mercury's architecture has three major reusable components; a harvester engine, an indexing system and a user interface component. The harvester engine is responsible for harvesting metadata records from various distributed servers around the USA and around the world. The harvester software was packaged in such a way that all the Mercury projects will use the same harvester scripts but each project will be driven by a set of project specific configuration files. The harvested files are structured metadata records that are indexed against the search library API consistently, so that it can render various search capabilities such as simple, fielded, spatial and temporal. This backend component is supported by a very flexible, easy to use Graphical User Interface which is driven by cascading style sheets, which make it even simpler for reusable design implementation. The new Mercury system is based on a Service Oriented Architecture and effectively reuses components for various services such as Thesaurus Service, Gazetteer Web Service and UDDI Directory Services. The software also provides various search services including: RSS, Geo-RSS, OpenSearch, Web Services and Portlets, integrated shopping cart to order datasets from various data centers (ORNL DAAC, NSIDC) and integrated visualization tools. Other features include: Filtering and dynamic sorting of search results, book- markable search results, save, retrieve, and modify search criteria.

Mercury: An Example of Effective Software Reuse for Metadata Management, Data Discovery and Access

DOE Office of Scientific and Technical Information (OSTI.GOV)

Devarakonda, Ranjeet

2008-01-01

Mercury is a federated metadata harvesting, data discovery and access tool based on both open source packages and custom developed software. Though originally developed for NASA, the Mercury development consortium now includes funding from NASA, USGS, and DOE. Mercury supports the reuse of metadata by enabling searching across a range of metadata specification and standards including XML, Z39.50, FGDC, Dublin-Core, Darwin-Core, EML, and ISO-19115. Mercury provides a single portal to information contained in distributed data management systems. It collects metadata and key data from contributing project servers distributed around the world and builds a centralized index. The Mercury search interfacesmore » then allow the users to perform simple, fielded, spatial and temporal searches across these metadata sources. One of the major goals of the recent redesign of Mercury was to improve the software reusability across the 12 projects which currently fund the continuing development of Mercury. These projects span a range of land, atmosphere, and ocean ecological communities and have a number of common needs for metadata searches, but they also have a number of needs specific to one or a few projects. To balance these common and project-specific needs, Mercury's architecture has three major reusable components; a harvester engine, an indexing system and a user interface component. The harvester engine is responsible for harvesting metadata records from various distributed servers around the USA and around the world. The harvester software was packaged in such a way that all the Mercury projects will use the same harvester scripts but each project will be driven by a set of project specific configuration files. The harvested files are structured metadata records that are indexed against the search library API consistently, so that it can render various search capabilities such as simple, fielded, spatial and temporal. This backend component is supported by a very flexible, easy to use Graphical User Interface which is driven by cascading style sheets, which make it even simpler for reusable design implementation. The new Mercury system is based on a Service Oriented Architecture and effectively reuses components for various services such as Thesaurus Service, Gazetteer Web Service and UDDI Directory Services. The software also provides various search services including: RSS, Geo-RSS, OpenSearch, Web Services and Portlets, integrated shopping cart to order datasets from various data centers (ORNL DAAC, NSIDC) and integrated visualization tools. Other features include: Filtering and dynamic sorting of search results, book- markable search results, save, retrieve, and modify search criteria.« less

The NCAR Digital Asset Services Hub (DASH): Implementing Unified Data Discovery and Access

NASA Astrophysics Data System (ADS)

Stott, D.; Worley, S. J.; Hou, C. Y.; Nienhouse, E.

2017-12-01

The National Center for Atmospheric Research (NCAR) Directorate created the Data Stewardship Engineering Team (DSET) to plan and implement an integrated single entry point for uniform digital asset discovery and access across the organization in order to improve the efficiency of access, reduce the costs, and establish the foundation for interoperability with other federated systems. This effort supports new policies included in federal funding mandates, NSF data management requirements, and journal citation recommendations. An inventory during the early planning stage identified diverse asset types across the organization that included publications, datasets, metadata, models, images, and software tools and code. The NCAR Digital Asset Services Hub (DASH) is being developed and phased in this year to improve the quality of users' experiences in finding and using these assets. DASH serves to provide engagement, training, search, and support through the following four nodes (see figure). DASH MetadataDASH provides resources for creating and cataloging metadata to the NCAR Dialect, a subset of ISO 19115. NMDEdit, an editor based on a European open source application, has been configured for manual entry of NCAR metadata. CKAN, an open source data portal platform, harvests these XML records (along with records output directly from databases) from a Web Accessible Folder (WAF) on GitHub for validation. DASH SearchThe NCAR Dialect metadata drives cross-organization search and discovery through CKAN, which provides the display interface of search results. DASH search will establish interoperability by facilitating metadata sharing with other federated systems. DASH ConsultingThe DASH Data Curation & Stewardship Coordinator assists with Data Management (DM) Plan preparation and advises on Digital Object Identifiers. The coordinator arranges training sessions on the DASH metadata tools and DM planning, and provides one-on-one assistance as requested. DASH RepositoryA repository is under development for NCAR datasets currently not in existing lab-managed archives. The DASH repository will be under NCAR governance and meet Trustworthy Repositories Audit & Certification (TRAC) requirements. This poster will highlight the processes, lessons learned, and current status of the DASH effort at NCAR.

MMI: Increasing Community Collaboration

NASA Astrophysics Data System (ADS)

Galbraith, N. R.; Stocks, K.; Neiswender, C.; Maffei, A.; Bermudez, L.

2007-12-01

Building community requires a collaborative environment and guidance to help move members towards a common goal. An effective environment for community collaboration is a workspace that fosters participation and cooperation; effective guidance furthers common understanding and promotes best practices. The Marine Metadata Interoperability (MMI) project has developed a community web site to provide a collaborative environment for scientists, technologists, and data managers from around the world to learn about metadata and exchange ideas. Workshops, demonstration projects, and presentations also provide community-building opportunities for MMI. MMI has developed comprehensive online guides to help users understand and work with metadata standards, ontologies, and other controlled vocabularies. Documents such as "The Importance of Metadata Standards", "Usage vs. Discovery Vocabularies" and "Developing Controlled Vocabularies" guide scientists and data managers through a variety of metadata-related concepts. Members from eight organizations involved in marine science and informatics collaborated on this effort. The MMI web site has moved from Plone to Drupal, two content management systems which provide different opportunities for community-based work. Drupal's "organic groups" feature will be used to provide workspace for future teams tasked with content development, outreach, and other MMI mission-critical work. The new site is designed to enable members to easily create working areas, to build communities dedicated to developing consensus on metadata and other interoperability issues. Controlled-vocabulary-driven menus, integrated mailing-lists, member-based content creation and review tools are facets of the new web site architecture. This move provided the challenge of developing a hierarchical vocabulary to describe the resources presented on the site; consistent and logical tagging of web pages is the basis of Drupal site navigation. The new MMI web site presents enhanced opportunities for electronic discussions, focused collaborative work, and even greater community participation. The MMI project is beginning a new initiative to comprehensively catalog and document tools for marine metadata. The new MMI community-based web site will be used to support this work and to support the work of other ad-hoc teams in the future. We are seeking broad input from the community on this effort.

Mercury: Reusable software application for Metadata Management, Data Discovery and Access

NASA Astrophysics Data System (ADS)

Devarakonda, Ranjeet; Palanisamy, Giri; Green, James; Wilson, Bruce E.

2009-12-01

Mercury is a federated metadata harvesting, data discovery and access tool based on both open source packages and custom developed software. It was originally developed for NASA, and the Mercury development consortium now includes funding from NASA, USGS, and DOE. Mercury is itself a reusable toolset for metadata, with current use in 12 different projects. Mercury also supports the reuse of metadata by enabling searching across a range of metadata specification and standards including XML, Z39.50, FGDC, Dublin-Core, Darwin-Core, EML, and ISO-19115. Mercury provides a single portal to information contained in distributed data management systems. It collects metadata and key data from contributing project servers distributed around the world and builds a centralized index. The Mercury search interfaces then allow the users to perform simple, fielded, spatial and temporal searches across these metadata sources. One of the major goals of the recent redesign of Mercury was to improve the software reusability across the projects which currently fund the continuing development of Mercury. These projects span a range of land, atmosphere, and ocean ecological communities and have a number of common needs for metadata searches, but they also have a number of needs specific to one or a few projects To balance these common and project-specific needs, Mercury’s architecture includes three major reusable components; a harvester engine, an indexing system and a user interface component. The harvester engine is responsible for harvesting metadata records from various distributed servers around the USA and around the world. The harvester software was packaged in such a way that all the Mercury projects will use the same harvester scripts but each project will be driven by a set of configuration files. The harvested files are then passed to the Indexing system, where each of the fields in these structured metadata records are indexed properly, so that the query engine can perform simple, keyword, spatial and temporal searches across these metadata sources. The search user interface software has two API categories; a common core API which is used by all the Mercury user interfaces for querying the index and a customized API for project specific user interfaces. For our work in producing a reusable, portable, robust, feature-rich application, Mercury received a 2008 NASA Earth Science Data Systems Software Reuse Working Group Peer-Recognition Software Reuse Award. The new Mercury system is based on a Service Oriented Architecture and effectively reuses components for various services such as Thesaurus Service, Gazetteer Web Service and UDDI Directory Services. The software also provides various search services including: RSS, Geo-RSS, OpenSearch, Web Services and Portlets, integrated shopping cart to order datasets from various data centers (ORNL DAAC, NSIDC) and integrated visualization tools. Other features include: Filtering and dynamic sorting of search results, book-markable search results, save, retrieve, and modify search criteria.

ResistoMap-online visualization of human gut microbiota antibiotic resistome.

PubMed

Yarygin, Konstantin S; Kovarsky, Boris A; Bibikova, Tatyana S; Melnikov, Damir S; Tyakht, Alexander V; Alexeev, Dmitry G

2017-07-15

We created ResistoMap—a Web-based interactive visualization of the presence of genetic determinants conferring resistance to antibiotics, biocides and heavy metals in human gut microbiota. ResistoMap displays the data on more than 1500 published gut metagenomes of world populations including both healthy subjects and patients. Multiparameter display filters allow visual assessment of the associations between the meta-data and proportions of resistome. The geographic map navigation layer allows to state hypotheses regarding the global trends of antibiotic resistance and correlates the gut resistome variations with the national clinical guidelines on antibiotics application. ResistoMap was implemented using AngularJS, CoffeeScript, D3.js and TopoJSON. The tool is publicly available at http://resistomap.rcpcm.org. yarygin@phystech.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Data Publication and Interoperability for Long Tail Researchers via the Open Data Repository's (ODR) Data Publisher.

NASA Astrophysics Data System (ADS)

Stone, N.; Lafuente, B.; Bristow, T.; Keller, R.; Downs, R. T.; Blake, D. F.; Fonda, M.; Pires, A.

2016-12-01

Working primarily with astrobiology researchers at NASA Ames, the Open Data Repository (ODR) has been conducting a software pilot to meet the varying needs of this multidisciplinary community. Astrobiology researchers often have small communities or operate individually with unique data sets that don't easily fit into existing database structures. The ODR constructed its Data Publisher software to allow researchers to create databases with common metadata structures and subsequently extend them to meet their individual needs and data requirements. The software accomplishes these tasks through a web-based interface that allows collaborative creation and revision of common metadata templates and individual extensions to these templates for custom data sets. This allows researchers to search disparate datasets based on common metadata established through the metadata tools, but still facilitates distinct analyses and data that may be stored alongside the required common metadata. The software produces web pages that can be made publicly available at the researcher's discretion so that users may search and browse the data in an effort to make interoperability and data discovery a human-friendly task while also providing semantic data for machine-based discovery. Once relevant data has been identified, researchers can utilize the built-in application programming interface (API) that exposes the data for machine-based consumption and integration with existing data analysis tools (e.g. R, MATLAB, Project Jupyter - http://jupyter.org). The current evolution of the project has created the Astrobiology Habitable Environments Database (AHED)[1] which provides an interface to databases connected through a common metadata core. In the next project phase, the goal is for small research teams and groups to be self-sufficient in publishing their research data to meet funding mandates and academic requirements as well as fostering increased data discovery and interoperability through human-readable and machine-readable interfaces. This project is supported by the Science-Enabling Research Activity (SERA) and NASA NNX11AP82A, MSL. [1] B. Lafuente et al. (2016) AGU, submitted.

SIPSMetGen: It's Not Just For Aircraft Data and ECS Anymore.

NASA Astrophysics Data System (ADS)

Schwab, M.

2015-12-01

The SIPSMetGen utility, developed for the NASA EOSDIS project, under the EED contract, simplified the creation of file level metadata for the ECS System. The utility has been enhanced for ease of use, efficiency, speed and increased flexibility. The SIPSMetGen utility was originally created as a means of generating file level spatial metadata for Operation IceBridge. The first version created only ODL metadata, specific for ingest into ECS. The core strength of the utility was, and continues to be, its ability to take complex shapes and patterns of data collection point clouds from aircraft flights and simplify them to a relatively simple concave hull geo-polygon. It has been found to be a useful and easy to use tool for creating file level metadata for many other missions, both aircraft and satellite. While the original version was useful it had its limitations. In 2014 Raytheon was tasked to make enhancements to SIPSMetGen, this resulted a new version of SIPSMetGen which can create ISO Compliant XML metadata; provides optimization and streamlining of the algorithm for creating the spatial metadata; a quicker runtime with more consistent results; a utility that can be configured to run multi-threaded on systems with multiple processors. The utility comes with a java based graphical user interface to aid in configuration and running of the utility. The enhanced SIPSMetGen allows more diverse data sets to be archived with file level metadata. The advantage of archiving data with file level metadata is that it makes it easier for data users, and scientists to find relevant data. File level metadata unlocks the power of existing archives and metadata repositories such as ECS and CMR and search and discovery utilities like Reverb and Earth Data Search. Current missions now using SIPSMetGen include: Aquarius, Measures, ARISE, and Nimbus.

Building a high level sample processing and quality assessment model for biogeochemical measurements: a case study from the ocean acidification community

NASA Astrophysics Data System (ADS)

Thomas, R.; Connell, D.; Spears, T.; Leadbetter, A.; Burger, E. F.

2016-12-01

The scientific literature heavily features small-scale studies with the impact of the results extrapolated to regional/global importance. There are on-going initiatives (e.g. OA-ICC, GOA-ON, GEOTRACES, EMODNet Chemistry) aiming to assemble regional to global-scale datasets that are available for trend or meta-analyses. Assessing the quality and comparability of these data requires information about the processing chain from "sampling to spreadsheet". This provenance information needs to be captured and readily available to assess data fitness for purpose. The NOAA Ocean Acidification metadata template was designed in consultation with domain experts for this reason; the core carbonate chemistry variables have 23-37 metadata fields each and for scientists generating these datasets there could appear to be an ever increasing amount of metadata expected to accompany a dataset. While this provenance metadata should be considered essential by those generating or using the data, for those discovering data there is a sliding scale between what is considered discovery metadata (title, abstract, contacts, etc.) versus usage metadata (methodology, environmental setup, lineage, etc.), the split depending on the intended use of data. As part of the OA-ICC's activities, the metadata fields from the NOAA template relevant to the sample processing chain and QA criteria have been factored to develop profiles for, and extensions to, the OM-JSON encoding supported by the PROV ontology. While this work started focused on carbonate chemistry variable specific metadata, the factorization could be applied within the O&M model across other disciplines such as trace metals or contaminants. In a linked data world with a suitable high level model for sample processing and QA available, tools and support can be provided to link reproducible units of metadata (e.g. the standard protocol for a variable as adopted by a community) and simplify the provision of metadata and subsequent discovery.

Metadata Creation, Management and Search System for your Scientific Data

NASA Astrophysics Data System (ADS)

Devarakonda, R.; Palanisamy, G.

2012-12-01

Mercury Search Systems is a set of tools for creating, searching, and retrieving of biogeochemical metadata. Mercury toolset provides orders of magnitude improvements in search speed, support for any metadata format, integration with Google Maps for spatial queries, multi-facetted type search, search suggestions, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. Mercury's metadata editor provides a easy way for creating metadata and Mercury's search interface provides a single portal to search for data and information contained in disparate data management systems, each of which may use any metadata format including FGDC, ISO-19115, Dublin-Core, Darwin-Core, DIF, ECHO, and EML. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury is being used more than 14 different projects across 4 federal agencies. It was originally developed for NASA, with continuing development funded by NASA, USGS, and DOE for a consortium of projects. Mercury search won the NASA's Earth Science Data Systems Software Reuse Award in 2008. References: R. Devarakonda, G. Palanisamy, B.E. Wilson, and J.M. Green, "Mercury: reusable metadata management data discovery and access system", Earth Science Informatics, vol. 3, no. 1, pp. 87-94, May 2010. R. Devarakonda, G. Palanisamy, J.M. Green, B.E. Wilson, "Data sharing and retrieval using OAI-PMH", Earth Science Informatics DOI: 10.1007/s12145-010-0073-0, (2010);

Metadata and Service at the GFZ ISDC Portal

NASA Astrophysics Data System (ADS)

Ritschel, B.

2008-05-01

The online service portal of the GFZ Potsdam Information System and Data Center (ISDC) is an access point for all manner of geoscientific geodata, its corresponding metadata, scientific documentation and software tools. At present almost 2000 national and international users and user groups have the opportunity to request Earth science data from a portfolio of 275 different products types and more than 20 Million single data files with an added volume of approximately 12 TByte. The majority of the data and information, the portal currently offers to the public, are global geomonitoring products such as satellite orbit and Earth gravity field data as well as geomagnetic and atmospheric data for the exploration. These products for Earths changing system are provided via state-of-the art retrieval techniques. The data product catalog system behind these techniques is based on the extensive usage of standardized metadata, which are describing the different geoscientific product types and data products in an uniform way. Where as all ISDC product types are specified by NASA's Directory Interchange Format (DIF), Version 9.0 Parent XML DIF metadata files, the individual data files are described by extended DIF metadata documents. Depending on the beginning of the scientific project, one part of data files are described by extended DIF, Version 6 metadata documents and the other part are specified by data Child XML DIF metadata documents. Both, the product type dependent parent DIF metadata documents and the data file dependent child DIF metadata documents are derived from a base-DIF.xsd xml schema file. The ISDC metadata philosophy defines a geoscientific product as a package consisting of mostly one or sometimes more than one data file plus one extended DIF metadata file. Because NASA's DIF metadata standard has been developed in order to specify a collection of data only, the extension of the DIF standard consists of new and specific attributes, which are necessary for an explicit identification of single data files and the set-up of a comprehensive Earth science data catalog. The huge ISDC data catalog is realized by product type dependent tables filled with data file related metadata, which have relations to corresponding metadata tables. The product type describing parent DIF XML metadata documents are stored and managed in ORACLE's XML storage structures. In order to improve the interoperability of the ISDC service portal, the existing proprietary catalog system will be extended by an ISO 19115 based web catalog service. In addition to this development there is ISDC related concerning semantic network of different kind of metadata resources, like different kind of standardized and not-standardized metadata documents and literature as well as Web 2.0 user generated information derived from tagging activities and social navigation data.

Designing an Exploratory Text Analysis Tool for Humanities and Social Sciences Research

ERIC Educational Resources Information Center

Shrikumar, Aditi

2013-01-01

This dissertation presents a new tool for exploratory text analysis that attempts to improve the experience of navigating and exploring text and its metadata. The design of the tool was motivated by the unmet need for text analysis tools in the humanities and social sciences. In these fields, it is common for scholars to have hundreds or thousands…

MetaSRA: normalized human sample-specific metadata for the Sequence Read Archive.

PubMed

Bernstein, Matthew N; Doan, AnHai; Dewey, Colin N

2017-09-15

The NCBI's Sequence Read Archive (SRA) promises great biological insight if one could analyze the data in the aggregate; however, the data remain largely underutilized, in part, due to the poor structure of the metadata associated with each sample. The rules governing submissions to the SRA do not dictate a standardized set of terms that should be used to describe the biological samples from which the sequencing data are derived. As a result, the metadata include many synonyms, spelling variants and references to outside sources of information. Furthermore, manual annotation of the data remains intractable due to the large number of samples in the archive. For these reasons, it has been difficult to perform large-scale analyses that study the relationships between biomolecular processes and phenotype across diverse diseases, tissues and cell types present in the SRA. We present MetaSRA, a database of normalized SRA human sample-specific metadata following a schema inspired by the metadata organization of the ENCODE project. This schema involves mapping samples to terms in biomedical ontologies, labeling each sample with a sample-type category, and extracting real-valued properties. We automated these tasks via a novel computational pipeline. The MetaSRA is available at metasra.biostat.wisc.edu via both a searchable web interface and bulk downloads. Software implementing our computational pipeline is available at http://github.com/deweylab/metasra-pipeline. cdewey@biostat.wisc.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

CellML metadata standards, associated tools and repositories

PubMed Central

Beard, Daniel A.; Britten, Randall; Cooling, Mike T.; Garny, Alan; Halstead, Matt D.B.; Hunter, Peter J.; Lawson, James; Lloyd, Catherine M.; Marsh, Justin; Miller, Andrew; Nickerson, David P.; Nielsen, Poul M.F.; Nomura, Taishin; Subramanium, Shankar; Wimalaratne, Sarala M.; Yu, Tommy

2009-01-01

The development of standards for encoding mathematical models is an important component of model building and model sharing among scientists interested in understanding multi-scale physiological processes. CellML provides such a standard, particularly for models based on biophysical mechanisms, and a substantial number of models are now available in the CellML Model Repository. However, there is an urgent need to extend the current CellML metadata standard to provide biological and biophysical annotation of the models in order to facilitate model sharing, automated model reduction and connection to biological databases. This paper gives a broad overview of a number of new developments on CellML metadata and provides links to further methodological details available from the CellML website. PMID:19380315

ODMedit: uniform semantic annotation for data integration in medicine based on a public metadata repository.

PubMed

Dugas, Martin; Meidt, Alexandra; Neuhaus, Philipp; Storck, Michael; Varghese, Julian

2016-06-01

The volume and complexity of patient data - especially in personalised medicine - is steadily increasing, both regarding clinical data and genomic profiles: Typically more than 1,000 items (e.g., laboratory values, vital signs, diagnostic tests etc.) are collected per patient in clinical trials. In oncology hundreds of mutations can potentially be detected for each patient by genomic profiling. Therefore data integration from multiple sources constitutes a key challenge for medical research and healthcare. Semantic annotation of data elements can facilitate to identify matching data elements in different sources and thereby supports data integration. Millions of different annotations are required due to the semantic richness of patient data. These annotations should be uniform, i.e., two matching data elements shall contain the same annotations. However, large terminologies like SNOMED CT or UMLS don't provide uniform coding. It is proposed to develop semantic annotations of medical data elements based on a large-scale public metadata repository. To achieve uniform codes, semantic annotations shall be re-used if a matching data element is available in the metadata repository. A web-based tool called ODMedit ( https://odmeditor.uni-muenster.de/ ) was developed to create data models with uniform semantic annotations. It contains ~800,000 terms with semantic annotations which were derived from ~5,800 models from the portal of medical data models (MDM). The tool was successfully applied to manually annotate 22 forms with 292 data items from CDISC and to update 1,495 data models of the MDM portal. Uniform manual semantic annotation of data models is feasible in principle, but requires a large-scale collaborative effort due to the semantic richness of patient data. A web-based tool for these annotations is available, which is linked to a public metadata repository.

DataUp 2.0: Improving On a Tool For Helping Researchers Archive, Manage, and Share Their Tabular Data

NASA Astrophysics Data System (ADS)

Strasser, C.; Borda, S.; Cruse, P.; Kunze, J.

2013-12-01

There are many barriers to data management and sharing among earth and environmental scientists; among the most significant are a lack of knowledge about best practices for data management, metadata standards, or appropriate data repositories for archiving and sharing data. Last year we developed an open source web application, DataUp, to help researchers overcome these barriers. DataUp helps scientists to (1) determine whether their file is CSV compatible, (2) generate metadata in a standard format, (3) retrieve an identifier to facilitate data citation, and (4) deposit their data into a repository. With funding from the NSF via a supplemental grant to the DataONE project, we are working to improve upon DataUp. Our main goal for DataUp 2.0 is to ensure organizations and repositories are able to adopt and adapt DataUp to meet their unique needs, including connecting to analytical tools, adding new metadata schema, and expanding the list of connected data repositories. DataUp is a collaborative project between the California Digital Library, DataONE, the San Diego Supercomputing Center, and Microsoft Research Connections.

OntoCheck: verifying ontology naming conventions and metadata completeness in Protégé 4

PubMed Central

2012-01-01

Background Although policy providers have outlined minimal metadata guidelines and naming conventions, ontologies of today still display inter- and intra-ontology heterogeneities in class labelling schemes and metadata completeness. This fact is at least partially due to missing or inappropriate tools. Software support can ease this situation and contribute to overall ontology consistency and quality by helping to enforce such conventions. Objective We provide a plugin for the Protégé Ontology editor to allow for easy checks on compliance towards ontology naming conventions and metadata completeness, as well as curation in case of found violations. Implementation In a requirement analysis, derived from a prior standardization approach carried out within the OBO Foundry, we investigate the needed capabilities for software tools to check, curate and maintain class naming conventions. A Protégé tab plugin was implemented accordingly using the Protégé 4.1 libraries. The plugin was tested on six different ontologies. Based on these test results, the plugin could be refined, also by the integration of new functionalities. Results The new Protégé plugin, OntoCheck, allows for ontology tests to be carried out on OWL ontologies. In particular the OntoCheck plugin helps to clean up an ontology with regard to lexical heterogeneity, i.e. enforcing naming conventions and metadata completeness, meeting most of the requirements outlined for such a tool. Found test violations can be corrected to foster consistency in entity naming and meta-annotation within an artefact. Once specified, check constraints like name patterns can be stored and exchanged for later re-use. Here we describe a first version of the software, illustrate its capabilities and use within running ontology development efforts and briefly outline improvements resulting from its application. Further, we discuss OntoChecks capabilities in the context of related tools and highlight potential future expansions. Conclusions The OntoCheck plugin facilitates labelling error detection and curation, contributing to lexical quality assurance in OWL ontologies. Ultimately, we hope this Protégé extension will ease ontology alignments as well as lexical post-processing of annotated data and hence can increase overall secondary data usage by humans and computers. PMID:23046606

Building a High Performance Metadata Broker using Clojure, NoSQL and Message Queues

NASA Astrophysics Data System (ADS)

Truslove, I.; Reed, S.

2013-12-01

In practice, Earth and Space Science Informatics often relies on getting more done with less: fewer hardware resources, less IT staff, fewer lines of code. As a capacity-building exercise focused on rapid development of high-performance geoinformatics software, the National Snow and Ice Data Center (NSIDC) built a prototype metadata brokering system using a new JVM language, modern database engines and virtualized or cloud computing resources. The metadata brokering system was developed with the overarching goals of (i) demonstrating a technically viable product with as little development effort as possible, (ii) using very new yet very popular tools and technologies in order to get the most value from the least legacy-encumbered code bases, and (iii) being a high-performance system by using scalable subcomponents, and implementation patterns typically used in web architectures. We implemented the system using the Clojure programming language (an interactive, dynamic, Lisp-like JVM language), Redis (a fast in-memory key-value store) as both the data store for original XML metadata content and as the provider for the message queueing service, and ElasticSearch for its search and indexing capabilities to generate search results. On evaluating the results of the prototyping process, we believe that the technical choices did in fact allow us to do more for less, due to the expressive nature of the Clojure programming language and its easy interoperability with Java libraries, and the successful reuse or re-application of high performance products or designs. This presentation will describe the architecture of the metadata brokering system, cover the tools and techniques used, and describe lessons learned, conclusions, and potential next steps.

The Planetary Data System Information Model for Geometry Metadata

NASA Astrophysics Data System (ADS)

Guinness, E. A.; Gordon, M. K.

2014-12-01

The NASA Planetary Data System (PDS) has recently developed a new set of archiving standards based on a rigorously defined information model. An important part of the new PDS information model is the model for geometry metadata, which includes, for example, attributes of the lighting and viewing angles of observations, position and velocity vectors of a spacecraft relative to Sun and observing body at the time of observation and the location and orientation of an observation on the target. The PDS geometry model is based on requirements gathered from the planetary research community, data producers, and software engineers who build search tools. A key requirement for the model is that it fully supports the breadth of PDS archives that include a wide range of data types from missions and instruments observing many types of solar system bodies such as planets, ring systems, and smaller bodies (moons, comets, and asteroids). Thus, important design aspects of the geometry model are that it standardizes the definition of the geometry attributes and provides consistency of geometry metadata across planetary science disciplines. The model specification also includes parameters so that the context of values can be unambiguously interpreted. For example, the reference frame used for specifying geographic locations on a planetary body is explicitly included with the other geometry metadata parameters. The structure and content of the new PDS geometry model is designed to enable both science analysis and efficient development of search tools. The geometry model is implemented in XML, as is the main PDS information model, and uses XML schema for validation. The initial version of the geometry model is focused on geometry for remote sensing observations conducted by flyby and orbiting spacecraft. Future releases of the PDS geometry model will be expanded to include metadata for landed and rover spacecraft.

Enabling Interoperability and Servicing Multiple User Segments Through Web Services, Standards, and Data Tools

NASA Astrophysics Data System (ADS)

Palanisamy, Giriprakash; Wilson, Bruce E.; Cook, Robert B.; Lenhardt, Chris W.; Santhana Vannan, Suresh; Pan, Jerry; McMurry, Ben F.; Devarakonda, Ranjeet

2010-12-01

The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) is one of the science-oriented data centers in EOSDIS, aligned primarily with terrestrial ecology. The ORNL DAAC archives and serves data from NASA-funded field campaigns (such as BOREAS, FIFE, and LBA), regional and global data sets relevant to biogeochemical cycles, land validation studies for remote sensing, and source code for some terrestrial ecology models. Users of the ORNL DAAC include field ecologists, remote sensing scientists, modelers at various scales, synthesis scientific groups, a range of educational users (particularly baccalaureate and graduate instruction), and decision support analysts. It is clear that the wide range of users served by the ORNL DAAC have differing needs and differing capabilities for accessing and using data. It is also not possible for the ORNL DAAC, or the other data centers in EDSS to develop all of the tools and interfaces to support even most of the potential uses of data directly. As is typical of Information Technology to support a research enterprise, the user needs will continue to evolve rapidly over time and users themselves cannot predict future needs, as those needs depend on the results of current investigation. The ORNL DAAC is addressing these needs by targeted implementation of web services and tools which can be consumed by other applications, so that a modeler can retrieve data in netCDF format with the Climate Forecasting convention and a field ecologist can retrieve subsets of that same data in a comma separated value format, suitable for use in Excel or R. Tools such as our MODIS Subsetting capability, the Spatial Data Access Tool (SDAT; based on OGC web services), and OPeNDAP-compliant servers such as THREDDS particularly enable such diverse means of access. We also seek interoperability of metadata, recognizing that terrestrial ecology is a field where there are a very large number of relevant data repositories. ORNL DAAC metadata is published to several metadata repositories using the Open Archive Initiative Protocol for Metadata Handling (OAI-PMH), to increase the chances that users can find data holdings relevant to their particular scientific problem. ORNL also seeks to leverage technology across these various data projects and encourage standardization of processes and technical architecture. This standardization is behind current efforts involving the use of Drupal and Fedora Commons. This poster describes the current and planned approaches that the ORNL DAAC is taking to enable cost-effective interoperability among data centers, both across the NASA EOSDIS data centers and across the international spectrum of terrestrial ecology-related data centers. The poster will highlight the standards that we are currently using across data formats, metadata formats, and data protocols. References: [1]Devarakonda R., et al. Mercury: reusable metadata management, data discovery and access system. Earth Science Informatics (2010), 3(1): 87-94. [2]Devarakonda R., et al. Data sharing and retrieval using OAI-PMH. Earth Science Informatics (2011), 4(1): 1-5.

Chapter 35: Describing Data and Data Collections in the VO

NASA Astrophysics Data System (ADS)

Kent, B. R.; Hanisch, R. J.; Williams, R. D.

The list of numbers: 19.22, 17.23, 18.11, 16.98, and 15.11, is of little intrinsic interest without information about the context in which they appear. For instance, are these daily closing stock prices for your favorite investment, or are they hourly photometric measurements of an increasingly bright quasar? The information needed to define this context is called metadata. Metadata are data about data. Astronomers are familiar with metadata through the headers of FITS files and the names and units associated with columns in a table or database. In the VO, metadata describe the contents of tables, images, and spectra, as well as aggregate collections of data (archives, surveys) and computational services. Moreover, VO metadata are constructed according to rules that avoid ambiguity and make it clear whether, in the example above, the stock prices are in dollars or euros, or the photometry is Johnson V or Sloan g. Organization of data is important in any scientific discipline. Equally crucial are the descriptions of that data: the organization publishing the data, its creator or the person making it available, what instruments were used, units assigned to measurement, calibration status, and data quality assessment. The Virtual Observatory metadata scheme not only applies to datasets, but to resources as well, including data archive facilities, searchable web forms, and online analysis and display tools. Since the scientific output flowing from large datasets depends greatly on how well the data are described, it is important for users to understand the basics of the metadata scheme in order to locate the data that they want and use it correctly. Metadata are the key to data discovery and data and service interoperability in the Virtual Observatory.

Evaluating the Interdisciplinary Discoverability of Data

NASA Astrophysics Data System (ADS)

Gordon, S.; Habermann, T.

2017-12-01

Documentation needs are similar across communities. Communities tend to agree on many of the basic concepts necessary for discovery. Shared concepts such as a title or a description of the data exist in most metadata dialects. Many dialects have been designed and recommendations implemented to create metadata valuable for data discovery. These implementations can create barriers to discovering the right data. How can we ensure that the documentation we curate will be discoverable and understandable by researchers outside of our own disciplines and organizations? Since communities tend to use and understand many of the same documentation concepts, the barriers to interdisciplinary discovery are caused by the differences in the implementation. Thus tools and methods designed for the conceptual layer that evaluate records for documentation concepts, regardless of the dialect, can be effective in identifying opportunities for improvement and providing guidance. The Metadata Evaluation Web Service combined with a Jupyter Notebook interface allows a user to gather insight about a collection of records with respect to different communities' conceptual recommendations. It accomplishes this via data visualizations and provides links to implementation specific guidance on the ESIP Wiki for each recommendation applied to the collection. By utilizing these curation tools as part of an iterative process the data's impact can be increased by making it discoverable to a greater scientific and research community. Due to the conceptual focus of the methods and tools used, they can be utilized by any community or organization regardless of their documentation dialect or tools.

The Value of Data and Metadata Standardization for Interoperability in Giovanni Or: Why Your Product's Metadata Causes Us Headaches!

NASA Technical Reports Server (NTRS)

Smit, Christine; Hegde, Mahabaleshwara; Strub, Richard; Bryant, Keith; Li, Angela; Petrenko, Maksym

2017-01-01

Giovanni is a data exploration and visualization tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC). It has been around in one form or another for more than 15 years. Giovanni calculates simple statistics and produces 22 different visualizations for more than 1600 geophysical parameters from more than 90 satellite and model products. Giovanni relies on external data format standards to ensure interoperability, including the NetCDF CF Metadata Conventions. Unfortunately, these standards were insufficient to make Giovanni's internal data representation truly simple to use. Finding and working with dimensions can be convoluted with the CF Conventions. Furthermore, the CF Conventions are silent on machine-friendly descriptive metadata such as the parameter's source product and product version. In order to simplify analyzing disparate earth science data parameters in a unified way, we developed Giovanni's internal standard. First, the format standardizes parameter dimensions and variables so they can be easily found. Second, the format adds all the machine-friendly metadata Giovanni needs to present our parameters to users in a consistent and clear manner. At a glance, users can grasp all the pertinent information about parameters both during parameter selection and after visualization.

Metadata management for high content screening in OMERO

PubMed Central

Li, Simon; Besson, Sébastien; Blackburn, Colin; Carroll, Mark; Ferguson, Richard K.; Flynn, Helen; Gillen, Kenneth; Leigh, Roger; Lindner, Dominik; Linkert, Melissa; Moore, William J.; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Allan, Chris; Burel, Jean-Marie; Moore, Josh; Swedlow, Jason R.

2016-01-01

High content screening (HCS) experiments create a classic data management challenge—multiple, large sets of heterogeneous structured and unstructured data, that must be integrated and linked to produce a set of “final” results. These different data include images, reagents, protocols, analytic output, and phenotypes, all of which must be stored, linked and made accessible for users, scientists, collaborators and where appropriate the wider community. The OME Consortium has built several open source tools for managing, linking and sharing these different types of data. The OME Data Model is a metadata specification that supports the image data and metadata recorded in HCS experiments. Bio-Formats is a Java library that reads recorded image data and metadata and includes support for several HCS screening systems. OMERO is an enterprise data management application that integrates image data, experimental and analytic metadata and makes them accessible for visualization, mining, sharing and downstream analysis. We discuss how Bio-Formats and OMERO handle these different data types, and how they can be used to integrate, link and share HCS experiments in facilities and public data repositories. OME specifications and software are open source and are available at https://www.openmicroscopy.org. PMID:26476368

Environmental Information Management For Data Discovery and Access System

NASA Astrophysics Data System (ADS)

Giriprakash, P.

2011-01-01

Mercury is a federated metadata harvesting, search and retrieval tool based on both open source software and software developed at Oak Ridge National Laboratory. It was originally developed for NASA, and the Mercury development consortium now includes funding from NASA, USGS, and DOE. A major new version of Mercury was developed during 2007 and released in early 2008. This new version provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, support for RSS delivery of search results, and ready customization to meet the needs of the multiple projects which use Mercury. For the end users, Mercury provides a single portal to very quickly search for data and information contained in disparate data management systems. It collects metadata and key data from contributing project servers distributed around the world and builds a centralized index. The Mercury search interfaces then allow ! the users to perform simple, fielded, spatial and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data.

The Modeling and Simulation Catalog for Discovery, Knowledge and Reuse

NASA Technical Reports Server (NTRS)

Stone, George F. III; Greenberg, Brandi; Daehler-Wilking, Richard; Hunt, Steven

2011-01-01

The DoD M&S Steering Committee has noted that the current DoD and Service's modeling and simulation resource repository (MSRR) services are not up-to-date limiting their value to the using communities. However, M&S leaders and managers also determined that the Department needs a functional M&S registry card catalog to facilitate M&S tool and data visibility to support M&S activities across the DoD. The M&S Catalog will discover and access M&S metadata maintained at nodes distributed across DoD networks in a centrally managed, decentralized process that employs metadata collection and management. The intent is to link information stores, precluding redundant location updating. The M&S Catalog uses a standard metadata schemas based on the DoD's Net-Centric Data Strategy Community of Interest metadata specification. The Air Force, Navy and OSD (CAPE) have provided initial information to participating DoD nodes, but plans on the horizon are being made to bring in hundreds of source providers.

Motivating Communities To Go Beyond the Discovery Plateau

NASA Astrophysics Data System (ADS)

Habermann, T.; Kozimor, J.

2014-12-01

Years of emphasizing discovery and minimal metadata requirements have resulted in a culture that accepts that metadata are for discovery and complete metadata are too complex or difficult for researchers to understand and create. Evolving the culture past this "data-discovery plateau" requires a multi-faceted approach that addresses the rational and emotional sides of the problem. On the rational side, scientists know that data and results must be well documented in order to be reproducible, re-usable, and trustworthy. We need tools that script critical moves towards well-described destinations and help identify members of the community that are already leading the way towards those destinations. We need mechanisms that help those leaders share their experiences and examples. On the emotional side, we need to emphasize that high-quality metadata makes data trustworthy, divide the improvement process into digestible pieces and create mechanisms for clearly identifying and rewarding progress. We also need to provide clear opportunities for community members to increase their expertise and to share their skills.

Metadata tables to enable dynamic data modeling and web interface design: the SEER example.

PubMed

Weiner, Mark; Sherr, Micah; Cohen, Abigail

2002-04-01

A wealth of information addressing health status, outcomes and resource utilization is compiled and made available by various government agencies. While exploration of the data is possible using existing tools, in general, would-be users of the resources must acquire CD-ROMs or download data from the web, and upload the data into their own database. Where web interfaces exist, they are highly structured, limiting the kinds of queries that can be executed. This work develops a web-based database interface engine whose content and structure is generated through interaction with a metadata table. The result is a dynamically generated web interface that can easily accommodate changes in the underlying data model by altering the metadata table, rather than requiring changes to the interface code. This paper discusses the background and implementation of the metadata table and web-based front end and provides examples of its use with the NCI's Surveillance, Epidemiology and End-Results (SEER) database.

Automated software system for checking the structure and format of ACM SIG documents

NASA Astrophysics Data System (ADS)

Mirza, Arsalan Rahman; Sah, Melike

2017-04-01

Microsoft (MS) Office Word is one of the most commonly used software tools for creating documents. MS Word 2007 and above uses XML to represent the structure of MS Word documents. Metadata about the documents are automatically created using Office Open XML (OOXML) syntax. We develop a new framework, which is called ADFCS (Automated Document Format Checking System) that takes the advantage of the OOXML metadata, in order to extract semantic information from MS Office Word documents. In particular, we develop a new ontology for Association for Computing Machinery (ACM) Special Interested Group (SIG) documents for representing the structure and format of these documents by using OWL (Web Ontology Language). Then, the metadata is extracted automatically in RDF (Resource Description Framework) according to this ontology using the developed software. Finally, we generate extensive rules in order to infer whether the documents are formatted according to ACM SIG standards. This paper, introduces ACM SIG ontology, metadata extraction process, inference engine, ADFCS online user interface, system evaluation and user study evaluations.

Web-based network analysis and visualization using CellMaps.

PubMed

Salavert, Francisco; García-Alonso, Luz; Sánchez, Rubén; Alonso, Roberto; Bleda, Marta; Medina, Ignacio; Dopazo, Joaquín

2016-10-01

: CellMaps is an HTML5 open-source web tool that allows displaying, editing, exploring and analyzing biological networks as well as integrating metadata into them. Computations and analyses are remotely executed in high-end servers, and all the functionalities are available through RESTful web services. CellMaps can easily be integrated in any web page by using an available JavaScript API. The application is available at: http://cellmaps.babelomics.org/ and the code can be found in: https://github.com/opencb/cell-maps The client is implemented in JavaScript and the server in C and Java. jdopazo@cipf.es Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Mercury- Distributed Metadata Management, Data Discovery and Access System

NASA Astrophysics Data System (ADS)

Palanisamy, Giri; Wilson, Bruce E.; Devarakonda, Ranjeet; Green, James M.

2007-12-01

Mercury is a federated metadata harvesting, search and retrieval tool based on both open source and ORNL- developed software. It was originally developed for NASA, and the Mercury development consortium now includes funding from NASA, USGS, and DOE. Mercury supports various metadata standards including XML, Z39.50, FGDC, Dublin-Core, Darwin-Core, EML, and ISO-19115 (under development). Mercury provides a single portal to information contained in disparate data management systems. It collects metadata and key data from contributing project servers distributed around the world and builds a centralized index. The Mercury search interfaces then allow the users to perform simple, fielded, spatial and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury supports various projects including: ORNL DAAC, NBII, DADDI, LBA, NARSTO, CDIAC, OCEAN, I3N, IAI, ESIP and ARM. The new Mercury system is based on a Service Oriented Architecture and supports various services such as Thesaurus Service, Gazetteer Web Service and UDDI Directory Services. This system also provides various search services including: RSS, Geo-RSS, OpenSearch, Web Services and Portlets. Other features include: Filtering and dynamic sorting of search results, book-markable search results, save, retrieve, and modify search criteria.

Integration of upper air data in the MeteoSwiss Data Warehouse

NASA Astrophysics Data System (ADS)

Musa, M.; Haeberli, Ch.; Ruffieux, D.

2010-09-01

Over the last 10 years MeteoSwiss established a Data Warehouse in order to get one single, integrated data platform for all kinds of meteorological and climatological data. In the MeteoSwiss Data Warehouse data and metadata are hold in a metadata driven relational database. To reach this goal, we started with the integration of the actual and historical data from our surface stations in a first step, including routines for aggregation and calculation and the implementation of enhanced Quality Control tools. In 2008 we started with the integration of actual and historical upper air data like soundings (PTU, Wind and Ozone), any kind of profilers like wind profiler or radiometer, profiles calculated from numerical weather models and AMDAR data in the Data Warehouse. The dataset includes also high resolution sounding data from the station Payerne and TEMP data from 20 European stations since 1942. A critical point was to work out a concept for the general architecture which could deal with all different types of data. While integrating the data itself all metadata of the aerological station Payerne was transferred and imported in the central metadata repository of the Data Warehouse. The implementation of the real time and daily QC tools as well as the routines for aggregation and calculation were realized in an analog way as for the surface data. The Quality Control tools include plausibility tests like limit tests, consistency tests in the same level and vertical consistency tests. From the beginning it was the aim to support the MeteoSwiss integration strategy which deals with all aspects of integration like various observing technologies and platforms, observing systems outside MeteoSwiss and the data and metadata itself. This kind of integration comprises all aspects of "Enterprise Data Integration". After the integration, the historical as well as the actual upper air data are now available for the climatologists and meteorologists with standardized access for data retrieving and visualization. We are convinced making these data accessible for the scientist is a good contribution to a better understanding of high resolution climatology.

PH5: HDF5 Based Format for Integrating and Archiving Seismic Data

NASA Astrophysics Data System (ADS)

Hess, D.; Azevedo, S.; Falco, N.; Beaudoin, B. C.

2017-12-01

PH5 is a seismic data format created by IRIS PASSCAL using HDF5. Building PH5 on HDF5 allows for portability and extensibility on a scale that is unavailable in older seismic data formats. PH5 is designed to evolve to accept new data types as they become available in the future and to operate on a variety of platforms (i.e. Mac, Linux, Windows). Exemplifying PH5's flexibility is the evolution from just handling active source seismic data to now including passive source, onshore-offshore, OBS and mixed source seismic data sets. In PH5, metadata is separated from the time series data and stored in a size and performance efficient manner that also allows for easy user interaction and output of the metadata in a format appropriate for the data set. PH5's full-fledged "Kitchen Software Suite" comprises tools for data ingestion (e.g. RefTek, SEG-Y, SEG-D, SEG-2, MSEED), meta-data management, QC, waveform viewing, and data output. This software suite not only includes command line and GUI tools for interacting with PH5, it is also a comprehensive Python package to support the creation of software tools by the community to further enhance PH5. The PH5 software suite is currently being used in multiple capacities, including in-field for creating archive ready data sets as well as by the IRIS Data Management Center (DMC) to offer an FDSN compliant set of web services for serving PH5 data to the community in a variety of standard data and meta-data formats (i.e. StationXML, QuakeML, EventXML, SAC + Poles and Zeroes, MiniSEED, and SEG-Y) as well as StationTXT and ShotText formats. These web services can be accessed via standard FDSN clients such as ObsPy, irisFetch.m, FetchData, and FetchMetadata. This presentation will highlight and demonstrate the benefits of PH5 as a next generation adaptable and extensible data format for use in both archiving and working with seismic data.

Air Quality uFIND: User-oriented Tool Set for Air Quality Data Discovery and Access

NASA Astrophysics Data System (ADS)

Hoijarvi, K.; Robinson, E. M.; Husar, R. B.; Falke, S. R.; Schultz, M. G.; Keating, T. J.

2012-12-01

Historically, there have been major impediments to seamless and effective data usage encountered by both data providers and users. Over the last five years, the international Air Quality (AQ) Community has worked through forums such as the Group on Earth Observations AQ Community of Practice, the ESIP AQ Working Group, and the Task Force on Hemispheric Transport of Air Pollution to converge on data format standards (e.g., netCDF), data access standards (e.g., Open Geospatial Consortium Web Coverage Services), metadata standards (e.g., ISO 19115), as well as other conventions (e.g., CF Naming Convention) in order to build an Air Quality Data Network. The centerpiece of the AQ Data Network is the web service-based tool set: user-oriented Filtering and Identification of Networked Data. The purpose of uFIND is to provide rich and powerful facilities for the user to: a) discover and choose a desired dataset by navigation through the multi-dimensional metadata space using faceted search, b) seamlessly access and browse datasets, and c) use uFINDs facilities as a web service for mashups with other AQ applications and portals. In a user-centric information system such as uFIND, the user experience is improved by metadata that includes the general fields for discovery as well as community-specific metadata to narrow the search beyond space, time and generic keyword searches. However, even with the community-specific additions, the ISO 19115 records were formed in compliance with the standard, so that other standards-based search interface could leverage this additional information. To identify the fields necessary for metadata discovery we started with the ISO 19115 Core Metadata fields and fields that were needed for a Catalog Service for the Web (CSW) Record. This fulfilled two goals - one to create valid ISO 19115 records and the other to be able to retrieve the records through a Catalog Service for the Web query. Beyond the required set of fields, the AQ Community added additional fields using a combination of keywords and ISO 19115 fields. These extensions allow discovery by measurement platform or observed phenomena. Beyond discovery metadata, the AQ records include service identification objects that allow standards-based clients, such as some brokers, to access the data found via OGC WCS or WMS data access protocols. uFIND, is one such smart client, this combination of discovery and access metadata allows the user to preview each registered dataset through spatial and temporal views; observe the data access and usage pattern and also find links to dataset-specific metadata directly in uFIND. The AQ data providers also benefit from this architecture since their data products are easier to find and re-use, enhancing the relevance and importance of their products. Finally, the earth science community at large benefits from the Service Oriented Architecture of uFIND, since it is a service itself and allows service-based interfacing with providers and users of the metadata, allowing uFIND facets to be further refined for a particular AQ application or completely repurposed for other Earth Science domains that use the same set of data access and metadata standards.

Pathogen metadata platform: software for accessing and analyzing pathogen strain information.

PubMed

Chang, Wenling E; Peterson, Matthew W; Garay, Christopher D; Korves, Tonia

2016-09-15

Pathogen metadata includes information about where and when a pathogen was collected and the type of environment it came from. Along with genomic nucleotide sequence data, this metadata is growing rapidly and becoming a valuable resource not only for research but for biosurveillance and public health. However, current freely available tools for analyzing this data are geared towards bioinformaticians and/or do not provide summaries and visualizations needed to readily interpret results. We designed a platform to easily access and summarize data about pathogen samples. The software includes a PostgreSQL database that captures metadata useful for disease outbreak investigations, and scripts for downloading and parsing data from NCBI BioSample and BioProject into the database. The software provides a user interface to query metadata and obtain standardized results in an exportable, tab-delimited format. To visually summarize results, the user interface provides a 2D histogram for user-selected metadata types and mapping of geolocated entries. The software is built on the LabKey data platform, an open-source data management platform, which enables developers to add functionalities. We demonstrate the use of the software in querying for a pathogen serovar and for genome sequence identifiers. This software enables users to create a local database for pathogen metadata, populate it with data from NCBI, easily query the data, and obtain visual summaries. Some of the components, such as the database, are modular and can be incorporated into other data platforms. The source code is freely available for download at https://github.com/wchangmitre/bioattribution .

Earth Science Data Grid System

NASA Astrophysics Data System (ADS)

Chi, Y.; Yang, R.; Kafatos, M.

2004-05-01

The Earth Science Data Grid System (ESDGS) is a software system in support of earth science data storage and access. It is built upon the Storage Resource Broker (SRB) data grid technology. We have developed a complete data grid system consistent of SRB server providing users uniform access to diverse storage resources in a heterogeneous computing environment and metadata catalog server (MCAT) managing the metadata associated with data set, users, and resources. We also develop the earth science application metadata; geospatial, temporal, and content-based indexing; and some other tools. In this paper, we will describe software architecture and components of the data grid system, and use a practical example in support of storage and access of rainfall data from the Tropical Rainfall Measuring Mission (TRMM) to illustrate its functionality and features.

GeoViQua: quality-aware geospatial data discovery and evaluation

NASA Astrophysics Data System (ADS)

Bigagli, L.; Papeschi, F.; Mazzetti, P.; Nativi, S.

2012-04-01

GeoViQua (QUAlity aware VIsualization for the Global Earth Observation System of Systems) is a recently started FP7 project aiming at complementing the Global Earth Observation System of Systems (GEOSS) with rigorous data quality specifications and quality-aware capabilities, in order to improve reliability in scientific studies and policy decision-making. GeoViQua main scientific and technical objective is to enhance the GEOSS Common Infrastructure (GCI) providing the user community with innovative quality-aware search and evaluation tools, which will be integrated in the GEO-Portal, as well as made available to other end-user interfaces. To this end, GeoViQua will promote the extension of the current standard metadata for geographic information with accurate and expressive quality indicators, also contributing to the definition of a quality label (GEOLabel). GeoViQua proposed solutions will be assessed in several pilot case studies covering the whole Earth Observation chain, from remote sensing acquisition to data processing, to applications in the main GEOSS Societal Benefit Areas. This work presents the preliminary results of GeoViQua Work Package 4 "Enhanced geo-search tools" (WP4), started in January 2012. Its major anticipated technical innovations are search and evaluation tools that communicate and exploit data quality information from the GCI. In particular, GeoViQua will investigate a graphical search interface featuring a coherent and meaningful aggregation of statistics and metadata summaries (e.g. in the form of tables, charts), thus enabling end users to leverage quality constraints for data discovery and evaluation. Preparatory work on WP4 requirements indicated that users need the "best" data for their purpose, implying a high degree of subjectivity in judgment. This suggests that the GeoViQua system should exploit a combination of provider-generated metadata (objective indicators such as summary statistics), system-generated metadata (contextual/tracking information such as provenance of data and metadata), and user-generated metadata (informal user comments, usage information, rating, etc.). Moreover, metadata should include sufficiently complete access information, to allow rich data visualization and propagation. The following main enabling components are currently identified within WP4: - Quality-aware access services, e.g. a quality-aware extension of the OGC Sensor Observation Service (SOS-Q) specification, to support quality constraints for sensor data publishing and access; - Quality-aware discovery services, namely a quality-aware extension of the OGC Catalog Service for the Web (CSW-Q), to cope with quality constrained search; - Quality-augmentation broker (GeoViQua Broker), to support the linking and combination of the existing GCI metadata with GeoViQua- and user-generated metadata required to support the users in selecting the "best" data for their intended use. We are currently developing prototypes of the above quality-enabled geo-search components, that will be assessed in a sensor-based pilot case study in the next months. In particular, the GeoViQua Broker will be integrated with the EuroGEOSS Broker, to implement CSW-Q and federate (either via distribution or harvesting schemes) quality-aware data sources, GeoViQua will constitute a valuable test-bed for advancing the current best practices and standards in geospatial quality representation and exploitation. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement n° 265178.

NetCDF4/HDF5 and Linked Data in the Real World - Enriching Geoscientific Metadata without Bloat

NASA Astrophysics Data System (ADS)

Ip, Alex; Car, Nicholas; Druken, Kelsey; Poudjom-Djomani, Yvette; Butcher, Stirling; Evans, Ben; Wyborn, Lesley

2017-04-01

NetCDF4 has become the dominant generic format for many forms of geoscientific data, leveraging (and constraining) the versatile HDF5 container format, while providing metadata conventions for interoperability. However, the encapsulation of detailed metadata within each file can lead to metadata "bloat", and difficulty in maintaining consistency where metadata is replicated to multiple locations. Complex conceptual relationships are also difficult to represent in simple key-value netCDF metadata. Linked Data provides a practical mechanism to address these issues by associating the netCDF files and their internal variables with complex metadata stored in Semantic Web vocabularies and ontologies, while complying with and complementing existing metadata conventions. One of the stated objectives of the netCDF4/HDF5 formats is that they should be self-describing: containing metadata sufficient for cataloguing and using the data. However, this objective can be regarded as only partially-met where details of conventions and definitions are maintained externally to the data files. For example, one of the most widely used netCDF community standards, the Climate and Forecasting (CF) Metadata Convention, maintains standard vocabularies for a broad range of disciplines across the geosciences, but this metadata is currently neither readily discoverable nor machine-readable. We have previously implemented useful Linked Data and netCDF tooling (ncskos) that associates netCDF files, and individual variables within those files, with concepts in vocabularies formulated using the Simple Knowledge Organization System (SKOS) ontology. NetCDF files contain Uniform Resource Identifier (URI) links to terms represented as SKOS Concepts, rather than plain-text representations of those terms, so we can use simple, standardised web queries to collect and use rich metadata for the terms from any Linked Data-presented SKOS vocabulary. Geoscience Australia (GA) manages a large volume of diverse geoscientific data, much of which is being translated from proprietary formats to netCDF at NCI Australia. This data is made available through the NCI National Environmental Research Data Interoperability Platform (NERDIP) for programmatic access and interdisciplinary analysis. The netCDF files contain both scientific data variables (e.g. gravity, magnetic or radiometric values), but also domain-specific operational values (e.g. specific instrument parameters) best described fully in formal vocabularies. Our ncskos codebase provides access to multiple stores of detailed external metadata in a standardised fashion. Geophysical datasets are generated from a "survey" event, and GA maintains corporate databases of all surveys and their associated metadata. It is impractical to replicate the full source survey metadata into each netCDF dataset so, instead, we link the netCDF files to survey metadata using public Linked Data URIs. These URIs link to Survey class objects which we model as a subclass of Activity objects as defined by the PROV Ontology, and we provide URI resolution for them via a custom Linked Data API which draws current survey metadata from GA's in-house databases. We have demonstrated that Linked Data is a practical way to associate netCDF data with detailed, external metadata. This allows us to ensure that catalogued metadata is kept consistent with metadata points-of-truth, and we can infer complex conceptual relationships not possible with netCDF key-value attributes alone.

May We Help You Find Something? AskNSDL!

ERIC Educational Resources Information Center

Silverstein, Joanne

2003-01-01

Explains the digital reference service AskNSDL that was developed for the National Science Digital Library (NSDL). Discusses tools used to design the service, including QABuilder software; QuIP (Question Interchange Profile) metadata format standard; GEM (Gateway to Educational Materials) cataloging tool; and the AskERIC question and answer…

Semantic-Aware Components and Services of ActiveMath

ERIC Educational Resources Information Center

Melis, Erica; Goguadze, Giorgi; Homik, Martin; Libbrecht, Paul; Ullrich, Carsten; Winterstein, Stefan

2006-01-01

ActiveMath is a complex web-based adaptive learning environment with a number of components and interactive learning tools. The basis for handling semantics of learning content is provided by its semantic (mathematics) content markup, which is additionally annotated with educational metadata. Several components, tools and external services can…

MaNIDA: Integration of marine expedition information, data and publications: Data Portal of German Marine Research

NASA Astrophysics Data System (ADS)

Koppe, Roland; Scientific MaNIDA-Team

2013-04-01

The Marine Network for Integrated Data Access (MaNIDA) aims to build a sustainable e-infrastructure to support discovery and re-use of marine data from distinct data providers in Germany (see related abstracts in session ESSI 1.2). In order to provide users integrated access and retrieval of expedition or cruise metadata, data, services and publications as well as relationships among the various objects, we are developing (web) applications based on state of the art technologies: the Data Portal of German Marine Research. Since the German network of distributed content providers have distinct objectives and mandates for storing digital objects (e.g. long-term data preservation, near real time data, publication repositories), we have to cope with heterogeneous metadata in terms of syntax and semantic, data types and formats as well as access solutions. We have defined a set of core metadata elements which are common to our content providers and therefore useful for discovery and building relationships among objects. Existing catalogues for various types of vocabularies are being used to assure the mapping to community-wide used terms. We distinguish between expedition metadata and continuously harvestable metadata objects from distinct data providers. • Existing expedition metadata from distinct sources is integrated and validated in order to create an expedition metadata catalogue which is used as authoritative source for expedition-related content. The web application allows browsing by e.g. research vessel and date, exploring expeditions and research gaps by tracklines and viewing expedition details (begin/end, ports, platforms, chief scientists, events, etc.). Also expedition-related objects from harvesting are dynamically associated with expedition information and presented to the user. Hence we will provide web services to detailed expedition information. • Other harvestable content is separated into four categories: archived data and data products, near real time data, publications and reports. Reports are a special case of publication, describing cruise planning, cruise reports or popular reports on expeditions and are orthogonal to e.g. peer-reviewed articles. Each object's metadata contains at least: identifier(s) e.g. doi/hdl, title, author(s), date, expedition(s), platform(s) e.g. research vessel Polarstern. Furthermore project(s), parameter(s), device(s) and e.g. geographic coverage are of interest. An international gazetteer resolves geographic coverage to region names and annotates to object metadata. Information is homogenously presented to the user, independent of the underlying format, but adaptable to specific disciplines e.g. bathymetry. Also data access and dissemination information is available to the user as data download link or web services (e.g. WFS, WMS). Based on relationship metadata we are dynamically building graphs of objects to support the user in finding possible relevant associated objects. Technically metadata is based on ISO / OGC standards or provider specification. Metadata is harvested via OAI-PMH or OGC CSW and indexed with Apache Lucene. This enables powerful full-text search, geographic and temporal search as well as faceting. In this presentation we will illustrate the architecture and the current implementation of our integrated approach.

A Python object-oriented framework for the CMS alignment and calibration data

NASA Astrophysics Data System (ADS)

Dawes, Joshua H.; CMS Collaboration

2017-10-01

The Alignment, Calibrations and Databases group at the CMS Experiment delivers Alignment and Calibration Conditions Data to a large set of workflows which process recorded event data and produce simulated events. The current infrastructure for releasing and consuming Conditions Data was designed in the two years of the first LHC long shutdown to respond to use cases from the preceding data-taking period. During the second run of the LHC, new use cases were defined. For the consumption of Conditions Metadata, no common interface existed for the detector experts to use in Python-based custom scripts, resulting in many different querying and transaction management patterns. A new framework has been built to address such use cases: a simple object-oriented tool that detector experts can use to read and write Conditions Metadata when using Oracle and SQLite databases, that provides a homogeneous method of querying across all services. The tool provides mechanisms for segmenting large sets of conditions while releasing them to the production database, allows for uniform error reporting to the client-side from the server-side and optimizes the data transfer to the server. The architecture of the new service has been developed exploiting many of the features made available by the metadata consumption framework to implement the required improvements. This paper presents the details of the design and implementation of the new metadata consumption and data upload framework, as well as analyses of the new upload service’s performance as the server-side state varies.

Correcting Inconsistencies and Errors in Bacterial Genome Metadata Using an Automated Curation Tool in Excel (AutoCurE).

PubMed

Schmedes, Sarah E; King, Jonathan L; Budowle, Bruce

2015-01-01

Whole-genome data are invaluable for large-scale comparative genomic studies. Current sequencing technologies have made it feasible to sequence entire bacterial genomes with relative ease and time with a substantially reduced cost per nucleotide, hence cost per genome. More than 3,000 bacterial genomes have been sequenced and are available at the finished status. Publically available genomes can be readily downloaded; however, there are challenges to verify the specific supporting data contained within the download and to identify errors and inconsistencies that may be present within the organizational data content and metadata. AutoCurE, an automated tool for bacterial genome database curation in Excel, was developed to facilitate local database curation of supporting data that accompany downloaded genomes from the National Center for Biotechnology Information. AutoCurE provides an automated approach to curate local genomic databases by flagging inconsistencies or errors by comparing the downloaded supporting data to the genome reports to verify genome name, RefSeq accession numbers, the presence of archaea, BioProject/UIDs, and sequence file descriptions. Flags are generated for nine metadata fields if there are inconsistencies between the downloaded genomes and genomes reports and if erroneous or missing data are evident. AutoCurE is an easy-to-use tool for local database curation for large-scale genome data prior to downstream analyses.

Observatory Bibliographies as Research Tools

NASA Astrophysics Data System (ADS)

Rots, Arnold H.; Winkelman, S. L.

2013-01-01

Traditionally, observatory bibliographies were maintained to provide insight in how successful a observatory is as measured by its prominence in the (refereed) literature. When we set up the bibliographic database for the Chandra X-ray Observatory (http://cxc.harvard.edu/cgi-gen/cda/bibliography) as part of the Chandra Data Archive ((http://cxc.harvard.edu/cda/), very early in the mission, our objective was to make it primarily a useful tool for our user community. To achieve this we are: (1) casting a very wide net in collecting Chandra-related publications; (2) including for each literature reference in the database a wealth of metadata that is useful for the users; and (3) providing specific links between the articles and the datasets in the archive that they use. As a result our users are able to browse the literature and the data archive simultaneously. As an added bonus, the rich metadata content and data links have also allowed us to assemble more meaningful statistics about the scientific efficacy of the observatory. In all this we collaborate closely with the Astrophysics Data System (ADS). Among the plans for future enhancement are the inclusion of press releases and the Chandra image gallery, linking with ADS semantic searching tools, full-text metadata mining, and linking with other observatories' bibliographies. This work is supported by NASA contract NAS8-03060 (CXC) and depends critically on the services provided by the ADS.

The Planetary Data System (PDS) Data Dictionary Tool (LDDTool)

NASA Astrophysics Data System (ADS)

Raugh, Anne C.; Hughes, John S.

2017-10-01

One of the major design goals of the PDS4 development effort was to provide an avenue for discipline specialists and large data preparers such as mission archivists to extend the core PDS4 Information Model (IM) to include metadata definitions specific to their own contexts. This capability is critical for the Planetary Data System - an archive that deals with a data collection that is diverse along virtually every conceivable axis. Amid such diversity, it is in the best interests of the PDS archive and its users that all extensions to the core IM follow the same design techniques, conventions, and restrictions as the core implementation itself. Notwithstanding, expecting all mission and discipline archivist seeking to define metadata for a new context to acquire expertise in information modeling, model-driven design, ontology, schema formulation, and PDS4 design conventions and philosophy is unrealistic, to say the least.To bridge that expertise gap, the PDS Engineering Node has developed the data dictionary creation tool known as “LDDTool”. This tool incorporates the same software used to maintain and extend the core IM, packaged with an interface that enables a developer to create his contextual information model using the same, open standards-based metadata framework PDS itself uses. Through this interface, the novice dictionary developer has immediate access to the common set of data types and unit classes for defining attributes, and a straight-forward method for constructing classes. The more experienced developer, using the same tool, has access to more sophisticated modeling methods like abstraction and extension, and can define very sophisticated validation rules.We present the key features of the PDS Local Data Dictionary Tool, which both supports the development of extensions to the PDS4 IM, and ensures their compatibility with the IM.

Planetary Sciences Literature - Access and Discovery

NASA Astrophysics Data System (ADS)

Henneken, Edwin A.; ADS Team

2017-10-01

The NASA Astrophysics Data System (ADS) has been around for over 2 decades, helping professional astronomers and planetary scientists navigate, without charge, through the increasingly complex environment of scholarly publications. As boundaries between disciplines dissolve and expand, the ADS provides powerful tools to help researchers discover useful information efficiently. In its new form, code-named ADS Bumblebee (https://ui.adsabs.harvard.edu), it may very well answer questions you didn't know you had! While the classic ADS (http://ads.harvard.edu) focuses mostly on searching basic metadata (author, title and abstract), today's ADS is best described as a an "aggregator" of scholarly resources relevant to the needs of researchers in astronomy and planetary sciences, and providing a discovery environment on top of this. In addition to indexing content from a variety of publishers, data and software archives, the ADS enriches its records by text-mining and indexing the full-text articles (about 4.7 million in total, with 130,000 from planetary science journals), enriching its metadata through the extraction of citations and acknowledgments. Recent technology developments include a new Application Programming Interface (API), a new user interface featuring a variety of visualizations and bibliometric analysis, and integration with ORCID services to support paper claiming. The new ADS provides powerful tools to help you find review papers on a given subject, prolific authors working on a subject and who they are collaborating with (within and outside their group) and papers most read by by people who read recent papers on the topic of your interest. These are just a couple of examples of the capabilities of the new ADS. We currently index most journals covering the planetary sciences and we are striving to include those journals most frequently cited by planetary science publications. The ADS is operated by the Smithsonian Astrophysical Observatory under NASA Cooperative Agreement NNX16AC86A.

NeuroTransDB: highly curated and structured transcriptomic metadata for neurodegenerative diseases.

PubMed

Bagewadi, Shweta; Adhikari, Subash; Dhrangadhariya, Anjani; Irin, Afroza Khanam; Ebeling, Christian; Namasivayam, Aishwarya Alex; Page, Matthew; Hofmann-Apitius, Martin; Senger, Philipp

2015-01-01

Neurodegenerative diseases are chronic debilitating conditions, characterized by progressive loss of neurons that represent a significant health care burden as the global elderly population continues to grow. Over the past decade, high-throughput technologies such as the Affymetrix GeneChip microarrays have provided new perspectives into the pathomechanisms underlying neurodegeneration. Public transcriptomic data repositories, namely Gene Expression Omnibus and curated ArrayExpress, enable researchers to conduct integrative meta-analysis; increasing the power to detect differentially regulated genes in disease and explore patterns of gene dysregulation across biologically related studies. The reliability of retrospective, large-scale integrative analyses depends on an appropriate combination of related datasets, in turn requiring detailed meta-annotations capturing the experimental setup. In most cases, we observe huge variation in compliance to defined standards for submitted metadata in public databases. Much of the information to complete, or refine meta-annotations are distributed in the associated publications. For example, tissue preparation or comorbidity information is frequently described in an article's supplementary tables. Several value-added databases have employed additional manual efforts to overcome this limitation. However, none of these databases explicate annotations that distinguish human and animal models in neurodegeneration context. Therefore, adopting a more specific disease focus, in combination with dedicated disease ontologies, will better empower the selection of comparable studies with refined annotations to address the research question at hand. In this article, we describe the detailed development of NeuroTransDB, a manually curated database containing metadata annotations for neurodegenerative studies. The database contains more than 20 dimensions of metadata annotations within 31 mouse, 5 rat and 45 human studies, defined in collaboration with domain disease experts. We elucidate the step-by-step guidelines used to critically prioritize studies from public archives and their metadata curation and discuss the key challenges encountered. Curated metadata for Alzheimer's disease gene expression studies are available for download. Database URL: www.scai.fraunhofer.de/NeuroTransDB.html. © The Author(s) 2015. Published by Oxford University Press.

The Energy Industry Profile of ISO/DIS 19115-1: Facilitating Discovery and Evaluation of, and Access to Distributed Information Resources

NASA Astrophysics Data System (ADS)

Hills, S. J.; Richard, S. M.; Doniger, A.; Danko, D. M.; Derenthal, L.; Energistics Metadata Work Group

2011-12-01

A diverse group of organizations representative of the international community involved in disciplines relevant to the upstream petroleum industry, - energy companies, - suppliers and publishers of information to the energy industry, - vendors of software applications used by the industry, - partner government and academic organizations, has engaged in the Energy Industry Metadata Standards Initiative. This Initiative envisions the use of standard metadata within the community to enable significant improvements in the efficiency with which users discover, evaluate, and access distributed information resources. The metadata standard needed to realize this vision is the initiative's primary deliverable. In addition to developing the metadata standard, the initiative is promoting its adoption to accelerate realization of the vision, and publishing metadata exemplars conformant with the standard. Implementation of the standard by community members, in the form of published metadata which document the information resources each organization manages, will allow use of tools requiring consistent metadata for efficient discovery and evaluation of, and access to, information resources. While metadata are expected to be widely accessible, access to associated information resources may be more constrained. The initiative is being conducting by Energistics' Metadata Work Group, in collaboration with the USGIN Project. Energistics is a global standards group in the oil and natural gas industry. The Work Group determined early in the initiative, based on input solicited from 40+ organizations and on an assessment of existing metadata standards, to develop the target metadata standard as a profile of a revised version of ISO 19115, formally the "Energy Industry Profile of ISO/DIS 19115-1 v1.0" (EIP). The Work Group is participating on the ISO/TC 211 project team responsible for the revision of ISO 19115, now ready for "Draft International Standard" (DIS) status. With ISO 19115 an established, capability-rich, open standard for geographic metadata, EIP v1 is expected to be widely acceptable within the community and readily sustainable over the long-term. The EIP design, also per community requirements, will enable discovery, evaluation, and access to types of information resources considered important to the community, including structured and unstructured digital resources, and physical assets such as hardcopy documents and material samples. This presentation will briefly review the development of this initiative as well as the current and planned Work Group activities. More time will be spent providing an overview of the EIP v1, including the requirements it prescribes, design efforts made to enable automated metadata capture and processing, and the structure and content of its documentation, which was written to minimize ambiguity and facilitate implementation. The Work Group considers EIP v1 a solid initial design for interoperable metadata, and first step toward the vision of the Initiative.

Publishing datasets with eSciDoc and panMetaDocs

NASA Astrophysics Data System (ADS)

Ulbricht, D.; Klump, J.; Bertelmann, R.

2012-04-01

Currently serveral research institutions worldwide undertake considerable efforts to have their scientific datasets published and to syndicate them to data portals as extensively described objects identified by a persistent identifier. This is done to foster the reuse of data, to make scientific work more transparent, and to create a citable entity that can be referenced unambigously in written publications. GFZ Potsdam established a publishing workflow for file based research datasets. Key software components are an eSciDoc infrastructure [1] and multiple instances of the data curation tool panMetaDocs [2]. The eSciDoc repository holds data objects and their associated metadata in container objects, called eSciDoc items. A key metadata element in this context is the publication status of the referenced data set. PanMetaDocs, which is based on PanMetaWorks [3], is a PHP based web application that allows to describe data with any XML-based metadata schema. The metadata fields can be filled with static or dynamic content to reduce the number of fields that require manual entries to a minimum and make use of contextual information in a project setting. Access rights can be applied to set visibility of datasets to other project members and allow collaboration on and notifying about datasets (RSS) and interaction with the internal messaging system, that was inherited from panMetaWorks. When a dataset is to be published, panMetaDocs allows to change the publication status of the eSciDoc item from status "private" to "submitted" and prepare the dataset for verification by an external reviewer. After quality checks, the item publication status can be changed to "published". This makes the data and metadata available through the internet worldwide. PanMetaDocs is developed as an eSciDoc application. It is an easy to use graphical user interface to eSciDoc items, their data and metadata. It is also an application supporting a DOI publication agent during the process of publishing scientific datasets as electronic data supplements to research papers. Publication of research manuscripts has an already well established workflow that shares junctures with other processes and involves several parties in the process of dataset publication. Activities of the author, the reviewer, the print publisher and the data publisher have to be coordinated into a common data publication workflow. The case of data publication at GFZ Potsdam displays some specifics, e.g. the DOIDB webservice. The DOIDB is a proxy service at GFZ for the DataCite [4] DOI registration and its metadata store. DOIDB provides a local summary of the dataset DOIs registered through GFZ as a publication agent. An additional use case for the DOIDB is its function to enrich the datacite metadata with additional custom attributes, like a geographic reference in a DIF record. These attributes are at the moment not available in the datacite metadata schema but would be valuable elements for the compilation of data catalogues in the earth sciences and for dissemination of catalogue data via OAI-PMH. [1] http://www.escidoc.org , eSciDoc, FIZ Karlruhe, Germany [2] http://panmetadocs.sf.net , panMetaDocs, GFZ Potsdam, Germany [3] http://metaworks.pangaea.de , panMetaWorks, Dr. R. Huber, MARUM, Univ. Bremen, Germany [4] http://www.datacite.org

Echo™ User Manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harvey, Dustin Yewell

Echo™ is a MATLAB-based software package designed for robust and scalable analysis of complex data workflows. An alternative to tedious, error-prone conventional processes, Echo is based on three transformative principles for data analysis: self-describing data, name-based indexing, and dynamic resource allocation. The software takes an object-oriented approach to data analysis, intimately connecting measurement data with associated metadata. Echo operations in an analysis workflow automatically track and merge metadata and computation parameters to provide a complete history of the process used to generate final results, while automated figure and report generation tools eliminate the potential to mislabel those results. History reportingmore » and visualization methods provide straightforward auditability of analysis processes. Furthermore, name-based indexing on metadata greatly improves code readability for analyst collaboration and reduces opportunities for errors to occur. Echo efficiently manages large data sets using a framework that seamlessly allocates resources such that only the necessary computations to produce a given result are executed. Echo provides a versatile and extensible framework, allowing advanced users to add their own tools and data classes tailored to their own specific needs. Applying these transformative principles and powerful features, Echo greatly improves analyst efficiency and quality of results in many application areas.« less

MMI's Metadata and Vocabulary Solutions: 10 Years and Growing

NASA Astrophysics Data System (ADS)

Graybeal, J.; Gayanilo, F.; Rueda-Velasquez, C. A.

2014-12-01

The Marine Metadata Interoperability project (http://marinemetadata.org) held its public opening at AGU's 2004 Fall Meeting. For 10 years since that debut, the MMI guidance and vocabulary sites have served over 100,000 visitors, with 525 community members and continuous Steering Committee leadership. Originally funded by the National Science Foundation, over the years multiple organizations have supported the MMI mission: "Our goal is to support collaborative research in the marine science domain, by simplifying the incredibly complex world of metadata into specific, straightforward guidance. MMI encourages scientists and data managers at all levels to apply good metadata practices from the start of a project, by providing the best guidance and resources for data management, and developing advanced metadata tools and services needed by the community." Now hosted by the Harte Research Institute at Texas A&M University at Corpus Christi, MMI continues to provide guidance and services to the community, and is planning for marine science and technology needs for the next 10 years. In this presentation we will highlight our major accomplishments, describe our recent achievements and imminent goals, and propose a vision for improving marine data interoperability for the next 10 years, including Ontology Registry and Repository (http://mmisw.org/orr) advancements and applications (http://mmisw.org/cfsn).

The ground truth about metadata and community detection in networks.

PubMed

Peel, Leto; Larremore, Daniel B; Clauset, Aaron

2017-05-01

Across many scientific domains, there is a common need to automatically extract a simplified view or coarse-graining of how a complex system's components interact. This general task is called community detection in networks and is analogous to searching for clusters in independent vector data. It is common to evaluate the performance of community detection algorithms by their ability to find so-called ground truth communities. This works well in synthetic networks with planted communities because these networks' links are formed explicitly based on those known communities. However, there are no planted communities in real-world networks. Instead, it is standard practice to treat some observed discrete-valued node attributes, or metadata, as ground truth. We show that metadata are not the same as ground truth and that treating them as such induces severe theoretical and practical problems. We prove that no algorithm can uniquely solve community detection, and we prove a general No Free Lunch theorem for community detection, which implies that there can be no algorithm that is optimal for all possible community detection tasks. However, community detection remains a powerful tool and node metadata still have value, so a careful exploration of their relationship with network structure can yield insights of genuine worth. We illustrate this point by introducing two statistical techniques that can quantify the relationship between metadata and community structure for a broad class of models. We demonstrate these techniques using both synthetic and real-world networks, and for multiple types of metadata and community structures.

PH5 for integrating and archiving different data types

NASA Astrophysics Data System (ADS)

Azevedo, Steve; Hess, Derick; Beaudoin, Bruce

2016-04-01

PH5 is IRIS PASSCAL's file organization of HDF5 used for seismic data. The extensibility and portability of HDF5 allows the PH5 format to evolve and operate on a variety of platforms and interfaces. To make PH5 even more flexible, the seismic metadata is separated from the time series data in order to achieve gains in performance as well as ease of use and to simplify user interaction. This separation affords easy updates to metadata after the data are archived without having to access waveform data. To date, PH5 is currently used for integrating and archiving active source, passive source, and onshore-offshore seismic data sets with the IRIS Data Management Center (DMC). Active development to make PH5 fully compatible with FDSN web services and deliver StationXML is near completion. We are also exploring the feasibility of utilizing QuakeML for active seismic source representation. The PH5 software suite, PIC KITCHEN, comprises in-field tools that include data ingestion (e.g. RefTek format, SEG-Y, and SEG-D), meta-data management tools including QC, and a waveform review tool. These tools enable building archive ready data in-field during active source experiments greatly decreasing the time to produce research ready data sets. Once archived, our online request page generates a unique web form and pre-populates much of it based on the metadata provided to it from the PH5 file. The data requester then can intuitively select the extraction parameters as well as data subsets they wish to receive (current output formats include SEG-Y, SAC, mseed). The web interface then passes this on to the PH5 processing tools to generate the requested seismic data, and e-mail the requester a link to the data set automatically as soon as the data are ready. PH5 file organization was originally designed to hold seismic time series data and meta-data from controlled source experiments using RefTek data loggers. The flexibility of HDF5 has enabled us to extend the use of PH5 in several areas one of which is using PH5 to handle very large data sets. PH5 is also good at integrating data from various types of seismic experiments such as OBS, onshore-offshore, controlled source, and passive recording. HDF5 is capable of holding practically any type of digital data so integrating GPS data with seismic data is possible. Since PH5 is a common format and data contained in HDF5 is accessible randomly it has been easy to extend to include new input and output data formats as community needs arise.

The Metadata Coverage Index (MCI): A standardized metric for quantifying database metadata richness.

PubMed

Liolios, Konstantinos; Schriml, Lynn; Hirschman, Lynette; Pagani, Ioanna; Nosrat, Bahador; Sterk, Peter; White, Owen; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Taylor, Chris; Kyrpides, Nikos C; Field, Dawn

2012-07-30

Variability in the extent of the descriptions of data ('metadata') held in public repositories forces users to assess the quality of records individually, which rapidly becomes impractical. The scoring of records on the richness of their description provides a simple, objective proxy measure for quality that enables filtering that supports downstream analysis. Pivotally, such descriptions should spur on improvements. Here, we introduce such a measure - the 'Metadata Coverage Index' (MCI): the percentage of available fields actually filled in a record or description. MCI scores can be calculated across a database, for individual records or for their component parts (e.g., fields of interest). There are many potential uses for this simple metric: for example; to filter, rank or search for records; to assess the metadata availability of an ad hoc collection; to determine the frequency with which fields in a particular record type are filled, especially with respect to standards compliance; to assess the utility of specific tools and resources, and of data capture practice more generally; to prioritize records for further curation; to serve as performance metrics of funded projects; or to quantify the value added by curation. Here we demonstrate the utility of MCI scores using metadata from the Genomes Online Database (GOLD), including records compliant with the 'Minimum Information about a Genome Sequence' (MIGS) standard developed by the Genomic Standards Consortium. We discuss challenges and address the further application of MCI scores; to show improvements in annotation quality over time, to inform the work of standards bodies and repository providers on the usability and popularity of their products, and to assess and credit the work of curators. Such an index provides a step towards putting metadata capture practices and in the future, standards compliance, into a quantitative and objective framework.

maxdLoad2 and maxdBrowse: standards-compliant tools for microarray experimental annotation, data management and dissemination.

PubMed

Hancock, David; Wilson, Michael; Velarde, Giles; Morrison, Norman; Hayes, Andrew; Hulme, Helen; Wood, A Joseph; Nashar, Karim; Kell, Douglas B; Brass, Andy

2005-11-03

maxdLoad2 is a relational database schema and Java application for microarray experimental annotation and storage. It is compliant with all standards for microarray meta-data capture; including the specification of what data should be recorded, extensive use of standard ontologies and support for data exchange formats. The output from maxdLoad2 is of a form acceptable for submission to the ArrayExpress microarray repository at the European Bioinformatics Institute. maxdBrowse is a PHP web-application that makes contents of maxdLoad2 databases accessible via web-browser, the command-line and web-service environments. It thus acts as both a dissemination and data-mining tool. maxdLoad2 presents an easy-to-use interface to an underlying relational database and provides a full complement of facilities for browsing, searching and editing. There is a tree-based visualization of data connectivity and the ability to explore the links between any pair of data elements, irrespective of how many intermediate links lie between them. Its principle novel features are: the flexibility of the meta-data that can be captured, the tools provided for importing data from spreadsheets and other tabular representations, the tools provided for the automatic creation of structured documents, the ability to browse and access the data via web and web-services interfaces. Within maxdLoad2 it is very straightforward to customise the meta-data that is being captured or change the definitions of the meta-data. These meta-data definitions are stored within the database itself allowing client software to connect properly to a modified database without having to be specially configured. The meta-data definitions (configuration file) can also be centralized allowing changes made in response to revisions of standards or terminologies to be propagated to clients without user intervention.maxdBrowse is hosted on a web-server and presents multiple interfaces to the contents of maxd databases. maxdBrowse emulates many of the browse and search features available in the maxdLoad2 application via a web-browser. This allows users who are not familiar with maxdLoad2 to browse and export microarray data from the database for their own analysis. The same browse and search features are also available via command-line and SOAP server interfaces. This both enables scripting of data export for use embedded in data repositories and analysis environments, and allows access to the maxd databases via web-service architectures. maxdLoad2 http://www.bioinf.man.ac.uk/microarray/maxd/ and maxdBrowse http://dbk.ch.umist.ac.uk/maxdBrowse are portable and compatible with all common operating systems and major database servers. They provide a powerful, flexible package for annotation of microarray experiments and a convenient dissemination environment. They are available for download and open sourced under the Artistic License.

User needs analysis and usability assessment of DataMed - a biomedical data discovery index.

PubMed

Dixit, Ram; Rogith, Deevakar; Narayana, Vidya; Salimi, Mandana; Gururaj, Anupama; Ohno-Machado, Lucila; Xu, Hua; Johnson, Todd R

2017-11-30

To present user needs and usability evaluations of DataMed, a Data Discovery Index (DDI) that allows searching for biomedical data from multiple sources. We conducted 2 phases of user studies. Phase 1 was a user needs analysis conducted before the development of DataMed, consisting of interviews with researchers. Phase 2 involved iterative usability evaluations of DataMed prototypes. We analyzed data qualitatively to document researchers' information and user interface needs. Biomedical researchers' information needs in data discovery are complex, multidimensional, and shaped by their context, domain knowledge, and technical experience. User needs analyses validate the need for a DDI, while usability evaluations of DataMed show that even though aggregating metadata into a common search engine and applying traditional information retrieval tools are promising first steps, there remain challenges for DataMed due to incomplete metadata and the complexity of data discovery. Biomedical data poses distinct problems for search when compared to websites or publications. Making data available is not enough to facilitate biomedical data discovery: new retrieval techniques and user interfaces are necessary for dataset exploration. Consistent, complete, and high-quality metadata are vital to enable this process. While available data and researchers' information needs are complex and heterogeneous, a successful DDI must meet those needs and fit into the processes of biomedical researchers. Research directions include formalizing researchers' information needs, standardizing overviews of data to facilitate relevance judgments, implementing user interfaces for concept-based searching, and developing evaluation methods for open-ended discovery systems such as DDIs. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

The NSF Arctic Data Center: Leveraging the DataONE Federation to Build a Sustainable Archive for the NSF Arctic Research Community

NASA Astrophysics Data System (ADS)

Budden, A. E.; Arzayus, K. M.; Baker-Yeboah, S.; Casey, K. S.; Dozier, J.; Jones, C. S.; Jones, M. B.; Schildhauer, M.; Walker, L.

2016-12-01

The newly established NSF Arctic Data Center plays a critical support role in archiving and curating the data and software generated by Arctic researchers from diverse disciplines. The Arctic community, comprising Earth science, archaeology, geography, anthropology, and other social science researchers, are supported through data curation services and domain agnostic tools and infrastructure, ensuring data are accessible in the most transparent and usable way possible. This interoperability across diverse disciplines within the Arctic community facilitates collaborative research and is mirrored by interoperability between the Arctic Data Center infrastructure and other large scale cyberinfrastructure initiatives. The Arctic Data Center leverages the DataONE federation to standardize access to and replication of data and metadata to other repositories, specifically the NOAA's National Centers for Environmental Information (NCEI). This approach promotes long-term preservation of the data and metadata, as well as opening the door for other data repositories to leverage this replication infrastructure with NCEI and other DataONE member repositories. The Arctic Data Center uses rich, detailed metadata following widely recognized standards. Particularly, measurement-level and provenance metadata provide scientists the details necessary to integrate datasets across studies and across repositories while enabling a full understanding of the provenance of data used in the system. The Arctic Data Center gains this deep metadata and provenance support by simply adopting DataONE services, which results in significant efficiency gains by eliminating the need to develop systems de novo. Similarly, the advanced search tool developed by the Knowledge Network for Biocomplexity and extended for data submission by the Arctic Data Center, can be used by other DataONE-compliant repositories without further development. By standardizing interfaces and leveraging the DataONE federation, the Arctic Data Center has advanced rapidly and can itself contribute to raising the capabilities of all members of the federation.

Discovery of Marine Datasets and Geospatial Metadata Visualization

NASA Astrophysics Data System (ADS)

Schwehr, K. D.; Brennan, R. T.; Sellars, J.; Smith, S.

2009-12-01

NOAA's National Geophysical Data Center (NGDC) provides the deep archive of US multibeam sonar hydrographic surveys. NOAA stores the data as Bathymetric Attributed Grids (BAG; http://www.opennavsurf.org/) that are HDF5 formatted files containing gridded bathymetry, gridded uncertainty, and XML metadata. While NGDC provides the deep store and a basic ERSI ArcIMS interface to the data, additional tools need to be created to increase the frequency with which researchers discover hydrographic surveys that might be beneficial for their research. Using Open Source tools, we have created a draft of a Google Earth visualization of NOAA's complete collection of BAG files as of March 2009. Each survey is represented as a bounding box, an optional preview image of the survey data, and a pop up placemark. The placemark contains a brief summary of the metadata and links to directly download of the BAG survey files and the complete metadata file. Each survey is time tagged so that users can search both in space and time for surveys that meet their needs. By creating this visualization, we aim to make the entire process of data discovery, validation of relevance, and download much more efficient for research scientists who may not be familiar with NOAA's hydrographic survey efforts or the BAG format. In the process of creating this demonstration, we have identified a number of improvements that can be made to the hydrographic survey process in order to make the results easier to use especially with respect to metadata generation. With the combination of the NGDC deep archiving infrastructure, a Google Earth virtual globe visualization, and GeoRSS feeds of updates, we hope to increase the utilization of these high-quality gridded bathymetry. This workflow applies equally well to LIDAR topography and bathymetry. Additionally, with proper referencing and geotagging in journal publications, we hope to close the loop and help the community create a true “Geospatial Scholar” infrastructure.

Report on the Global Data Assembly Center (GDAC) to the 12th GHRSST Science Team Meeting

NASA Technical Reports Server (NTRS)

Armstrong, Edward M.; Bingham, Andrew; Vazquez, Jorge; Thompson, Charles; Huang, Thomas; Finch, Chris

2011-01-01

In 2010/2011 the Global Data Assembly Center (GDAC) at NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) continued its role as the primary clearinghouse and access node for operational Group for High Resolution Sea Surface Temperature (GHRSST) datastreams, as well as its collaborative role with the NOAA Long Term Stewardship and Reanalysis Facility (LTSRF) for archiving. Here we report on our data management activities and infrastructure improvements since the last science team meeting in June 2010.These include the implementation of all GHRSST datastreams in the new PO.DAAC Data Management and Archive System (DMAS) for more reliable and timely data access. GHRSST dataset metadata are now stored in a new database that has made the maintenance and quality improvement of metadata fields more straightforward. A content management system for a revised suite of PO.DAAC web pages allows dynamic access to a subset of these metadata fields for enhanced dataset description as well as discovery through a faceted search mechanism from the perspective of the user. From the discovery and metadata standpoint the GDAC has also implemented the NASA version of the OpenSearch protocol for searching for GHRSST granules and developed a web service to generate ISO 19115-2 compliant metadata records. Furthermore, the GDAC has continued to implement a new suite of tools and services for GHRSST datastreams including a Level 2 subsetter known as Dataminer, a revised POET Level 3/4 subsetter and visualization tool, a Google Earth interface to selected daily global Level 2 and Level 4 data, and experimented with a THREDDS catalog of GHRSST data collections. Finally we will summarize the expanding user and data statistics, and other metrics that we have collected over the last year demonstrating the broad user community and applications that the GHRSST project continues to serve via the GDAC distribution mechanisms. This report also serves by extension to summarize the activities of the GHRSST Data Assembly and Systems Technical Advisory Group (DAS-TAG).

A Metadata Standard for Hydroinformatic Data Conforming to International Standards

NASA Astrophysics Data System (ADS)

Notay, Vikram; Carstens, Georg; Lehfeldt, Rainer

2017-04-01

The affordable availability of computing power and digital storage has been a boon for the scientific community. The hydroinformatics community has also benefitted from the so-called digital revolution, which has enabled the tackling of more and more complex physical phenomena using hydroinformatic models, instruments, sensors, etc. With models getting more and more complex, computational domains getting larger and the resolution of computational grids and measurement data getting finer, a large amount of data is generated and consumed in any hydroinformatics related project. The ubiquitous availability of internet also contributes to this phenomenon with data being collected through sensor networks connected to telecommunications networks and the internet long before the term Internet of Things existed. Although generally good, this exponential increase in the number of available datasets gives rise to the need to describe this data in a standardised way to not only be able to get a quick overview about the data but to also facilitate interoperability of data from different sources. The Federal Waterways Engineering and Research Institute (BAW) is a federal authority of the German Federal Ministry of Transport and Digital Infrastructure. BAW acts as a consultant for the safe and efficient operation of the German waterways. As part of its consultation role, BAW operates a number of physical and numerical models for sections of inland and marine waterways. In order to uniformly describe the data produced and consumed by these models throughout BAW and to ensure interoperability with other federal and state institutes on the one hand and with EU countries on the other, a metadata profile for hydroinformatic data has been developed at BAW. The metadata profile is composed in its entirety using the ISO 19115 international standard for metadata related to geographic information. Due to the widespread use of the ISO 19115 standard in the existing geodata infrastructure worldwide, the profile provides a means to describe hydroinformatic data that conforms to existing metadata standards. Additionally, EU and German national standards, INSPIRE and GDI-DE have been considered to ensure interoperability on an international and national level. Finally, elements of the GovData profile of the Federal Government of Germany have been integrated to be able to participate in its Open Data initiative. All these factors make the metadata profile developed at BAW highly suitable for describing hydroinformatic data in particular and physical state variables in general. Further details about this metadata profile will be presented at the conference. Acknowledgements: The authors would like to thank Christoph Wosniok and Peter Schade for their contributions towards the development of this metadata standard.

OPUS: A Comprehensive Search Tool for Remote Sensing Observations of the Outer Planets. Now with Enhanced Geometric Metadata for Cassini and New Horizons Optical Remote Sensing Instruments.

NASA Astrophysics Data System (ADS)

Gordon, M. K.; Showalter, M. R.; Ballard, L.; Tiscareno, M.; French, R. S.; Olson, D.

2017-06-01

The PDS RMS Node hosts OPUS - an accurate, comprehensive search tool for spacecraft remote sensing observations. OPUS supports Cassini: CIRS, ISS, UVIS, VIMS; New Horizons: LORRI, MVIC; Galileo SSI; Voyager ISS; and Hubble: ACS, STIS, WFC3, WFPC2.

Using Metadata To Improve Organization and Information Retrieval on the WWW.

ERIC Educational Resources Information Center

Doan, Bich-Lien; Beigbeder, Michel; Girardot, Jean-Jacques; Jaillon, Philippe

The growing volume of heterogeneous and distributed information on the World Wide Web has made it increasingly difficult for existing tools to retrieve relevant information. To improve the performance of these tools, this paper suggests how to handle two aspects of the problem. The first aspect concerns a better representation and description of…

Social Influences on User Behavior in Group Information Repositories

ERIC Educational Resources Information Center

Rader, Emilee Jeanne

2009-01-01

Group information repositories are systems for organizing and sharing files kept in a central location that all group members can access. These systems are often assumed to be tools for storage and control of files and their metadata, not tools for communication. The purpose of this research is to better understand user behavior in group…

The ground truth about metadata and community detection in networks

PubMed Central

Peel, Leto; Larremore, Daniel B.; Clauset, Aaron

2017-01-01

Across many scientific domains, there is a common need to automatically extract a simplified view or coarse-graining of how a complex system’s components interact. This general task is called community detection in networks and is analogous to searching for clusters in independent vector data. It is common to evaluate the performance of community detection algorithms by their ability to find so-called ground truth communities. This works well in synthetic networks with planted communities because these networks’ links are formed explicitly based on those known communities. However, there are no planted communities in real-world networks. Instead, it is standard practice to treat some observed discrete-valued node attributes, or metadata, as ground truth. We show that metadata are not the same as ground truth and that treating them as such induces severe theoretical and practical problems. We prove that no algorithm can uniquely solve community detection, and we prove a general No Free Lunch theorem for community detection, which implies that there can be no algorithm that is optimal for all possible community detection tasks. However, community detection remains a powerful tool and node metadata still have value, so a careful exploration of their relationship with network structure can yield insights of genuine worth. We illustrate this point by introducing two statistical techniques that can quantify the relationship between metadata and community structure for a broad class of models. We demonstrate these techniques using both synthetic and real-world networks, and for multiple types of metadata and community structures. PMID:28508065

Who Tweets? Deriving the Demographic Characteristics of Age, Occupation and Social Class from Twitter User Meta-Data

PubMed Central

Sloan, Luke; Morgan, Jeffrey; Burnap, Pete; Williams, Matthew

2015-01-01

This paper specifies, designs and critically evaluates two tools for the automated identification of demographic data (age, occupation and social class) from the profile descriptions of Twitter users in the United Kingdom (UK). Meta-data data routinely collected through the Collaborative Social Media Observatory (COSMOS: http://www.cosmosproject.net/) relating to UK Twitter users is matched with the occupational lookup tables between job and social class provided by the Office for National Statistics (ONS) using SOC2010. Using expert human validation, the validity and reliability of the automated matching process is critically assessed and a prospective class distribution of UK Twitter users is offered with 2011 Census baseline comparisons. The pattern matching rules for identifying age are explained and enacted following a discussion on how to minimise false positives. The age distribution of Twitter users, as identified using the tool, is presented alongside the age distribution of the UK population from the 2011 Census. The automated occupation detection tool reliably identifies certain occupational groups, such as professionals, for which job titles cannot be confused with hobbies or are used in common parlance within alternative contexts. An alternative explanation on the prevalence of hobbies is that the creative sector is overrepresented on Twitter compared to 2011 Census data. The age detection tool illustrates the youthfulness of Twitter users compared to the general UK population as of the 2011 Census according to proportions, but projections demonstrate that there is still potentially a large number of older platform users. It is possible to detect “signatures” of both occupation and age from Twitter meta-data with varying degrees of accuracy (particularly dependent on occupational groups) but further confirmatory work is needed. PMID:25729900

Applying the Karma Provenance tool to NASA's AMSR-E Data Production Stream

NASA Astrophysics Data System (ADS)

Ramachandran, R.; Conover, H.; Regner, K.; Movva, S.; Goodman, H. M.; Pale, B.; Purohit, P.; Sun, Y.

2010-12-01

Current procedures for capturing and disseminating provenance, or data product lineage, are limited in both what is captured and how it is disseminated to the science community. For example, the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) Science Investigator-led Processing System (SIPS) generates Level 2 and Level 3 data products for a variety of geophysical parameters. Data provenance and quality information for these data sets is either very general (e.g., user guides, a list of anomalous data receipt and processing conditions over the life of the missions) or difficult to access or interpret (e.g., quality flags embedded in the data, production history files not easily available to users). Karma is a provenance collection and representation tool designed and developed for data driven workflows such as the productions streams used to produce EOS standard products. Karma records uniform and usable provenance metadata independent of the processing system while minimizing both the modification burden on the processing system and the overall performance overhead. Karma collects both the process and data provenance. The process provenance contains information about the workflow execution and the associated algorithm invocations. The data provenance captures metadata about the derivation history of the data product, including algorithms used and input data sources transformed to generate it. As part of an ongoing NASA funded project, Karma is being integrated into the AMSR-E SIPS data production streams. Metadata gathered by the tool will be presented to the data consumers as provenance graphs, which are useful in validating the workflows and determining the quality of the data product. This presentation will discuss design and implementation issues faced while incorporating a provenance tool into a structured data production flow. Prototype results will also be presented in this talk.

The Value of Data and Metadata Standardization for Interoperability in Giovanni

NASA Astrophysics Data System (ADS)

Smit, C.; Hegde, M.; Strub, R. F.; Bryant, K.; Li, A.; Petrenko, M.

2017-12-01

Giovanni (https://giovanni.gsfc.nasa.gov/giovanni/) is a data exploration and visualization tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC). It has been around in one form or another for more than 15 years. Giovanni calculates simple statistics and produces 22 different visualizations for more than 1600 geophysical parameters from more than 90 satellite and model products. Giovanni relies on external data format standards to ensure interoperability, including the NetCDF CF Metadata Conventions. Unfortunately, these standards were insufficient to make Giovanni's internal data representation truly simple to use. Finding and working with dimensions can be convoluted with the CF Conventions. Furthermore, the CF Conventions are silent on machine-friendly descriptive metadata such as the parameter's source product and product version. In order to simplify analyzing disparate earth science data parameters in a unified way, we developed Giovanni's internal standard. First, the format standardizes parameter dimensions and variables so they can be easily found. Second, the format adds all the machine-friendly metadata Giovanni needs to present our parameters to users in a consistent and clear manner. At a glance, users can grasp all the pertinent information about parameters both during parameter selection and after visualization. This poster gives examples of how our metadata and data standards, both external and internal, have both simplified our code base and improved our users' experiences.

A metadata reporting framework for standardization and synthesis of ecohydrological field observations

NASA Astrophysics Data System (ADS)

Christianson, D. S.; Varadharajan, C.; Detto, M.; Faybishenko, B.; Gimenez, B.; Jardine, K.; Negron Juarez, R. I.; Pastorello, G.; Powell, T.; Warren, J.; Wolfe, B.; McDowell, N. G.; Kueppers, L. M.; Chambers, J.; Agarwal, D.

2016-12-01

The U.S. Department of Energy's (DOE) Next Generation Ecosystem Experiment (NGEE) Tropics project aims to develop a process-rich tropical forest ecosystem model that is parameterized and benchmarked by field observations. Thus, data synthesis, quality assurance and quality control (QA/QC), and data product generation of a diverse and complex set of ecohydrological observations, including sapflux, leaf surface temperature, soil water content, and leaf gas exchange from sites across the Tropics, are required to support model simulations. We have developed a metadata reporting framework, implemented in conjunction with the NGEE Tropics Data Archive tool, to enable cross-site and cross-method comparison, data interpretability, and QA/QC. We employed a modified User-Centered Design approach, which involved short development cycles based on user-identified needs, and iterative testing with data providers and users. The metadata reporting framework currently has been implemented for sensor-based observations and leverages several existing metadata protocols. The framework consists of templates that define a multi-scale measurement position hierarchy, descriptions of measurement settings, and details about data collection and data file organization. The framework also enables data providers to define data-access permission settings, provenance, and referencing to enable appropriate data usage, citation, and attribution. In addition to describing the metadata reporting framework, we discuss tradeoffs and impressions from both data providers and users during the development process, focusing on the scalability, usability, and efficiency of the framework.

Protocols for Scholarly Communication

NASA Astrophysics Data System (ADS)

Pepe, A.; Yeomans, J.

2007-10-01

CERN, the European Organization for Nuclear Research, has operated an institutional preprint repository for more than 10 years. The repository contains over 850,000 records of which more than 450,000 are full-text OA preprints, mostly in the field of particle physics, and it is integrated with the library's holdings of books, conference proceedings, journals and other grey literature. In order to encourage effective propagation and open access to scholarly material, CERN is implementing a range of innovative library services into its document repository: automatic keywording, reference extraction, collaborative management tools and bibliometric tools. Some of these services, such as user reviewing and automatic metadata extraction, could make up an interesting testbed for future publishing solutions and certainly provide an exciting environment for e-science possibilities. The future protocol for scientific communication should guide authors naturally towards OA publication, and CERN wants to help reach a full open access publishing environment for the particle physics community and related sciences in the next few years.

Automated geo/ortho registered aerial imagery product generation using the mapping system interface card (MSIC)

NASA Astrophysics Data System (ADS)

Bratcher, Tim; Kroutil, Robert; Lanouette, André; Lewis, Paul E.; Miller, David; Shen, Sylvia; Thomas, Mark

2013-05-01

The development concept paper for the MSIC system was first introduced in August 2012 by these authors. This paper describes the final assembly, testing, and commercial availability of the Mapping System Interface Card (MSIC). The 2.3kg MSIC is a self-contained, compact variable configuration, low cost real-time precision metadata annotator with embedded INS/GPS designed specifically for use in small aircraft. The MSIC was specifically designed to convert commercial-off-the-shelf (COTS) digital cameras and imaging/non-imaging spectrometers with Camera Link standard data streams into mapping systems for airborne emergency response and scientific remote sensing applications. COTS digital cameras and imaging/non-imaging spectrometers covering the ultraviolet through long-wave infrared wavelengths are important tools now readily available and affordable for use by emergency responders and scientists. The MSIC will significantly enhance the capability of emergency responders and scientists by providing a direct transformation of these important COTS sensor tools into low-cost real-time aerial mapping systems.

Tools for automated acoustic monitoring within the R package monitoR

USGS Publications Warehouse

Katz, Jonathan; Hafner, Sasha D.; Donovan, Therese

2016-01-01

The R package monitoR contains tools for managing an acoustic-monitoring program including survey metadata, template creation and manipulation, automated detection and results management. These tools are scalable for use with small projects as well as larger long-term projects and those with expansive spatial extents. Here, we describe typical workflow when using the tools in monitoR. Typical workflow utilizes a generic sequence of functions, with the option for either binary point matching or spectrogram cross-correlation detectors.

Community cyberinfrastructure for Advanced Microbial Ecology Research and Analysis: the CAMERA resource

PubMed Central

Sun, Shulei; Chen, Jing; Li, Weizhong; Altintas, Ilkay; Lin, Abel; Peltier, Steve; Stocks, Karen; Allen, Eric E.; Ellisman, Mark; Grethe, Jeffrey; Wooley, John

2011-01-01

The Community Cyberinfrastructure for Advanced Microbial Ecology Research and Analysis (CAMERA, http://camera.calit2.net/) is a database and associated computational infrastructure that provides a single system for depositing, locating, analyzing, visualizing and sharing data about microbial biology through an advanced web-based analysis portal. CAMERA collects and links metadata relevant to environmental metagenome data sets with annotation in a semantically-aware environment allowing users to write expressive semantic queries against the database. To meet the needs of the research community, users are able to query metadata categories such as habitat, sample type, time, location and other environmental physicochemical parameters. CAMERA is compliant with the standards promulgated by the Genomic Standards Consortium (GSC), and sustains a role within the GSC in extending standards for content and format of the metagenomic data and metadata and its submission to the CAMERA repository. To ensure wide, ready access to data and annotation, CAMERA also provides data submission tools to allow researchers to share and forward data to other metagenomics sites and community data archives such as GenBank. It has multiple interfaces for easy submission of large or complex data sets, and supports pre-registration of samples for sequencing. CAMERA integrates a growing list of tools and viewers for querying, analyzing, annotating and comparing metagenome and genome data. PMID:21045053

Community cyberinfrastructure for Advanced Microbial Ecology Research and Analysis: the CAMERA resource.

PubMed

Sun, Shulei; Chen, Jing; Li, Weizhong; Altintas, Ilkay; Lin, Abel; Peltier, Steve; Stocks, Karen; Allen, Eric E; Ellisman, Mark; Grethe, Jeffrey; Wooley, John

2011-01-01

The Community Cyberinfrastructure for Advanced Microbial Ecology Research and Analysis (CAMERA, http://camera.calit2.net/) is a database and associated computational infrastructure that provides a single system for depositing, locating, analyzing, visualizing and sharing data about microbial biology through an advanced web-based analysis portal. CAMERA collects and links metadata relevant to environmental metagenome data sets with annotation in a semantically-aware environment allowing users to write expressive semantic queries against the database. To meet the needs of the research community, users are able to query metadata categories such as habitat, sample type, time, location and other environmental physicochemical parameters. CAMERA is compliant with the standards promulgated by the Genomic Standards Consortium (GSC), and sustains a role within the GSC in extending standards for content and format of the metagenomic data and metadata and its submission to the CAMERA repository. To ensure wide, ready access to data and annotation, CAMERA also provides data submission tools to allow researchers to share and forward data to other metagenomics sites and community data archives such as GenBank. It has multiple interfaces for easy submission of large or complex data sets, and supports pre-registration of samples for sequencing. CAMERA integrates a growing list of tools and viewers for querying, analyzing, annotating and comparing metagenome and genome data.

Solutions for extracting file level spatial metadata from airborne mission data

NASA Astrophysics Data System (ADS)

Schwab, M. J.; Stanley, M.; Pals, J.; Brodzik, M.; Fowler, C.; Icebridge Engineering/Spatial Metadata

2011-12-01

Authors: Michael Stanley Mark Schwab Jon Pals Mary J. Brodzik Cathy Fowler Collaboration: Raytheon EED and NSIDC Raytheon / EED 5700 Rivertech Court Riverdale, MD 20737 NSIDC University of Colorado UCB 449 Boulder, CO 80309-0449 Data sets acquired from satellites and aircraft may differ in many ways. We will focus on the differences in spatial coverage between the two platforms. Satellite data sets over a given period typically cover large geographic regions. These data are collected in a consistent, predictable and well understood manner due to the uniformity of satellite orbits. Since satellite data collection paths are typically smooth and uniform the data from satellite instruments can usually be described with simple spatial metadata. Subsequently, these spatial metadata can be stored and searched easily and efficiently. Conversely, aircraft have significantly more freedom to change paths, circle, overlap, and vary altitude all of which add complexity to the spatial metadata. Aircraft are also subject to wind and other elements that result in even more complicated and unpredictable spatial coverage areas. This unpredictability and complexity makes it more difficult to extract usable spatial metadata from data sets collected on aircraft missions. It is not feasible to use all of the location data from aircraft mission data sets for use as spatial metadata. The number of data points in typical data sets poses serious performance problems for spatial searching. In order to provide efficient spatial searching of the large number of files cataloged in our systems, we need to extract approximate spatial descriptions as geo-polygons from a small number of vertices (fewer than two hundred). We present some of the challenges and solutions for creating airborne mission-derived spatial metadata. We are implementing these methods to create the spatial metadata for insertion of IceBridge mission data into ECS for public access through NSIDC and ECHO but, they are potentially extensible to any aircraft mission data.

linkedISA: semantic representation of ISA-Tab experimental metadata.

PubMed

González-Beltrán, Alejandra; Maguire, Eamonn; Sansone, Susanna-Assunta; Rocca-Serra, Philippe

2014-01-01

Reporting and sharing experimental metadata- such as the experimental design, characteristics of the samples, and procedures applied, along with the analysis results, in a standardised manner ensures that datasets are comprehensible and, in principle, reproducible, comparable and reusable. Furthermore, sharing datasets in formats designed for consumption by humans and machines will also maximize their use. The Investigation/Study/Assay (ISA) open source metadata tracking framework facilitates standards-compliant collection, curation, visualization, storage and sharing of datasets, leveraging on other platforms to enable analysis and publication. The ISA software suite includes several components used in increasingly diverse set of life science and biomedical domains; it is underpinned by a general-purpose format, ISA-Tab, and conversions exist into formats required by public repositories. While ISA-Tab works well mainly as a human readable format, we have also implemented a linked data approach to semantically define the ISA-Tab syntax. We present a semantic web representation of the ISA-Tab syntax that complements ISA-Tab's syntactic interoperability with semantic interoperability. We introduce the linkedISA conversion tool from ISA-Tab to the Resource Description Framework (RDF), supporting mappings from the ISA syntax to multiple community-defined, open ontologies and capitalising on user-provided ontology annotations in the experimental metadata. We describe insights of the implementation and how annotations can be expanded driven by the metadata. We applied the conversion tool as part of Bio-GraphIIn, a web-based application supporting integration of the semantically-rich experimental descriptions. Designed in a user-friendly manner, the Bio-GraphIIn interface hides most of the complexities to the users, exposing a familiar tabular view of the experimental description to allow seamless interaction with the RDF representation, and visualising descriptors to drive the query over the semantic representation of the experimental design. In addition, we defined queries over the linkedISA RDF representation and demonstrated its use over the linkedISA conversion of datasets from Nature' Scientific Data online publication. Our linked data approach has allowed us to: 1) make the ISA-Tab semantics explicit and machine-processable, 2) exploit the existing ontology-based annotations in the ISA-Tab experimental descriptions, 3) augment the ISA-Tab syntax with new descriptive elements, 4) visualise and query elements related to the experimental design. Reasoning over ISA-Tab metadata and associated data will facilitate data integration and knowledge discovery.

The MPO system for automatic workflow documentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abla, G.; Coviello, E. N.; Flanagan, S. M.

Data from large-scale experiments and extreme-scale computing is expensive to produce and may be used for critical applications. However, it is not the mere existence of data that is important, but our ability to make use of it. Experience has shown that when metadata is better organized and more complete, the underlying data becomes more useful. Traditionally, capturing the steps of scientific workflows and metadata was the role of the lab notebook, but the digital era has resulted instead in the fragmentation of data, processing, and annotation. Here, this article presents the Metadata, Provenance, and Ontology (MPO) System, the softwaremore » that can automate the documentation of scientific workflows and associated information. Based on recorded metadata, it provides explicit information about the relationships among the elements of workflows in notebook form augmented with directed acyclic graphs. A set of web-based graphical navigation tools and Application Programming Interface (API) have been created for searching and browsing, as well as programmatically accessing the workflows and data. We describe the MPO concepts and its software architecture. We also report the current status of the software as well as the initial deployment experience.« less

The MPO system for automatic workflow documentation

DOE PAGES

Abla, G.; Coviello, E. N.; Flanagan, S. M.; ...

2016-04-18

Data from large-scale experiments and extreme-scale computing is expensive to produce and may be used for critical applications. However, it is not the mere existence of data that is important, but our ability to make use of it. Experience has shown that when metadata is better organized and more complete, the underlying data becomes more useful. Traditionally, capturing the steps of scientific workflows and metadata was the role of the lab notebook, but the digital era has resulted instead in the fragmentation of data, processing, and annotation. Here, this article presents the Metadata, Provenance, and Ontology (MPO) System, the softwaremore » that can automate the documentation of scientific workflows and associated information. Based on recorded metadata, it provides explicit information about the relationships among the elements of workflows in notebook form augmented with directed acyclic graphs. A set of web-based graphical navigation tools and Application Programming Interface (API) have been created for searching and browsing, as well as programmatically accessing the workflows and data. We describe the MPO concepts and its software architecture. We also report the current status of the software as well as the initial deployment experience.« less

Evolving the Living With a Star Data System Definition

NASA Astrophysics Data System (ADS)

Otranto, J. F.; Dijoseph, M.

2003-12-01

NASA's Living With a Star (LWS) Program is a space weather-focused and applications-driven research program. The LWS Program is soliciting input from the solar, space physics, space weather, and climate science communities to develop a system that enables access to science data associated with these disciplines, and advances the development of discipline and interdisciplinary findings. The LWS Program will implement a data system that builds upon the existing and planned data capture, processing, and storage components put in place by individual spacecraft missions and also inter-project data management systems, including active and deep archives, and multi-mission data repositories. It is technically feasible for the LWS Program to integrate data from a broad set of resources, assuming they are either publicly accessible or allow access by permission. The LWS Program data system will work in coordination with spacecraft mission data systems and science data repositories, integrating their holdings using a common metadata representation. This common representation relies on a robust metadata definition that provides journalistic and technical data descriptions, plus linkages to supporting data products and tools. The LWS Program intends to become an enabling resource to PIs, interdisciplinary scientists, researchers, and students facilitating both access to a broad collection of science data, as well as the necessary supporting components to understand and make productive use of these data. For the LWS Program to represent science data that are physically distributed across various ground system elements, information will be collected about these distributed data products through a series of LWS Program-created agents. These agents will be customized to interface or interact with each one of these data systems, collect information, and forward any new metadata records to a LWS Program-developed metadata library. A populated LWS metadata library will function as a single point-of-contact that serves the entire science community as a first stop for data availability, whether or not science data are physically stored in an LWS-operated repository. Further, this metadata library will provide the user access to information for understanding these data including descriptions of the associated spacecraft and instrument, data format, calibration and operations issues, links to ancillary and correlative data products, links to processing tools and models associated with these data, and any corresponding findings produced using these data. The LWS may also support an active archive for solar, space physics, space weather, and climate data when these data would otherwise be discarded or archived off-line. This archive could potentially serve also as a data storage backup facility for LWS missions. The plan for the LWS Program metadata library is developed based upon input received from the solar and geospace science communities; the library's architecture is based on existing systems developed for serving science metadata. The LWS Program continues to seek constructive input from the science community, examples of both successes and failures in dealing with science data systems, and insights regarding the obstacles between the current state-of-the-practice and this vision for the LWS Program metadata library.

XML at the ADC: Steps to a Next Generation Data Archive

NASA Astrophysics Data System (ADS)

Shaya, E.; Blackwell, J.; Gass, J.; Oliversen, N.; Schneider, G.; Thomas, B.; Cheung, C.; White, R. A.

1999-05-01

The eXtensible Markup Language (XML) is a document markup language that allows users to specify their own tags, to create hierarchical structures to qualify their data, and to support automatic checking of documents for structural validity. It is being intensively supported by nearly every major corporate software developer. Under the funds of a NASA AISRP proposal, the Astronomical Data Center (ADC, http://adc.gsfc.nasa.gov) is developing an infrastructure for importation, enhancement, and distribution of data and metadata using XML as the document markup language. We discuss the preliminary Document Type Definition (DTD, at http://adc.gsfc.nasa.gov/xml) which specifies the elements and their attributes in our metadata documents. This attempts to define both the metadata of an astronomical catalog and the `header' information of an astronomical table. In addition, we give an overview of the planned flow of data through automated pipelines from authors and journal presses into our XML archive and retrieval through the web via the XML-QL Query Language and eXtensible Style Language (XSL) scripts. When completed, the catalogs and journal tables at the ADC will be tightly hyperlinked to enhance data discovery. In addition one will be able to search on fragmentary information. For instance, one could query for a table by entering that the second author is so-and-so or that the third author is at such-and-such institution.

Application Profiling for Rural Communities: eGov Services and Training Resources in Rural Inclusion

NASA Astrophysics Data System (ADS)

Karamolegkos, Pantelis; Maroudas, Axel; Manouselis, Nikos

Metadata plays a critical role in the design and development of online repositories. The efficiency and ease of use of the repositories are directly associated with the metadata structure, since end-user functionalities such as search, retrieval and access are highly dependent on how the metadata schema and application profile have been conceptualized and implemented. The need for efficient and interoperable application profiles is even more substantial when it comes to services related to the e-government (eGov) paradigm, given a) the close association between services related to eGov and the metadata usage and b) the fact that the eGov concept is associated with time and cost critical processes, i.e. interaction of citizens and services with public authorities. In this paper, we outline an effort related to application profiling for eGov services and training resources, used in the platform of RuralObservatory2.0, which will underpin a major objective of the ICT PSP Rural Inclusion project, i.e. the eGov paradigm uptake by rural communities.

Evolution of the use of relational and NoSQL databases in the ATLAS experiment

NASA Astrophysics Data System (ADS)

Barberis, D.

2016-09-01

The ATLAS experiment used for many years a large database infrastructure based on Oracle to store several different types of non-event data: time-dependent detector configuration and conditions data, calibrations and alignments, configurations of Grid sites, catalogues for data management tools, job records for distributed workload management tools, run and event metadata. The rapid development of "NoSQL" databases (structured storage services) in the last five years allowed an extended and complementary usage of traditional relational databases and new structured storage tools in order to improve the performance of existing applications and to extend their functionalities using the possibilities offered by the modern storage systems. The trend is towards using the best tool for each kind of data, separating for example the intrinsically relational metadata from payload storage, and records that are frequently updated and benefit from transactions from archived information. Access to all components has to be orchestrated by specialised services that run on front-end machines and shield the user from the complexity of data storage infrastructure. This paper describes this technology evolution in the ATLAS database infrastructure and presents a few examples of large database applications that benefit from it.

Lessons Learned From 104 Years of Mobile Observatories

NASA Astrophysics Data System (ADS)

Miller, S. P.; Clark, P. D.; Neiswender, C.; Raymond, L.; Rioux, M.; Norton, C.; Detrick, R.; Helly, J.; Sutton, D.; Weatherford, J.

2007-12-01

As the oceanographic community ventures into a new era of integrated observatories, it may be helpful to look back on the era of "mobile observatories" to see what Cyberinfrastructure lessons might be learned. For example, SIO has been operating research vessels for 104 years, supporting a wide range of disciplines: marine geology and geophysics, physical oceanography, geochemistry, biology, seismology, ecology, fisheries, and acoustics. In the last 6 years progress has been made with diverse data types, formats and media, resulting in a fully-searchable online SIOExplorer Digital Library of more than 800 cruises (http://SIOExplorer.ucsd.edu). Public access to SIOExplorer is considerable, with 795,351 files (206 GB) downloaded last year. During the last 3 years the efforts have been extended to WHOI, with a "Multi-Institution Testbed for Scalable Digital Archiving" funded by the Library of Congress and NSF (IIS 0455998). The project has created a prototype digital library of data from both institutions, including cruises, Alvin submersible dives, and ROVs. In the process, the team encountered technical and cultural issues that will be facing the observatory community in the near future. Technological Lessons Learned: Shipboard data from multiple institutions are extraordinarily diverse, and provide a good training ground for observatories. Data are gathered from a wide range of authorities, laboratories, servers and media, with little documentation. Conflicting versions exist, generated by alternative processes. Domain- and institution-specific issues were addressed during initial staging. Data files were categorized and metadata harvested with automated procedures. With our second-generation approach to staging, we achieve higher levels of automation with greater use of controlled vocabularies. Database and XML- based procedures deal with the diversity of raw metadata values and map them to agreed-upon standard values, in collaboration with the Marine Metadata Interoperability (MMI) community. All objects are tagged with an expert level, thus serving an educational audience, as well as research users. After staging, publication into the digital library is completely automated. The technical challenges have been largely overcome, thanks to a scalable, federated digital library architecture from the San Diego Supercomputer Center, implemented at SIO, WHOI and other sites. The metadata design is flexible, supporting modular blocks of metadata tailored to the needs of instruments, samples, documents, derived products, cruises or dives, as appropriate. Controlled metadata vocabularies, with content and definitions negotiated by all parties, are critical. Metadata may be mapped to required external standards and formats, as needed. Cultural Lessons Learned: The cultural challenges have been more formidable than expected. They became most apparent during attempts to categorize and stage digital data objects across two institutions, each with their own naming conventions and practices, generally undocumented, and evolving across decades. Whether the questions concerned data ownership, collection techniques, data diversity or institutional practices, the solution involved a joint discussion with scientists, data managers, technicians and archivists, working together. Because metadata discussions go on endlessly, significant benefit comes from dictionaries with definitions of all community-authorized metadata values.

Expanding Access to NCAR's Digital Assets: Towards a Unified Scientific Data Management System

NASA Astrophysics Data System (ADS)

Stott, D.

2016-12-01

In 2014 the National Center for Atmospheric Research (NCAR) Directorate created the Data Stewardship Engineering Team (DSET) to plan and implement the strategic vision of an integrated front door for data discovery and access across the organization, including all laboratories, the library, and UCAR Community Programs. The DSET is focused on improving the quality of users' experiences in finding and using NCAR's digital assets. This effort also supports new policies included in federal mandates, NSF requirements, and journal publication rules. An initial survey with 97 respondents identified 68 persons responsible for more than 3 petabytes of data. An inventory, using the Data Asset Framework produced by the UK Digital Curation Centre as a starting point, identified asset types that included files and metadata, publications, images, and software (visualization, analysis, model codes). User story sessions with representatives from each lab identified and ranked desired features for a unified Scientific Data Management System (SDMS). A process beginning with an organization-wide assessment of metadata by the HDF Group and followed by meetings with labs to identify key documentation concepts, culminated in the development of an NCAR metadata dialect that leverages the DataCite and ISO 19115 standards. The tasks ahead are to build out an SDMS and populate it with rich standardized metadata. Software packages have been prototyped and currently are being tested and reviewed by DSET members. Key challenges for the DSET include technical and non-technical issues. First, the status quo with regard to how assets are managed varies widely across the organization. There are differences in file format standards, technologies, and discipline-specific vocabularies. Metadata diversity is another real challenge. The types of metadata, the standards used, and the capacity to create new metadata varies across the organization. Significant effort is required to develop tools to create new standard metadata across the organization, adapt and integrate current digital assets, and establish consistent data management practices going forward. To be successful, best practices must be infused into daily activities. This poster will highlight the processes, lessons learned, and current status of the DSET effort at NCAR.

Open Source Software Development and Lotka's Law: Bibliometric Patterns in Programming.

ERIC Educational Resources Information Center

Newby, Gregory B.; Greenberg, Jane; Jones, Paul

2003-01-01

Applies Lotka's Law to metadata on open source software development. Authoring patterns found in software development productivity are found to be comparable to prior studies of Lotka's Law for scientific and scholarly publishing, and offer promise in predicting aggregate behavior of open source developers. (Author/LRW)

BioUSeR: a semantic-based tool for retrieving Life Science web resources driven by text-rich user requirements

PubMed Central

2013-01-01

Background Open metadata registries are a fundamental tool for researchers in the Life Sciences trying to locate resources. While most current registries assume that resources are annotated with well-structured metadata, evidence shows that most of the resource annotations simply consists of informal free text. This reality must be taken into account in order to develop effective techniques for resource discovery in Life Sciences. Results BioUSeR is a semantic-based tool aimed at retrieving Life Sciences resources described in free text. The retrieval process is driven by the user requirements, which consist of a target task and a set of facets of interest, both expressed in free text. BioUSeR is able to effectively exploit the available textual descriptions to find relevant resources by using semantic-aware techniques. Conclusions BioUSeR overcomes the limitations of the current registries thanks to: (i) rich specification of user information needs, (ii) use of semantics to manage textual descriptions, (iii) retrieval and ranking of resources based on user requirements. PMID:23635042

The Water SWITCH-ON Spatial Information Platform (SIP)

NASA Astrophysics Data System (ADS)

Sala Calero, J., Sr.; Boot, G., Sr.; Dihé, P., Sr.; Arheimer, B.

2017-12-01

The amount of hydrological open data is continually growing and providing opportunities to the scientific community. Although the existing data portals (GEOSS Portal, INSPIRE community geoportal and others) enable access to open data, many users still find browsing through them difficult. Moreover, the time spent on gathering and preparing data usually is more significant than the time spent on the experiment itself. Thus, any improvement on searching, understanding, accessing or using open data is greatly beneficial. The Spatial Information Platform (SIP) has been developed to tackle these issues within the SWITCH-ON European Commission funded FP7 project. The SIP has been designed as a set of tools based on open standards that provide to the user all the necessary functionalities as described in the Publish-Find-Bind (PFB) pattern. In other words, this means that the SIP helps users to locate relevant and suitable data for their experiments analysis, to access and transform it (filtering, extraction, selection, conversion, aggregation). Moreover, the SIP can be used to provide descriptive information about the data and to publish it so others can find and use it. The SIP is based on existing open data protocols such as the OGC/CSW, OGC/WMS, OpenDAP and open-source components like PostgreSQL/PostGIS, GeoServer and pyCSW. The SIP is divided in three main user interfaces: the BYOD (Browse your open dataset) web interface, the Expert GUI tool and the Upload Data and Metadata web interface. The BYOD HTML5 client is the main entry point for users that want to browse through open data in the SIP. The BYOD has a map interface based on Leaflet JavaScript libraries so that the users can search more efficiently. The web-based Open Data Registration Tool is a user-friendly upload and metadata description interface (geographical extent, license, DOI generation). The Expert GUI is a desktop application that provides full metadata editing capabilities for the metadata moderators of the project. In conclusion, the Spatial Information Platform (SIP) provides to its community a set of tools for better understanding and ease of use of hydrological open-data. Moreover, the SIP has been based on well-known OGC standards that will allow the connection and data harvesting from popular open data portals such as the GEOSS system of systems.

mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data

PubMed Central

Larralde, Martin; Lawson, Thomas N.; Weber, Ralf J. M.; Moreno, Pablo; Haug, Kenneth; Rocca-Serra, Philippe; Viant, Mark R.; Steinbeck, Christoph; Salek, Reza M.

2017-01-01

Abstract Summary Submission to the MetaboLights repository for metabolomics data currently places the burden of reporting instrument and acquisition parameters in ISA-Tab format on users, who have to do it manually, a process that is time consuming and prone to user input error. Since the large majority of these parameters are embedded in instrument raw data files, an opportunity exists to capture this metadata more accurately. Here we report a set of Python packages that can automatically generate ISA-Tab metadata file stubs from raw XML metabolomics data files. The parsing packages are separated into mzML2ISA (encompassing mzML and imzML formats) and nmrML2ISA (nmrML format only). Overall, the use of mzML2ISA & nmrML2ISA reduces the time needed to capture metadata substantially (capturing 90% of metadata on assay and sample levels), is much less prone to user input errors, improves compliance with minimum information reporting guidelines and facilitates more finely grained data exploration and querying of datasets. Availability and Implementation mzML2ISA & nmrML2ISA are available under version 3 of the GNU General Public Licence at https://github.com/ISA-tools. Documentation is available from http://2isa.readthedocs.io/en/latest/. Contact reza.salek@ebi.ac.uk or isatools@googlegroups.com Supplementary information Supplementary data are available at Bioinformatics online. PMID:28402395

The use of advanced web-based survey design in Delphi research.

PubMed

Helms, Christopher; Gardner, Anne; McInnes, Elizabeth

2017-12-01

A discussion of the application of metadata, paradata and embedded data in web-based survey research, using two completed Delphi surveys as examples. Metadata, paradata and embedded data use in web-based Delphi surveys has not been described in the literature. The rapid evolution and widespread use of online survey methods imply that paper-based Delphi methods will likely become obsolete. Commercially available web-based survey tools offer a convenient and affordable means of conducting Delphi research. Researchers and ethics committees may be unaware of the benefits and risks of using metadata in web-based surveys. Discussion paper. Two web-based, three-round Delphi surveys were conducted sequentially between August 2014 - January 2015 and April - May 2016. Their aims were to validate the Australian nurse practitioner metaspecialties and their respective clinical practice standards. Our discussion paper is supported by researcher experience and data obtained from conducting both web-based Delphi surveys. Researchers and ethics committees should consider the benefits and risks of metadata use in web-based survey methods. Web-based Delphi research using paradata and embedded data may introduce efficiencies that improve individual participant survey experiences and reduce attrition across iterations. Use of embedded data allows the efficient conduct of multiple simultaneous Delphi surveys across a shorter timeframe than traditional survey methods. The use of metadata, paradata and embedded data appears to improve response rates, identify bias and give possible explanation for apparent outlier responses, providing an efficient method of conducting web-based Delphi surveys. © 2017 John Wiley & Sons Ltd.

Logic programming and metadata specifications

NASA Technical Reports Server (NTRS)

Lopez, Antonio M., Jr.; Saacks, Marguerite E.

1992-01-01

Artificial intelligence (AI) ideas and techniques are critical to the development of intelligent information systems that will be used to collect, manipulate, and retrieve the vast amounts of space data produced by 'Missions to Planet Earth.' Natural language processing, inference, and expert systems are at the core of this space application of AI. This paper presents logic programming as an AI tool that can support inference (the ability to draw conclusions from a set of complicated and interrelated facts). It reports on the use of logic programming in the study of metadata specifications for a small problem domain of airborne sensors, and the dataset characteristics and pointers that are needed for data access.

THE NEW ONLINE METADATA EDITOR FOR GENERATING STRUCTURED METADATA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Devarakonda, Ranjeet; Shrestha, Biva; Palanisamy, Giri

Nobody is better suited to describe data than the scientist who created it. This description about a data is called Metadata. In general terms, Metadata represents the who, what, when, where, why and how of the dataset [1]. eXtensible Markup Language (XML) is the preferred output format for metadata, as it makes it portable and, more importantly, suitable for system discoverability. The newly developed ORNL Metadata Editor (OME) is a Web-based tool that allows users to create and maintain XML files containing key information, or metadata, about the research. Metadata include information about the specific projects, parameters, time periods, andmore » locations associated with the data. Such information helps put the research findings in context. In addition, the metadata produced using OME will allow other researchers to find these data via Metadata clearinghouses like Mercury [2][4]. OME is part of ORNL s Mercury software fleet [2][3]. It was jointly developed to support projects funded by the United States Geological Survey (USGS), U.S. Department of Energy (DOE), National Aeronautics and Space Administration (NASA) and National Oceanic and Atmospheric Administration (NOAA). OME s architecture provides a customizable interface to support project-specific requirements. Using this new architecture, the ORNL team developed OME instances for USGS s Core Science Analytics, Synthesis, and Libraries (CSAS&L), DOE s Next Generation Ecosystem Experiments (NGEE) and Atmospheric Radiation Measurement (ARM) Program, and the international Surface Ocean Carbon Dioxide ATlas (SOCAT). Researchers simply use the ORNL Metadata Editor to enter relevant metadata into a Web-based form. From the information on the form, the Metadata Editor can create an XML file on the server that the editor is installed or to the user s personal computer. Researchers can also use the ORNL Metadata Editor to modify existing XML metadata files. As an example, an NGEE Arctic scientist use OME to register their datasets to the NGEE data archive and allows the NGEE archive to publish these datasets via a data search portal (http://ngee.ornl.gov/data). These highly descriptive metadata created using OME allows the Archive to enable advanced data search options using keyword, geo-spatial, temporal and ontology filters. Similarly, ARM OME allows scientists or principal investigators (PIs) to submit their data products to the ARM data archive. How would OME help Big Data Centers like the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC)? The ORNL DAAC is one of NASA s Earth Observing System Data and Information System (EOSDIS) data centers managed by the Earth Science Data and Information System (ESDIS) Project. The ORNL DAAC archives data produced by NASA's Terrestrial Ecology Program. The DAAC provides data and information relevant to biogeochemical dynamics, ecological data, and environmental processes, critical for understanding the dynamics relating to the biological, geological, and chemical components of the Earth's environment. Typically data produced, archived and analyzed is at a scale of multiple petabytes, which makes the discoverability of the data very challenging. Without proper metadata associated with the data, it is difficult to find the data you are looking for and equally difficult to use and understand the data. OME will allow data centers like the NGEE and ORNL DAAC to produce meaningful, high quality, standards-based, descriptive information about their data products in-turn helping with the data discoverability and interoperability. Useful Links: USGS OME: http://mercury.ornl.gov/OME/ NGEE OME: http://ngee-arctic.ornl.gov/ngeemetadata/ ARM OME: http://archive2.ornl.gov/armome/ Contact: Ranjeet Devarakonda (devarakondar@ornl.gov) References: [1] Federal Geographic Data Committee. Content standard for digital geospatial metadata. Federal Geographic Data Committee, 1998. [2] Devarakonda, Ranjeet, et al. "Mercury: reusable metadata management, data discovery and access system." Earth Science Informatics 3.1-2 (2010): 87-94. [3] Wilson, B. E., Palanisamy, G., Devarakonda, R., Rhyne, B. T., Lindsley, C., & Green, J. (2010). Mercury Toolset for Spatiotemporal Metadata. [4] Pouchard, L. C., Branstetter, M. L., Cook, R. B., Devarakonda, R., Green, J., Palanisamy, G., ... & Noy, N. F. (2013). A Linked Science investigation: enhancing climate change data discovery with semantic technologies. Earth science informatics, 6(3), 175-185.« less

Electronic Collection Management and Electronic Information Services

DTIC Science & Technology

2004-12-01

federated search tools are still being perfected with much debate surrounding their use. Encouragingly, as the federated search tools have evolved...institutional repositories to be included in a federated search process, libraries would have to harvest the metadata from the repositories and then make...providers in Library High Tech News. At this time, federated search engines serve some user groups better than others. Undergraduate students are well

Estimating pediatric entrance skin dose from digital radiography examination using DICOM metadata: A quality assurance tool.

PubMed

Brady, S L; Kaufman, R A

2015-05-01

To develop an automated methodology to estimate patient examination dose in digital radiography (DR) imaging using DICOM metadata as a quality assurance (QA) tool. Patient examination and demographical information were gathered from metadata analysis of DICOM header data. The x-ray system radiation output (i.e., air KERMA) was characterized for all filter combinations used for patient examinations. Average patient thicknesses were measured for head, chest, abdomen, knees, and hands using volumetric images from CT. Backscatter factors (BSFs) were calculated from examination kVp. Patient entrance skin air KERMA (ESAK) was calculated by (1) looking up examination technique factors taken from DICOM header metadata (i.e., kVp and mA s) to derive an air KERMA (k air) value based on an x-ray characteristic radiation output curve; (2) scaling k air with a BSF value; and (3) correcting k air for patient thickness. Finally, patient entrance skin dose (ESD) was calculated by multiplying a mass-energy attenuation coefficient ratio by ESAK. Patient ESD calculations were computed for common DR examinations at our institution: dual view chest, anteroposterior (AP) abdomen, lateral (LAT) skull, dual view knee, and bone age (left hand only) examinations. ESD was calculated for a total of 3794 patients; mean age was 11 ± 8 yr (range: 2 months to 55 yr). The mean ESD range was 0.19-0.42 mGy for dual view chest, 0.28-1.2 mGy for AP abdomen, 0.18-0.65 mGy for LAT view skull, 0.15-0.63 mGy for dual view knee, and 0.10-0.12 mGy for bone age (left hand) examinations. A methodology combining DICOM header metadata and basic x-ray tube characterization curves was demonstrated. In a regulatory era where patient dose reporting has become increasingly in demand, this methodology will allow a knowledgeable user the means to establish an automatable dose reporting program for DR and perform patient dose related QA testing for digital x-ray imaging.

The Risa R/Bioconductor package: integrative data analysis from experimental metadata and back again.

PubMed

González-Beltrán, Alejandra; Neumann, Steffen; Maguire, Eamonn; Sansone, Susanna-Assunta; Rocca-Serra, Philippe

2014-01-01

The ISA-Tab format and software suite have been developed to break the silo effect induced by technology-specific formats for a variety of data types and to better support experimental metadata tracking. Experimentalists seldom use a single technique to monitor biological signals. Providing a multi-purpose, pragmatic and accessible format that abstracts away common constructs for describing Investigations, Studies and Assays, ISA is increasingly popular. To attract further interest towards the format and extend support to ensure reproducible research and reusable data, we present the Risa package, which delivers a central component to support the ISA format by enabling effortless integration with R, the popular, open source data crunching environment. The Risa package bridges the gap between the metadata collection and curation in an ISA-compliant way and the data analysis using the widely used statistical computing environment R. The package offers functionality for: i) parsing ISA-Tab datasets into R objects, ii) augmenting annotation with extra metadata not explicitly stated in the ISA syntax; iii) interfacing with domain specific R packages iv) suggesting potentially useful R packages available in Bioconductor for subsequent processing of the experimental data described in the ISA format; and finally v) saving back to ISA-Tab files augmented with analysis specific metadata from R. We demonstrate these features by presenting use cases for mass spectrometry data and DNA microarray data. The Risa package is open source (with LGPL license) and freely available through Bioconductor. By making Risa available, we aim to facilitate the task of processing experimental data, encouraging a uniform representation of experimental information and results while delivering tools for ensuring traceability and provenance tracking. The Risa package is available since Bioconductor 2.11 (version 1.0.0) and version 1.2.1 appeared in Bioconductor 2.12, both along with documentation and examples. The latest version of the code is at the development branch in Bioconductor and can also be accessed from GitHub https://github.com/ISA-tools/Risa, where the issue tracker allows users to report bugs or feature requests.

Estimating pediatric entrance skin dose from digital radiography examination using DICOM metadata: A quality assurance tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brady, S. L., E-mail: samuel.brady@stjude.org; Kaufman, R. A., E-mail: robert.kaufman@stjude.org

Purpose: To develop an automated methodology to estimate patient examination dose in digital radiography (DR) imaging using DICOM metadata as a quality assurance (QA) tool. Methods: Patient examination and demographical information were gathered from metadata analysis of DICOM header data. The x-ray system radiation output (i.e., air KERMA) was characterized for all filter combinations used for patient examinations. Average patient thicknesses were measured for head, chest, abdomen, knees, and hands using volumetric images from CT. Backscatter factors (BSFs) were calculated from examination kVp. Patient entrance skin air KERMA (ESAK) was calculated by (1) looking up examination technique factors taken frommore » DICOM header metadata (i.e., kVp and mA s) to derive an air KERMA (k{sub air}) value based on an x-ray characteristic radiation output curve; (2) scaling k{sub air} with a BSF value; and (3) correcting k{sub air} for patient thickness. Finally, patient entrance skin dose (ESD) was calculated by multiplying a mass–energy attenuation coefficient ratio by ESAK. Patient ESD calculations were computed for common DR examinations at our institution: dual view chest, anteroposterior (AP) abdomen, lateral (LAT) skull, dual view knee, and bone age (left hand only) examinations. Results: ESD was calculated for a total of 3794 patients; mean age was 11 ± 8 yr (range: 2 months to 55 yr). The mean ESD range was 0.19–0.42 mGy for dual view chest, 0.28–1.2 mGy for AP abdomen, 0.18–0.65 mGy for LAT view skull, 0.15–0.63 mGy for dual view knee, and 0.10–0.12 mGy for bone age (left hand) examinations. Conclusions: A methodology combining DICOM header metadata and basic x-ray tube characterization curves was demonstrated. In a regulatory era where patient dose reporting has become increasingly in demand, this methodology will allow a knowledgeable user the means to establish an automatable dose reporting program for DR and perform patient dose related QA testing for digital x-ray imaging.« less

The Risa R/Bioconductor package: integrative data analysis from experimental metadata and back again

PubMed Central

2014-01-01

Background The ISA-Tab format and software suite have been developed to break the silo effect induced by technology-specific formats for a variety of data types and to better support experimental metadata tracking. Experimentalists seldom use a single technique to monitor biological signals. Providing a multi-purpose, pragmatic and accessible format that abstracts away common constructs for describing Investigations, Studies and Assays, ISA is increasingly popular. To attract further interest towards the format and extend support to ensure reproducible research and reusable data, we present the Risa package, which delivers a central component to support the ISA format by enabling effortless integration with R, the popular, open source data crunching environment. Results The Risa package bridges the gap between the metadata collection and curation in an ISA-compliant way and the data analysis using the widely used statistical computing environment R. The package offers functionality for: i) parsing ISA-Tab datasets into R objects, ii) augmenting annotation with extra metadata not explicitly stated in the ISA syntax; iii) interfacing with domain specific R packages iv) suggesting potentially useful R packages available in Bioconductor for subsequent processing of the experimental data described in the ISA format; and finally v) saving back to ISA-Tab files augmented with analysis specific metadata from R. We demonstrate these features by presenting use cases for mass spectrometry data and DNA microarray data. Conclusions The Risa package is open source (with LGPL license) and freely available through Bioconductor. By making Risa available, we aim to facilitate the task of processing experimental data, encouraging a uniform representation of experimental information and results while delivering tools for ensuring traceability and provenance tracking. Software availability The Risa package is available since Bioconductor 2.11 (version 1.0.0) and version 1.2.1 appeared in Bioconductor 2.12, both along with documentation and examples. The latest version of the code is at the development branch in Bioconductor and can also be accessed from GitHub https://github.com/ISA-tools/Risa, where the issue tracker allows users to report bugs or feature requests. PMID:24564732

Multi-facetted Metadata - Describing datasets with different metadata schemas at the same time

NASA Astrophysics Data System (ADS)

Ulbricht, Damian; Klump, Jens; Bertelmann, Roland

2013-04-01

Inspired by the wish to re-use research data a lot of work is done to bring data systems of the earth sciences together. Discovery metadata is disseminated to data portals to allow building of customized indexes of catalogued dataset items. Data that were once acquired in the context of a scientific project are open for reappraisal and can now be used by scientists that were not part of the original research team. To make data re-use easier, measurement methods and measurement parameters must be documented in an application metadata schema and described in a written publication. Linking datasets to publications - as DataCite [1] does - requires again a specific metadata schema and every new use context of the measured data may require yet another metadata schema sharing only a subset of information with the meta information already present. To cope with the problem of metadata schema diversity in our common data repository at GFZ Potsdam we established a solution to store file-based research data and describe these with an arbitrary number of metadata schemas. Core component of the data repository is an eSciDoc infrastructure that provides versioned container objects, called eSciDoc [2] "items". The eSciDoc content model allows assigning files to "items" and adding any number of metadata records to these "items". The eSciDoc items can be submitted, revised, and finally published, which makes the data and metadata available through the internet worldwide. GFZ Potsdam uses eSciDoc to support its scientific publishing workflow, including mechanisms for data review in peer review processes by providing temporary web links for external reviewers that do not have credentials to access the data. Based on the eSciDoc API, panMetaDocs [3] provides a web portal for data management in research projects. PanMetaDocs, which is based on panMetaWorks [4], is a PHP based web application that allows to describe data with any XML-based schema. It uses the eSciDoc infrastructures REST-interface to store versioned dataset files and metadata in a XML-format. The software is able to administrate more than one eSciDoc metadata record per item and thus allows the description of a dataset according to its context. The metadata fields can be filled with static or dynamic content to reduce the number of fields that require manual entries to a minimum and, at the same time, make use of contextual information available in a project setting. Access rights can be adjusted to set visibility of datasets to the required degree of openness. Metadata from separate instances of panMetaDocs can be syndicated to portals through RSS and OAI-PMH interfaces. The application architecture presented here allows storing file-based datasets and describe these datasets with any number of metadata schemas, depending on the intended use case. Data and metadata are stored in the same entity (eSciDoc items) and are managed by a software tool through the eSciDoc REST interface - in this case the application is panMetaDocs. Other software may re-use the produced items and modify the appropriate metadata records by accessing the web API of the eSciDoc data infrastructure. For presentation of the datasets in a web browser we are not bound to panMetaDocs. This is done by stylesheet transformation of the eSciDoc-item. [1] http://www.datacite.org [2] http://www.escidoc.org , eSciDoc, FIZ Karlruhe, Germany [3] http://panmetadocs.sf.net , panMetaDocs, GFZ Potsdam, Germany [4] http://metaworks.pangaea.de , panMetaWorks, Dr. R. Huber, MARUM, Univ. Bremen, Germany

PGP repository: a plant phenomics and genomics data publication infrastructure.

PubMed

Arend, Daniel; Junker, Astrid; Scholz, Uwe; Schüler, Danuta; Wylie, Juliane; Lange, Matthias

2016-01-01

Plant genomics and phenomics represents the most promising tools for accelerating yield gains and overcoming emerging crop productivity bottlenecks. However, accessing this wealth of plant diversity requires the characterization of this material using state-of-the-art genomic, phenomic and molecular technologies and the release of subsequent research data via a long-term stable, open-access portal. Although several international consortia and public resource centres offer services for plant research data management, valuable digital assets remains unpublished and thus inaccessible to the scientific community. Recently, the Leibniz Institute of Plant Genetics and Crop Plant Research and the German Plant Phenotyping Network have jointly initiated the Plant Genomics and Phenomics Research Data Repository (PGP) as infrastructure to comprehensively publish plant research data. This covers in particular cross-domain datasets that are not being published in central repositories because of its volume or unsupported data scope, like image collections from plant phenotyping and microscopy, unfinished genomes, genotyping data, visualizations of morphological plant models, data from mass spectrometry as well as software and documents.The repository is hosted at Leibniz Institute of Plant Genetics and Crop Plant Research using e!DAL as software infrastructure and a Hierarchical Storage Management System as data archival backend. A novel developed data submission tool was made available for the consortium that features a high level of automation to lower the barriers of data publication. After an internal review process, data are published as citable digital object identifiers and a core set of technical metadata is registered at DataCite. The used e!DAL-embedded Web frontend generates for each dataset a landing page and supports an interactive exploration. PGP is registered as research data repository at BioSharing.org, re3data.org and OpenAIRE as valid EU Horizon 2020 open data archive. Above features, the programmatic interface and the support of standard metadata formats, enable PGP to fulfil the FAIR data principles-findable, accessible, interoperable, reusable.Database URL:http://edal.ipk-gatersleben.de/repos/pgp/. © The Author(s) 2016. Published by Oxford University Press.

ReGaTE: Registration of Galaxy Tools in Elixir

PubMed Central

Mareuil, Fabien; Deveaud, Eric; Kalaš, Matúš; Soranzo, Nicola; van den Beek, Marius; Grüning, Björn; Ison, Jon; Ménager, Hervé

2017-01-01

Abstract Background: Bioinformaticians routinely use multiple software tools and data sources in their day-to-day work and have been guided in their choices by a number of cataloguing initiatives. The ELIXIR Tools and Data Services Registry (bio.tools) aims to provide a central information point, independent of any specific scientific scope within bioinformatics or technological implementation. Meanwhile, efforts to integrate bioinformatics software in workbench and workflow environments have accelerated to enable the design, automation, and reproducibility of bioinformatics experiments. One such popular environment is the Galaxy framework, with currently more than 80 publicly available Galaxy servers around the world. In the context of a generic registry for bioinformatics software, such as bio.tools, Galaxy instances constitute a major source of valuable content. Yet there has been, to date, no convenient mechanism to register such services en masse. Findings: We present ReGaTE (Registration of Galaxy Tools in Elixir), a software utility that automates the process of registering the services available in a Galaxy instance. This utility uses the BioBlend application program interface to extract service metadata from a Galaxy server, enhance the metadata with the scientific information required by bio.tools, and push it to the registry. Conclusions: ReGaTE provides a fast and convenient way to publish Galaxy services in bio.tools. By doing so, service providers may increase the visibility of their services while enriching the software discovery function that bio.tools provides for its users. The source code of ReGaTE is freely available on Github at https://github.com/C3BI-pasteur-fr/ReGaTE. PMID:28402416

Accessing Data Federations with CVMFS

DOE PAGES

Weitzel, Derek; Bockelman, Brian; Dykstra, Dave; ...

2017-11-23

Data federations have become an increasingly common tool for large collaborations such as CMS and Atlas to efficiently distribute large data files. Unfortunately, these typically are implemented with weak namespace semantics and a non-POSIX API. On the other hand, CVMFS has provided a POSIX-compliant read-only interface for use cases with a small working set size (such as software distribution). The metadata required for the CVMFS POSIX interface is distributed through a caching hierarchy, allowing it to scale to the level of about a hundred thousand hosts. In this paper, we will describe our contributions to CVMFS that merges the datamore » scalability of XRootD-based data federations (such as AAA) with metadata scalability and POSIX interface of CVMFS. We modified CVMFS so it can serve unmodified files without copying them to the repository server. CVMFS 2.2.0 is also able to redirect requests for data files to servers outside of the CVMFS content distribution network. Finally, we added the ability to manage authorization and authentication using security credentials such as X509 proxy certificates. We combined these modifications with the OSGs StashCache regional XRootD caching infrastructure to create a cached data distribution network. Here, we will show performance metrics accessing the data federation through CVMFS compared to direct data federation access. Additionally, we will discuss the improved user experience of providing access to a data federation through a POSIX filesystem.« less

Accessing Data Federations with CVMFS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weitzel, Derek; Bockelman, Brian; Dykstra, Dave

Data federations have become an increasingly common tool for large collaborations such as CMS and Atlas to efficiently distribute large data files. Unfortunately, these typically are implemented with weak namespace semantics and a non-POSIX API. On the other hand, CVMFS has provided a POSIX-compliant read-only interface for use cases with a small working set size (such as software distribution). The metadata required for the CVMFS POSIX interface is distributed through a caching hierarchy, allowing it to scale to the level of about a hundred thousand hosts. In this paper, we will describe our contributions to CVMFS that merges the datamore » scalability of XRootD-based data federations (such as AAA) with metadata scalability and POSIX interface of CVMFS. We modified CVMFS so it can serve unmodified files without copying them to the repository server. CVMFS 2.2.0 is also able to redirect requests for data files to servers outside of the CVMFS content distribution network. Finally, we added the ability to manage authorization and authentication using security credentials such as X509 proxy certificates. We combined these modifications with the OSGs StashCache regional XRootD caching infrastructure to create a cached data distribution network. Here, we will show performance metrics accessing the data federation through CVMFS compared to direct data federation access. Additionally, we will discuss the improved user experience of providing access to a data federation through a POSIX filesystem.« less

Accessing Data Federations with CVMFS

NASA Astrophysics Data System (ADS)

Weitzel, Derek; Bockelman, Brian; Dykstra, Dave; Blomer, Jakob; Meusel, Ren

2017-10-01

Data federations have become an increasingly common tool for large collaborations such as CMS and Atlas to efficiently distribute large data files. Unfortunately, these typically are implemented with weak namespace semantics and a non-POSIX API. On the other hand, CVMFS has provided a POSIX-compliant read-only interface for use cases with a small working set size (such as software distribution). The metadata required for the CVMFS POSIX interface is distributed through a caching hierarchy, allowing it to scale to the level of about a hundred thousand hosts. In this paper, we will describe our contributions to CVMFS that merges the data scalability of XRootD-based data federations (such as AAA) with metadata scalability and POSIX interface of CVMFS. We modified CVMFS so it can serve unmodified files without copying them to the repository server. CVMFS 2.2.0 is also able to redirect requests for data files to servers outside of the CVMFS content distribution network. Finally, we added the ability to manage authorization and authentication using security credentials such as X509 proxy certificates. We combined these modifications with the OSGs StashCache regional XRootD caching infrastructure to create a cached data distribution network. We will show performance metrics accessing the data federation through CVMFS compared to direct data federation access. Additionally, we will discuss the improved user experience of providing access to a data federation through a POSIX filesystem.

DataUp: Helping manage and archive data within the researcher's workflow

NASA Astrophysics Data System (ADS)

Strasser, C.

2012-12-01

There are many barriers to data management and sharing among earth and environmental scientists; among the most significant are lacks of knowledge about best practices for data management, metadata standards, or appropriate data repositories for archiving and sharing data. We have developed an open-source add-in for Excel and an open source web application intended to help researchers overcome these barriers. DataUp helps scientists to (1) determine whether their file is CSV compatible, (2) generate metadata in a standard format, (3) retrieve an identifier to facilitate data citation, and (4) deposit their data into a repository. The researcher does not need a prior relationship with a data repository to use DataUp; the newly implemented ONEShare repository, a DataONE member node, is available for any researcher to archive and share their data. By meeting researchers where they already work, in spreadsheets, DataUp becomes part of the researcher's workflow and data management and sharing becomes easier. Future enhancement of DataUp will rely on members of the community adopting and adapting the DataUp tools to meet their unique needs, including connecting to analytical tools, adding new metadata schema, and expanding the list of connected data repositories. DataUp is a collaborative project between Microsoft Research Connections, the University of California's California Digital Library, the Gordon and Betty Moore Foundation, and DataONE.

HELIOGate, a Portal for the Heliophysics Community

NASA Astrophysics Data System (ADS)

Pierantoni; Gabriele; Carley, Eoin

2014-10-01

Heliophysics is the branch of physics that investigates the interactions between the Sun and the other bodies of the solar system. Heliophysicists rely on data collected from numerous sources scattered across the Solar System. The data collected from these sources is processed to extract metadata and the metadata extracted in this fashion is then used to build indexes of features and events called catalogues. Heliophysicists also develop conceptual and mathematical models of the phenomena and the environment of the Solar System. More specifically, they investigate the physical characteristics of the phenomena and they simulate how they propagate throughout the Solar System with mathematical and physical abstractions called propagation models. HELIOGate aims at addressing the need to combine and orchestrate existing web services in a flexible and easily configurable fashion to tackle different scientific questions. HELIOGate also offers a tool capable of connecting to size! able computation and storage infrastructures to execute data processing codes that are needed to calibrate raw data and to extract metadata.

Documenting Climate Models and Their Simulations

DOE PAGES

Guilyardi, Eric; Balaji, V.; Lawrence, Bryan; ...

2013-05-01

The results of climate models are of increasing and widespread importance. No longer is climate model output of sole interest to climate scientists and researchers in the climate change impacts and adaptation fields. Now nonspecialists such as government officials, policy makers, and the general public all have an increasing need to access climate model output and understand its implications. For this host of users, accurate and complete metadata (i.e., information about how and why the data were produced) is required to document the climate modeling results. We describe a pilot community initiative to collect and make available documentation of climatemore » models and their simulations. In an initial application, a metadata repository is being established to provide information of this kind for a major internationally coordinated modeling activity known as CMIP5 (Coupled Model Intercomparison Project, Phase 5). We expected that for a wide range of stakeholders, this and similar community-managed metadata repositories will spur development of analysis tools that facilitate discovery and exploitation of Earth system simulations.« less

The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification

PubMed Central

Reddy, T.B.K.; Thomas, Alex D.; Stamatis, Dimitri; Bertsch, Jon; Isbandi, Michelle; Jansson, Jakob; Mallajosyula, Jyothi; Pagani, Ioanna; Lobos, Elizabeth A.; Kyrpides, Nikos C.

2015-01-01

The Genomes OnLine Database (GOLD; http://www.genomesonline.org) is a comprehensive online resource to catalog and monitor genetic studies worldwide. GOLD provides up-to-date status on complete and ongoing sequencing projects along with a broad array of curated metadata. Here we report version 5 (v.5) of the database. The newly designed database schema and web user interface supports several new features including the implementation of a four level (meta)genome project classification system and a simplified intuitive web interface to access reports and launch search tools. The database currently hosts information for about 19 200 studies, 56 000 Biosamples, 56 000 sequencing projects and 39 400 analysis projects. More than just a catalog of worldwide genome projects, GOLD is a manually curated, quality-controlled metadata warehouse. The problems encountered in integrating disparate and varying quality data into GOLD are briefly highlighted. GOLD fully supports and follows the Genomic Standards Consortium (GSC) Minimum Information standards. PMID:25348402

The IceBridge Portal - Automated Metadata Generation for Enhanced Data Access

NASA Astrophysics Data System (ADS)

Tanner, S.; Schwab, M.; Beam, K.; Deems, J. S.; Fitzgerrell, A.

2016-12-01

NASA's Operation IceBridge (OIB) mission, initiated in 2009, collects airborne remote sensing measurements over the polar regions to bridge the gap between NASA's Ice, Cloud and Land Elevation satellite (ICESat) mission and the upcoming ICESat-2 mission in 2017. OIB combines an evolving mix of instruments to gather data on topography, ice and snow thickness, high-resolution photography, and other properties that are more difficult or impossible to measure via satellite. Once collected, these data are stored and made available at the National Snow and Ice Data Center (NSIDC) in Boulder, Colorado. To date, there are nearly 200 terabytes of data available, and with several more campaigns to go. Initially, OIB data could be difficult to discover and access, due to a lack of consistent metadata. However, the Project Office made a decision to revamp the data delivery process. This has led to substantial data reformatting and better adherence to NASA standards as well as the generation of far more metadata associated with each data product. Because of this change, NSIDC has been able to develop a powerful map-based portal for search, discovery and access of these data products. The tools used for automated metadata generation, and the resulting new data portal will be presented.

Development of a Searchable Metabolite Database and Simulator of Xenobiotic Metabolism

EPA Science Inventory

A computational tool (MetaPath) has been developed for storage and analysis of metabolic pathways and associated metadata. The system is capable of sophisticated text and chemical structure/substructure searching as well as rapid comparison of metabolites formed across chemicals,...

ASIS '99 Knowledge: Creation, Organization and Use, Part II: SIG Sessions.

ERIC Educational Resources Information Center

Proceedings of the ASIS Annual Meeting, 1999

1999-01-01

Abstracts and descriptions of Special Interest Group (SIG) sessions include such topics as: knowledge management tools, knowledge organization, information retrieval, information seeking behavior, metadata, indexing, library service for distance education, electronic books, future information workforce needs, technological developments, and…

Towards Making Data Bases Practical for use in the Field

NASA Astrophysics Data System (ADS)

Fischer, T. P.; Lehnert, K. A.; Chiodini, G.; McCormick, B.; Cardellini, C.; Clor, L. E.; Cottrell, E.

2014-12-01

Geological, geochemical, and geophysical research is often field based with travel to remote areas and collection of samples and data under challenging environmental conditions. Cross-disciplinary investigations would greatly benefit from near real-time data access and visualisation within the existing framework of databases and GIS tools. An example of complex, interdisciplinary field-based and data intensive investigations is that of volcanologists and gas geochemists, who sample gases from fumaroles, hot springs, dry gas vents, hydrothermal vents and wells. Compositions of volcanic gas plumes are measured directly or by remote sensing. Soil gas fluxes from volcanic areas are measured by accumulation chamber and involve hundreds of measurements to calculate the total emission of a region. Many investigators also collect rock samples from recent or ancient volcanic eruptions. Structural, geochronological, and geophysical data collected during the same or related field campaigns complement these emissions data. All samples and data collected in the field require a set of metadata including date, time, location, sample or measurement id, and descriptive comments. Currently, most of these metadata are written in field notebooks and later transferred into a digital format. Final results such as laboratory analyses of samples and calculated flux data are tabulated for plotting, correlation with other types of data, modeling and finally publication and presentation. Data handling, organization and interpretation could be greatly streamlined by using digital tools available in the field to record metadata, assign an International Geo Sample Number (IGSN), upload measurements directly from field instruments, and arrange sample curation. Available data display tools such as GeoMapApp and existing data sets (PetDB, IRIS, UNAVCO) could be integrated to direct locations for additional measurements during a field campaign. Nearly live display of sampling locations, pictures, and comments could be used as an educational and outreach tool during sampling expeditions. Achieving these goals requires the integration of existing online data resources, with common access through a dedicated web portal.

Data System for HS3 Airborne Field Campaign

NASA Astrophysics Data System (ADS)

Maskey, M.; Mceniry, M.; Berendes, T.; Bugbee, K.; Conover, H.; Ramachandran, R.

2014-12-01

Hurricane and Severe Storm Sentinel (HS3) is a NASA airborne field campaign aimed at better understanding the physical processes that control hurricane intensity change. HS3 will help answer questions related to the roles of environmental conditions and internal storm structures to storm intensification. Due to the nature of the questions that HS3 mission is addressing, it involves a variety of in-situ, satellite observations, airborne data, meteorological analyses, and simulation data. This variety of datasets presents numerous data management challenges for HS3. The methods used for airborne data management differ greatly from the methods used for space-borne data. In particular, metadata extraction, spatial and temporal indexing, and the large number of instruments and subsequent variables are a few of the data management challenges unique to airborne missions. A robust data system is required to successfully help HS3 scientist achieve their mission goals. Furthermore, the data system also needs to provide for data management that assists in broader use of HS3 data to enable future research activities. The Global Hydrology Resource Center (GHRC) is considering all these needs and designing a data system for HS3. Experience with past airborne field campaign puts GHRC in a good position to address HS3 needs. However, the scale of this mission along with science requirements separates HS3 from previous field campaigns. The HS3 data system will include automated services for geo-location, metadata extraction, discovery, and distribution for all HS3 data. To answer the science questions, the data system will include a visual data exploration tool that is fully integrated into the data catalog. The tool will allow visually augmenting airborne data with analyses and simulations. Satellite data will provide contextual information during such data explorations. All HS3 tools will be supported by an enterprise service architecture that will allow scaling, easy integration of new tools and existing services, and integration of new ESDIS metadata and security guidelines.

DUBLIN CORE

EPA Science Inventory

The Dublin Core is a metadata element set intended to facilitate discovery of electronic resources. It was originally conceived for author-generated descriptions of Web resources, and the Dublin Core has attracted broad ranging international and interdisciplinary support. The cha...

Study on Information Management for the Conservation of Traditional Chinese Architectural Heritage - 3d Modelling and Metadata Representation

NASA Astrophysics Data System (ADS)

Yen, Y. N.; Weng, K. H.; Huang, H. Y.

2013-07-01

After over 30 years of practise and development, Taiwan's architectural conservation field is moving rapidly into digitalization and its applications. Compared to modern buildings, traditional Chinese architecture has considerably more complex elements and forms. To document and digitize these unique heritages in their conservation lifecycle is a new and important issue. This article takes the caisson ceiling of the Taipei Confucius Temple, octagonal with 333 elements in 8 types, as a case study for digitization practise. The application of metadata representation and 3D modelling are the two key issues to discuss. Both Revit and SketchUp were appliedin this research to compare its effectiveness to metadata representation. Due to limitation of the Revit database, the final 3D models wasbuilt with SketchUp. The research found that, firstly, cultural heritage databasesmustconvey that while many elements are similar in appearance, they are unique in value; although 3D simulations help the general understanding of architectural heritage, software such as Revit and SketchUp, at this stage, could onlybe used tomodel basic visual representations, and is ineffective indocumenting additional critical data ofindividually unique elements. Secondly, when establishing conservation lifecycle information for application in management systems, a full and detailed presentation of the metadata must also be implemented; the existing applications of BIM in managing conservation lifecycles are still insufficient. Results of the research recommends SketchUp as a tool for present modelling needs, and BIM for sharing data between users, but the implementation of metadata representation is of the utmost importance.

Unified Science Information Model for SoilSCAPE using the Mercury Metadata Search System

NASA Astrophysics Data System (ADS)

Devarakonda, Ranjeet; Lu, Kefa; Palanisamy, Giri; Cook, Robert; Santhana Vannan, Suresh; Moghaddam, Mahta Clewley, Dan; Silva, Agnelo; Akbar, Ruzbeh

2013-12-01

SoilSCAPE (Soil moisture Sensing Controller And oPtimal Estimator) introduces a new concept for a smart wireless sensor web technology for optimal measurements of surface-to-depth profiles of soil moisture using in-situ sensors. The objective is to enable a guided and adaptive sampling strategy for the in-situ sensor network to meet the measurement validation objectives of spaceborne soil moisture sensors such as the Soil Moisture Active Passive (SMAP) mission. This work is being carried out at the University of Michigan, the Massachusetts Institute of Technology, University of Southern California, and Oak Ridge National Laboratory. At Oak Ridge National Laboratory we are using Mercury metadata search system [1] for building a Unified Information System for the SoilSCAPE project. This unified portal primarily comprises three key pieces: Distributed Search/Discovery; Data Collections and Integration; and Data Dissemination. Mercury, a Federally funded software for metadata harvesting, indexing, and searching would be used for this module. Soil moisture data sources identified as part of this activity such as SoilSCAPE and FLUXNET (in-situ sensors), AirMOSS (airborne retrieval), SMAP (spaceborne retrieval), and are being indexed and maintained by Mercury. Mercury would be the central repository of data sources for cal/val for soil moisture studies and would provide a mechanism to identify additional data sources. Relevant metadata from existing inventories such as ORNL DAAC, USGS Clearinghouse, ARM, NASA ECHO, GCMD etc. would be brought in to this soil-moisture data search/discovery module. The SoilSCAPE [2] metadata records will also be published in broader metadata repositories such as GCMD, data.gov. Mercury can be configured to provide a single portal to soil moisture information contained in disparate data management systems located anywhere on the Internet. Mercury is able to extract, metadata systematically from HTML pages or XML files using a variety of methods including OAI-PMH [3]. The Mercury search interface then allows users to perform simple, fielded, spatial and temporal searches across a central harmonized index of metadata. Mercury supports various metadata standards including FGDC, ISO-19115, DIF, Dublin-Core, Darwin-Core, and EML. This poster describes in detail how Mercury implements the Unified Science Information Model for Soil moisture data. References: [1]Devarakonda R., et al. Mercury: reusable metadata management, data discovery and access system. Earth Science Informatics (2010), 3(1): 87-94. [2]Devarakonda R., et al. Daymet: Single Pixel Data Extraction Tool. http://daymet.ornl.gov/singlepixel.html (2012). Last Accesses 10-01-2013 [3]Devarakonda R., et al. Data sharing and retrieval using OAI-PMH. Earth Science Informatics (2011), 4(1): 1-5.

Automatic publishing ISO 19115 metadata with PanMetaDocs using SensorML information

NASA Astrophysics Data System (ADS)

Stender, Vivien; Ulbricht, Damian; Schroeder, Matthias; Klump, Jens

2014-05-01

Terrestrial Environmental Observatories (TERENO) is an interdisciplinary and long-term research project spanning an Earth observation network across Germany. It includes four test sites within Germany from the North German lowlands to the Bavarian Alps and is operated by six research centers of the Helmholtz Association. The contribution by the participating research centers is organized as regional observatories. A challenge for TERENO and its observatories is to integrate all aspects of data management, data workflows, data modeling and visualizations into the design of a monitoring infrastructure. TERENO Northeast is one of the sub-observatories of TERENO and is operated by the German Research Centre for Geosciences (GFZ) in Potsdam. This observatory investigates geoecological processes in the northeastern lowland of Germany by collecting large amounts of environmentally relevant data. The success of long-term projects like TERENO depends on well-organized data management, data exchange between the partners involved and on the availability of the captured data. Data discovery and dissemination are facilitated not only through data portals of the regional TERENO observatories but also through a common spatial data infrastructure TEODOOR (TEreno Online Data repOsitORry). TEODOOR bundles the data, provided by the different web services of the single observatories, and provides tools for data discovery, visualization and data access. The TERENO Northeast data infrastructure integrates data from more than 200 instruments and makes data available through standard web services. Geographic sensor information and services are described using the ISO 19115 metadata schema. TEODOOR accesses the OGC Sensor Web Enablement (SWE) interfaces offered by the regional observatories. In addition to the SWE interface, TERENO Northeast also published data through DataCite. The necessary metadata are created in an automated process by extracting information from the SWE SensorML to create ISO 19115 compliant metadata. The resulting metadata file is stored in the GFZ Potsdam data infrastructure. The publishing workflow for file based research datasets at GFZ Potsdam is based on the eSciDoc infrastructure, using PanMetaDocs (PMD) as the graphical user interface. PMD is a collaborative, metadata based data and information exchange platform [1]. Besides SWE, metadata are also syndicated by PMD through an OAI-PMH interface. In addition, metadata from other observatories, projects or sensors in TERENO can be accessed through the TERENO Northeast data portal. [1] http://meetingorganizer.copernicus.org/EGU2012/EGU2012-7058-2.pdf

Definition of an ISO 19115 metadata profile for SeaDataNet II Cruise Summary Reports and its XML encoding

NASA Astrophysics Data System (ADS)

Boldrini, Enrico; Schaap, Dick M. A.; Nativi, Stefano

2013-04-01

SeaDataNet implements a distributed pan-European infrastructure for Ocean and Marine Data Management whose nodes are maintained by 40 national oceanographic and marine data centers from 35 countries riparian to all European seas. A unique portal makes possible distributed discovery, visualization and access of the available sea data across all the member nodes. Geographic metadata play an important role in such an infrastructure, enabling an efficient documentation and discovery of the resources of interest. In particular: - Common Data Index (CDI) metadata describe the sea datasets, including identification information (e.g. product title, interested area), evaluation information (e.g. data resolution, constraints) and distribution information (e.g. download endpoint, download protocol); - Cruise Summary Reports (CSR) metadata describe cruises and field experiments at sea, including identification information (e.g. cruise title, name of the ship), acquisition information (e.g. utilized instruments, number of samples taken) In the context of the second phase of SeaDataNet (SeaDataNet 2 EU FP7 project, grant agreement 283607, started on October 1st, 2011 for a duration of 4 years) a major target is the setting, adoption and promotion of common international standards, to the benefit of outreach and interoperability with the international initiatives and communities (e.g. OGC, INSPIRE, GEOSS, …). A standardization effort conducted by CNR with the support of MARIS, IFREMER, STFC, BODC and ENEA has led to the creation of a ISO 19115 metadata profile of CDI and its XML encoding based on ISO 19139. The CDI profile is now in its stable version and it's being implemented and adopted by the SeaDataNet community tools and software. The effort has then continued to produce an ISO based metadata model and its XML encoding also for CSR. The metadata elements included in the CSR profile belong to different models: - ISO 19115: E.g. cruise identification information, including title and area of interest; metadata responsible party information - ISO 19115-2: E.g. acquisition information, including date of sampling, instruments used - SeaDataNet: E.g. SeaDataNet community specific, including EDMO and EDMERP code lists Two main guidelines have been followed in the metadata model drafting: - All the obligations and constraints required by both the ISO standards and INSPIRE directive had to be satisfied. These include the presence of specific elements with given cardinality (e.g. mandatory metadata date stamp, mandatory lineage information) - All the content information of legacy CSR format had to be supported by the new metadata model. An XML encoding of the CSR profile has been defined as well. Based on the ISO 19139 XML schema and constraints, it adds the new elements specific of the SeaDataNet community. The associated Schematron rules are used to enforce constraints not enforceable just with the Schema and to validate elements content against the SeaDataNet code lists vocabularies.

An open annotation ontology for science on web 3.0

PubMed Central

2011-01-01

Background There is currently a gap between the rich and expressive collection of published biomedical ontologies, and the natural language expression of biomedical papers consumed on a daily basis by scientific researchers. The purpose of this paper is to provide an open, shareable structure for dynamic integration of biomedical domain ontologies with the scientific document, in the form of an Annotation Ontology (AO), thus closing this gap and enabling application of formal biomedical ontologies directly to the literature as it emerges. Methods Initial requirements for AO were elicited by analysis of integration needs between biomedical web communities, and of needs for representing and integrating results of biomedical text mining. Analysis of strengths and weaknesses of previous efforts in this area was also performed. A series of increasingly refined annotation tools were then developed along with a metadata model in OWL, and deployed for feedback and additional requirements the ontology to users at a major pharmaceutical company and a major academic center. Further requirements and critiques of the model were also elicited through discussions with many colleagues and incorporated into the work. Results This paper presents Annotation Ontology (AO), an open ontology in OWL-DL for annotating scientific documents on the web. AO supports both human and algorithmic content annotation. It enables “stand-off” or independent metadata anchored to specific positions in a web document by any one of several methods. In AO, the document may be annotated but is not required to be under update control of the annotator. AO contains a provenance model to support versioning, and a set model for specifying groups and containers of annotation. AO is freely available under open source license at http://purl.org/ao/, and extensive documentation including screencasts is available on AO’s Google Code page: http://code.google.com/p/annotation-ontology/ . Conclusions The Annotation Ontology meets critical requirements for an open, freely shareable model in OWL, of annotation metadata created against scientific documents on the Web. We believe AO can become a very useful common model for annotation metadata on Web documents, and will enable biomedical domain ontologies to be used quite widely to annotate the scientific literature. Potential collaborators and those with new relevant use cases are invited to contact the authors. PMID:21624159

An open annotation ontology for science on web 3.0.

PubMed

Ciccarese, Paolo; Ocana, Marco; Garcia Castro, Leyla Jael; Das, Sudeshna; Clark, Tim

2011-05-17

There is currently a gap between the rich and expressive collection of published biomedical ontologies, and the natural language expression of biomedical papers consumed on a daily basis by scientific researchers. The purpose of this paper is to provide an open, shareable structure for dynamic integration of biomedical domain ontologies with the scientific document, in the form of an Annotation Ontology (AO), thus closing this gap and enabling application of formal biomedical ontologies directly to the literature as it emerges. Initial requirements for AO were elicited by analysis of integration needs between biomedical web communities, and of needs for representing and integrating results of biomedical text mining. Analysis of strengths and weaknesses of previous efforts in this area was also performed. A series of increasingly refined annotation tools were then developed along with a metadata model in OWL, and deployed for feedback and additional requirements the ontology to users at a major pharmaceutical company and a major academic center. Further requirements and critiques of the model were also elicited through discussions with many colleagues and incorporated into the work. This paper presents Annotation Ontology (AO), an open ontology in OWL-DL for annotating scientific documents on the web. AO supports both human and algorithmic content annotation. It enables "stand-off" or independent metadata anchored to specific positions in a web document by any one of several methods. In AO, the document may be annotated but is not required to be under update control of the annotator. AO contains a provenance model to support versioning, and a set model for specifying groups and containers of annotation. AO is freely available under open source license at http://purl.org/ao/, and extensive documentation including screencasts is available on AO's Google Code page: http://code.google.com/p/annotation-ontology/ . The Annotation Ontology meets critical requirements for an open, freely shareable model in OWL, of annotation metadata created against scientific documents on the Web. We believe AO can become a very useful common model for annotation metadata on Web documents, and will enable biomedical domain ontologies to be used quite widely to annotate the scientific literature. Potential collaborators and those with new relevant use cases are invited to contact the authors.

mvMapper: statistical and geographical data exploration and visualization of multivariate analysis of population structure

USDA-ARS?s Scientific Manuscript database

Characterizing population genetic structure across geographic space is a fundamental challenge in population genetics. Multivariate statistical analyses are powerful tools for summarizing genetic variability, but geographic information and accompanying metadata is not always easily integrated into t...

Designing and Managing Your Digital Library.

ERIC Educational Resources Information Center

Guenther, Kim

2000-01-01

Discusses digital libraries and Web site design issues. Highlights include accessibility issues, including standards, markup languages like HTML and XML, and metadata; building virtual communities; the use of Web portals for customized delivery of information; quality assurance tools, including data mining; and determining user needs, including…

Automated metadata--final project report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schissel, David

This report summarizes the work of the Automated Metadata, Provenance Cataloging, and Navigable Interfaces: Ensuring the Usefulness of Extreme-Scale Data Project (MPO Project) funded by the United States Department of Energy (DOE), Offices of Advanced Scientific Computing Research and Fusion Energy Sciences. Initially funded for three years starting in 2012, it was extended for 6 months with additional funding. The project was a collaboration between scientists at General Atomics, Lawrence Berkley National Laboratory (LBNL), and Massachusetts Institute of Technology (MIT). The group leveraged existing computer science technology where possible, and extended or created new capabilities where required. The MPO projectmore » was able to successfully create a suite of software tools that can be used by a scientific community to automatically document their scientific workflows. These tools were integrated into workflows for fusion energy and climate research illustrating the general applicability of the project’s toolkit. Feedback was very positive on the project’s toolkit and the value of such automatic workflow documentation to the scientific endeavor.« less

TokSearch: A search engine for fusion experimental data

DOE PAGES

Sammuli, Brian S.; Barr, Jayson L.; Eidietis, Nicholas W.; ...

2018-04-01

At a typical fusion research site, experimental data is stored using archive technologies that deal with each discharge as an independent set of data. These technologies (e.g. MDSplus or HDF5) are typically supplemented with a database that aggregates metadata for multiple shots to allow for efficient querying of certain predefined quantities. Often, however, a researcher will need to extract information from the archives, possibly for many shots, that is not available in the metadata store or otherwise indexed for quick retrieval. To address this need, a new search tool called TokSearch has been added to the General Atomics TokSys controlmore » design and analysis suite [1]. This tool provides the ability to rapidly perform arbitrary, parallelized queries of archived tokamak shot data (both raw and analyzed) over large numbers of shots. The TokSearch query API borrows concepts from SQL, and users can choose to implement queries in either MatlabTM or Python.« less

TokSearch: A search engine for fusion experimental data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sammuli, Brian S.; Barr, Jayson L.; Eidietis, Nicholas W.

At a typical fusion research site, experimental data is stored using archive technologies that deal with each discharge as an independent set of data. These technologies (e.g. MDSplus or HDF5) are typically supplemented with a database that aggregates metadata for multiple shots to allow for efficient querying of certain predefined quantities. Often, however, a researcher will need to extract information from the archives, possibly for many shots, that is not available in the metadata store or otherwise indexed for quick retrieval. To address this need, a new search tool called TokSearch has been added to the General Atomics TokSys controlmore » design and analysis suite [1]. This tool provides the ability to rapidly perform arbitrary, parallelized queries of archived tokamak shot data (both raw and analyzed) over large numbers of shots. The TokSearch query API borrows concepts from SQL, and users can choose to implement queries in either MatlabTM or Python.« less

The STP (Solar-Terrestrial Physics) Semantic Web based on the RSS1.0 and the RDF

NASA Astrophysics Data System (ADS)

Kubo, T.; Murata, K. T.; Kimura, E.; Ishikura, S.; Shinohara, I.; Kasaba, Y.; Watari, S.; Matsuoka, D.

2006-12-01

In the Solar-Terrestrial Physics (STP), it is pointed out that circulation and utilization of observation data among researchers are insufficient. To archive interdisciplinary researches, we need to overcome this circulation and utilization problems. Under such a background, authors' group has developed a world-wide database that manages meta-data of satellite and ground-based observation data files. It is noted that retrieving meta-data from the observation data and registering them to database have been carried out by hand so far. Our goal is to establish the STP Semantic Web. The Semantic Web provides a common framework that allows a variety of data shared and reused across applications, enterprises, and communities. We also expect that the secondary information related with observations, such as event information and associated news, are also shared over the networks. The most fundamental issue on the establishment is who generates, manages and provides meta-data in the Semantic Web. We developed an automatic meta-data collection system for the observation data using the RSS (RDF Site Summary) 1.0. The RSS1.0 is one of the XML-based markup languages based on the RDF (Resource Description Framework), which is designed for syndicating news and contents of news-like sites. The RSS1.0 is used to describe the STP meta-data, such as data file name, file server address and observation date. To describe the meta-data of the STP beyond RSS1.0 vocabulary, we defined original vocabularies for the STP resources using the RDF Schema. The RDF describes technical terms on the STP along with the Dublin Core Metadata Element Set, which is standard for cross-domain information resource descriptions. Researchers' information on the STP by FOAF, which is known as an RDF/XML vocabulary, creates a machine-readable metadata describing people. Using the RSS1.0 as a meta-data distribution method, the workflow from retrieving meta-data to registering them into the database is automated. This technique is applied for several database systems, such as the DARTS database system and NICT Space Weather Report Service. The DARTS is a science database managed by ISAS/JAXA in Japan. We succeeded in generating and collecting the meta-data automatically for the CDF (Common data Format) data, such as Reimei satellite data, provided by the DARTS. We also create an RDF service for space weather report and real-time global MHD simulation 3D data provided by the NICT. Our Semantic Web system works as follows: The RSS1.0 documents generated on the data sites (ISAS and NICT) are automatically collected by a meta-data collection agent. The RDF documents are registered and the agent extracts meta-data to store them in the Sesame, which is an open source RDF database with support for RDF Schema inferencing and querying. The RDF database provides advanced retrieval processing that has considered property and relation. Finally, the STP Semantic Web provides automatic processing or high level search for the data which are not only for observation data but for space weather news, physical events, technical terms and researches information related to the STP.

Web Based Data Access to the World Data Center for Climate

NASA Astrophysics Data System (ADS)

Toussaint, F.; Lautenschlager, M.

2006-12-01

The World Data Center for Climate (WDC-Climate, www.wdc-climate.de) is hosted by the Model &Data Group (M&D) of the Max Planck Institute for Meteorology. The M&D department is financed by the German government and uses the computers and mass storage facilities of the German Climate Computing Centre (Deutsches Klimarechenzentrum, DKRZ). The WDC-Climate provides web access to 200 Terabytes of climate data; the total mass storage archive contains nearly 4 Petabytes. Although the majority of the datasets concern model output data, some satellite and observational data are accessible as well. The underlying relational database is distributed on five servers. The CERA relational data model is used to integrate catalogue data and mass data. The flexibility of the model allows to store and access very different types of data and metadata. The CERA metadata catalogue provides easy access to the content of the CERA database as well as to other data in the web. Visit ceramodel.wdc-climate.de for additional information on the CERA data model. The majority of the users access data via the CERA metadata catalogue, which is open without registration. However, prior to retrieving data user are required to check in and apply for a userid and password. The CERA metadata catalogue is servlet based. So it is accessible worldwide through any web browser at cera.wdc-climate.de. In addition to data and metadata access by the web catalogue, WDC-Climate offers a number of other forms of web based data access. All metadata are available via http request as xml files in various metadata formats (ISO, DC, etc., see wini.wdc-climate.de) which allows for easy data interchange with other catalogues. Model data can be retrieved in GRIB, ASCII, NetCDF, and binary (IEEE) format. WDC-Climate serves as data centre for various projects. Since xml files are accessible by http, the integration of data into applications of different projects is very easy. Projects supported by WDC-Climate are e.g. CEOP, IPCC, and CARIBIC. A script tool for data download (jblob) is offered on the web page, to make retrieval of huge data quantities more comfortable.

CruiseViewer: SIOExplorer Graphical Interface to Metadata and Archives.

NASA Astrophysics Data System (ADS)

Sutton, D. W.; Helly, J. J.; Miller, S. P.; Chase, A.; Clark, D.

2002-12-01

We are introducing "CruiseViewer" as a prototype graphical interface for the SIOExplorer digital library project, part of the overall NSF National Science Digital Library (NSDL) effort. When complete, CruiseViewer will provide access to nearly 800 cruises, as well as 100 years of documents and images from the archives of the Scripps Institution of Oceanography (SIO). The project emphasizes data object accessibility, a rich metadata format, efficient uploading methods and interoperability with other digital libraries. The primary function of CruiseViewer is to provide a human interface to the metadata database and to storage systems filled with archival data. The system schema is based on the concept of an "arbitrary digital object" (ADO). Arbitrary in that if the object can be stored on a computer system then SIOExplore can manage it. Common examples are a multibeam swath bathymetry file, a .pdf cruise report, or a tar file containing all the processing scripts used on a cruise. We require a metadata file for every ADO in an ascii "metadata interchange format" (MIF), which has proven to be highly useful for operability and extensibility. Bulk ADO storage is managed using the Storage Resource Broker, SRB, data handling middleware developed at the San Diego Supercomputer Center that centralizes management and access to distributed storage devices. MIF metadata are harvested from several sources and housed in a relational (Oracle) database. For CruiseViewer, cgi scripts resident on an Apache server are the primary communication and service request handling tools. Along with the CruiseViewer java application, users can query, access and download objects via a separate method that operates through standard web browsers, http://sioexplorer.ucsd.edu. Both provide the functionability to query and view object metadata, and select and download ADOs. For the CruiseViewer application Java 2D is used to add a geo-referencing feature that allows users to select basemap images and have vector shapes representing query results mapped over the basemap in the image panel. The two methods together address a wide range of user access needs and will allow for widespread use of SIOExplorer.

Distributed metadata servers for cluster file systems using shared low latency persistent key-value metadata store

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bent, John M.; Faibish, Sorin; Pedone, Jr., James M.

A cluster file system is provided having a plurality of distributed metadata servers with shared access to one or more shared low latency persistent key-value metadata stores. A metadata server comprises an abstract storage interface comprising a software interface module that communicates with at least one shared persistent key-value metadata store providing a key-value interface for persistent storage of key-value metadata. The software interface module provides the key-value metadata to the at least one shared persistent key-value metadata store in a key-value format. The shared persistent key-value metadata store is accessed by a plurality of metadata servers. A metadata requestmore » can be processed by a given metadata server independently of other metadata servers in the cluster file system. A distributed metadata storage environment is also disclosed that comprises a plurality of metadata servers having an abstract storage interface to at least one shared persistent key-value metadata store.« less

The Global War on Terrorism: Analytical Support, Tools and Metrics of Assessment. MORS Workshop

DTIC Science & Technology

2005-08-11

is the matter of intelligence, as COL(P) Keller pointed out, we need to spend less time in the intelligence cycle on managing information and...models, decision aids: "named things " * Methodologies: potentially useful things "* Resources: databases, people, books? * Meta-data on tools * Develop a...experience. Only one member (Mr. Garry Greco) had served on the Joint Intelligence Task Force for Counter Terrorism. Although Gary heavily participated

Scalable Metadata Management for a Large Multi-Source Seismic Data Repository

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaylord, J. M.; Dodge, D. A.; Magana-Zook, S. A.

In this work, we implemented the key metadata management components of a scalable seismic data ingestion framework to address limitations in our existing system, and to position it for anticipated growth in volume and complexity. We began the effort with an assessment of open source data flow tools from the Hadoop ecosystem. We then began the construction of a layered architecture that is specifically designed to address many of the scalability and data quality issues we experience with our current pipeline. This included implementing basic functionality in each of the layers, such as establishing a data lake, designing a unifiedmore » metadata schema, tracking provenance, and calculating data quality metrics. Our original intent was to test and validate the new ingestion framework with data from a large-scale field deployment in a temporary network. This delivered somewhat unsatisfying results, since the new system immediately identified fatal flaws in the data relatively early in the pipeline. Although this is a correct result it did not allow us to sufficiently exercise the whole framework. We then widened our scope to process all available metadata from over a dozen online seismic data sources to further test the implementation and validate the design. This experiment also uncovered a higher than expected frequency of certain types of metadata issues that challenged us to further tune our data management strategy to handle them. Our result from this project is a greatly improved understanding of real world data issues, a validated design, and prototype implementations of major components of an eventual production framework. This successfully forms the basis of future development for the Geophysical Monitoring Program data pipeline, which is a critical asset supporting multiple programs. It also positions us very well to deliver valuable metadata management expertise to our sponsors, and has already resulted in an NNSA Office of Defense Nuclear Nonproliferation commitment to a multi-year project for follow-on work.« less

Web Services as Building Blocks for an Open Coastal Observing System

NASA Astrophysics Data System (ADS)

Breitbach, G.; Krasemann, H.

2012-04-01

In coastal observing systems it is needed to integrate different observing methods like remote sensing, in-situ measurements, and models into a synoptic view of the state of the observed region. This integration can be based solely on web services combining data and metadata. Such an approach is pursued for COSYNA (Coastal Observing System for Northern and Artic seas). Data from satellite and radar remote sensing, measurements of buoys, stations and Ferryboxes are the observation part of COSYNA. These data are assimilated into models to create pre-operational forecasts. For discovering data an OGC Web Feature Service (WFS) is used by the COSYNA data portal. This Web Feature Service knows the necessary metadata not only for finding data, but in addition the URLs of web services to view and download the data. To make the data from different resources comparable a common vocabulary is needed. For COSYNA the standard names from CF-conventions are stored within the metadata whenever possible. For the metadata an INSPIRE and ISO19115 compatible data format is used. The WFS is fed from the metadata-system using database-views. Actual data are stored in two different formats, in NetCDF-files for gridded data and in an RDBMS for time-series-like data. The web service URLs are mostly standard based the standards are mainly OGC standards. Maps were created from netcdf files with the help of the ncWMS tool whereas a self-developed java servlet is used for maps of moving measurement platforms. In this case download of data is offered via OGC SOS. For NetCDF-files OPeNDAP is used for the data download. The OGC CSW is used for accessing extended metadata. The concept of data management in COSYNA will be presented which is independent of the special services used in COSYNA. This concept is parameter and data centric and might be useful for other observing systems.

The Climate-G testbed: towards a large scale data sharing environment for climate change

NASA Astrophysics Data System (ADS)

Aloisio, G.; Fiore, S.; Denvil, S.; Petitdidier, M.; Fox, P.; Schwichtenberg, H.; Blower, J.; Barbera, R.

2009-04-01

The Climate-G testbed provides an experimental large scale data environment for climate change addressing challenging data and metadata management issues. The main scope of Climate-G is to allow scientists to carry out geographical and cross-institutional climate data discovery, access, visualization and sharing. Climate-G is a multidisciplinary collaboration involving both climate and computer scientists and it currently involves several partners such as: Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Institut Pierre-Simon Laplace (IPSL), Fraunhofer Institut für Algorithmen und Wissenschaftliches Rechnen (SCAI), National Center for Atmospheric Research (NCAR), University of Reading, University of Catania and University of Salento. To perform distributed metadata search and discovery, we adopted a CMCC metadata solution (which provides a high level of scalability, transparency, fault tolerance and autonomy) leveraging both on P2P and grid technologies (GRelC Data Access and Integration Service). Moreover, data are available through OPeNDAP/THREDDS services, Live Access Server as well as the OGC compliant Web Map Service and they can be downloaded, visualized, accessed into the proposed environment through the Climate-G Data Distribution Centre (DDC), the web gateway to the Climate-G digital library. The DDC is a data-grid portal allowing users to easily, securely and transparently perform search/discovery, metadata management, data access, data visualization, etc. Godiva2 (integrated into the DDC) displays 2D maps (and animations) and also exports maps for display on the Google Earth virtual globe. Presently, Climate-G publishes (through the DDC) about 2TB of data related to the ENSEMBLES project (also including distributed replicas of data) as well as to the IPCC AR4. The main results of the proposed work are: wide data access/sharing environment for climate change; P2P/grid metadata approach; production-level Climate-G DDC; high quality tools for data visualization; metadata search/discovery across several countries/institutions; open environment for climate change data sharing.

A Multi-Purpose Data Dissemination Infrastructure for the Marine-Earth Observations

NASA Astrophysics Data System (ADS)

Hanafusa, Y.; Saito, H.; Kayo, M.; Suzuki, H.

2015-12-01

To open the data from a variety of observations, the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) has developed a multi-purpose data dissemination infrastructure. Although many observations have been made in the earth science, all the data are not opened completely. We think data centers may provide researchers with a universal data dissemination service which can handle various kinds of observation data with little effort. For this purpose JAMSTEC Data Management Office has developed the "Information Catalog Infrastructure System (Catalog System)". This is a kind of catalog management system which can create, renew and delete catalogs (= databases) and has following features, - The Catalog System does not depend on data types or granularity of data records. - By registering a new metadata schema to the system, a new database can be created on the same system without sytem modification. - As web pages are defined by the cascading style sheets, databases have different look and feel, and operability. - The Catalog System provides databases with basic search tools; search by text, selection from a category tree, and selection from a time line chart. - For domestic users it creates the Japanese and English pages at the same time and has dictionary to control terminology and proper noun. As of August 2015 JAMSTEC operates 7 databases on the Catalog System. We expect to transfer existing databases to this system, or create new databases on it. In comparison with a dedicated database developed for the specific dataset, the Catalog System is suitable for the dissemination of small datasets, with minimum cost. Metadata held in the catalogs may be transfered to other metadata schema to exchange global databases or portals. Examples: JAMSTEC Data Catalog: http://www.godac.jamstec.go.jp/catalog/data_catalog/metadataList?lang=enJAMSTEC Document Catalog: http://www.godac.jamstec.go.jp/catalog/doc_catalog/metadataList?lang=en&tab=categoryResearch Information and Data Access Site of TEAMS: http://www.i-teams.jp/catalog/rias/metadataList?lang=en&tab=list

Developments in Geometric Metadata and Tools at the PDS Ring-Moon Systems Node

NASA Astrophysics Data System (ADS)

Showalter, M. R.; Ballard, L.; French, R. S.; Gordon, M. K.; Tiscareno, M. S.

2018-04-01

Object-Oriented Python/SPICE (OOPS) is an overlay on the SPICE toolkit that vastly simplifies and speeds up geometry calculations for planetary data products. This toolkit is the basis for much of the development at the PDS Ring-Moon Systems Node.

A Common Metadata System for Marine Data Portals

NASA Astrophysics Data System (ADS)

Wosniok, C.; Breitbach, G.; Lehfeldt, R.

2012-04-01

Processing and allocation of marine datasets depend on the nature of the data resulting from field campaigns, continuous monitoring and numerical modeling. Two research and development projects in northern Germany manage different types of marine data. Due to different data characteristics and institutional frameworks separate data portals are required. This paper describes the integration of distributed marine data in Germany. The Marine Data Infrastructure of Germany (MDI-DE) supports public authorities in the German coastal zone with the implementation of European directives like INSPIRE or the Marine Strategy Framework Directive. This is carried out through setting up standardized web services within a network of participating coastal agencies and the installation of a common data portal (http://www.mdi-de.org), which integrates distributed marine data concerning coastal engineering, coastal water protection and nature conservation in an interoperable and harmonized manner for administrative and scientific purposes as well as for information of the general public. The Coastal Observation System for Northern and Arctic Seas (COSYNA) aims at developing and testing analysis systems for the operational synoptic description of the environmental status of the North Sea and of Arctic coastal waters. This is done by establishing a network of monitoring facilities and the provision of its data in near-real-time. In situ measurements with poles, ferry boxes, and buoys, together with remote sensing measurements, and the data assimilation of these data into simulation results enables COSYNA to provide pre-operational 'products', that are beyond the present routinely applied techniques in observation and modelling. The data allocation in near-real-time requires thoroughly executed data validation, which is processed on the fly before data is passed on to the COSYNA portal (http://kofserver2.hzg.de/codm/). Both projects apply OGC standards such as Web Mapping Service (WMS), Web Feature Service (WFS) and Sensor Observation Service (SOS), which ensures interoperability and extensibility. In addition, metadata as crucial components for searching and finding information in large data infrastructures is provided via the Catalogue Web Service (CS-W). MDI-DE and COSYNA rely on the metadata information system for marine metadata NOKIS, which reflects a metadata profile tailored for marine data according to the specifications of German coastal authorities. In spite of this common software base, interoperability between the two data collections requires constant alignments of the diverse data processed by the two portals. While monitoring data in the MDI-DE is currently rather campaign-based, COSYNA has to fit constantly evolving time series into metadata sets. With all data following the same metadata profile, we now reach full interoperability between the different data collections. The distributed marine information system provides options to search, find and visualise the harmonised results from continuous monitoring, field campaigns, numerical modeling and other data in one web client.

Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) - A New U.S. DOE Data Archive

NASA Astrophysics Data System (ADS)

Agarwal, D.; Varadharajan, C.; Cholia, S.; Snavely, C.; Hendrix, V.; Gunter, D.; Riley, W. J.; Jones, M.; Budden, A. E.; Vieglais, D.

2017-12-01

The ESS-DIVE archive is a new U.S. Department of Energy (DOE) data archive designed to provide long-term stewardship and use of data from observational, experimental, and modeling activities in the earth and environmental sciences. The ESS-DIVE infrastructure is constructed with the long-term vision of enabling broad access to and usage of the DOE sponsored data stored in the archive. It is designed as a scalable framework that incentivizes data providers to contribute well-structured, high-quality data to the archive and that enables the user community to easily build data processing, synthesis, and analysis capabilities using those data. The key innovations in our design include: (1) application of user-experience research methods to understand the needs of users and data contributors; (2) support for early data archiving during project data QA/QC and before public release; (3) focus on implementation of data standards in collaboration with the community; (4) support for community built tools for data search, interpretation, analysis, and visualization tools; (5) data fusion database to support search of the data extracted from packages submitted and data available in partner data systems such as the Earth System Grid Federation (ESGF) and DataONE; and (6) support for archiving of data packages that are not to be released to the public. ESS-DIVE data contributors will be able to archive and version their data and metadata, obtain data DOIs, search for and access ESS data and metadata via web and programmatic portals, and provide data and metadata in standardized forms. The ESS-DIVE archive and catalog will be federated with other existing catalogs, allowing cross-catalog metadata search and data exchange with existing systems, including DataONE's Metacat search. ESS-DIVE is operated by a multidisciplinary team from Berkeley Lab, the National Center for Ecological Analysis and Synthesis (NCEAS), and DataONE. The primarily data copies are hosted at DOE's NERSC supercomputing facility with replicas at DataONE nodes.

The Heliophysics Data Environment: Open Source, Open Systems and Open Data.

NASA Astrophysics Data System (ADS)

King, Todd; Roberts, Aaron; Walker, Raymond; Thieman, James

2012-07-01

The Heliophysics Data Environment (HPDE) is a place for scientific discovery. Today the Heliophysics Data Environment is a framework of technologies, standards and services which enables the international community to collaborate more effectively in space physics research. Crafting a framework for a data environment begins with defining a model of the tasks to be performed, then defining the functional aspects and the work flow. The foundation of any data environment is an information model which defines the structure and content of the metadata necessary to perform the tasks. In the Heliophysics Data Environment the information model is the Space Physics Archive Search and Extract (SPASE) model and available resources are described by using this model. A described resource can reside anywhere on the internet which makes it possible for a national archive, mission, data center or individual researcher to be a provider. The generated metadata is shared, reviewed and harvested to enable services. Virtual Observatories use the metadata to provide community based portals. Through unique identifiers and registry services tools can quickly discover and access data available anywhere on the internet. This enables a researcher to quickly view and analyze data in a variety of settings and enhances the Heliophysics Data Environment. To illustrate the current Heliophysics Data Environment we present the design, architecture and operation of the Heliophysics framework. We then walk through a real example of using available tools to investigate the effects of the solar wind on Earth's magnetosphere.

Developing a Metadata Infrastructure to facilitate data driven science gateway and to provide Inspire/GEMINI compliance for CLIPC

NASA Astrophysics Data System (ADS)

Mihajlovski, Andrej; Plieger, Maarten; Som de Cerff, Wim; Page, Christian

2016-04-01

The CLIPC project is developing a portal to provide a single point of access for scientific information on climate change. This is made possible through the Copernicus Earth Observation Programme for Europe, which will deliver a new generation of environmental measurements of climate quality. The data about the physical environment which is used to inform climate change policy and adaptation measures comes from several categories: satellite measurements, terrestrial observing systems, model projections and simulations and from re-analyses (syntheses of all available observations constrained with numerical weather prediction systems). These data categories are managed by different communities: CLIPC will provide a single point of access for the whole range of data. The CLIPC portal will provide a number of indicators showing impacts on specific sectors which have been generated using a range of factors selected through structured expert consultation. It will also, as part of the transformation services, allow users to explore the consequences of using different combinations of driving factors which they consider to be of particular relevance to their work or life. The portal will provide information on the scientific quality and pitfalls of such transformations to prevent misleading usage of the results. The CLIPC project will develop an end to end processing chain (indicator tool kit), from comprehensive information on the climate state through to highly aggregated decision relevant products. Indicators of climate change and climate change impact will be provided, and a tool kit to update and post process the collection of indicators will be integrated into the portal. The CLIPC portal has a distributed architecture, making use of OGC services provided by e.g., climate4impact.eu and CEDA. CLIPC has two themes: 1. Harmonized access to climate datasets derived from models, observations and re-analyses 2. A climate impact tool kit to evaluate, rank and aggregate indicators Key is the availability of standardized metadata, describing indicator data and services. This will enable standardization and interoperability between the different distributed services of CLIPC. To disseminate CLIPC indicator data, transformed data products to enable impacts assessments and climate change impact indicators a standardized meta-data infrastructure is provided. The challenge is that compliance of existing metadata to INSPIRE ISO standards and GEMINI standards needs to be extended to further allow the web portal to be generated from the available metadata blueprint. The information provided in the headers of netCDF files available through multiple catalogues, allow us to generate ISO compliant meta data which is in turn used to generate web based interface content, as well as OGC compliant web services such as WCS and WMS for front end and WPS interactions for the scientific users to combine and generate new datasets. The goal of the metadata infrastructure is to provide a blueprint for creating a data driven science portal, generated from the underlying: GIS data, web services and processing infrastructure. In the presentation we will present the results and lessons learned.

EMERALD: A Flexible Framework for Managing Seismic Data

NASA Astrophysics Data System (ADS)

West, J. D.; Fouch, M. J.; Arrowsmith, R.

2010-12-01

The seismological community is challenged by the vast quantity of new broadband seismic data provided by large-scale seismic arrays such as EarthScope’s USArray. While this bonanza of new data enables transformative scientific studies of the Earth’s interior, it also illuminates limitations in the methods used to prepare and preprocess those data. At a recent seismic data processing focus group workshop, many participants expressed the need for better systems to minimize the time and tedium spent on data preparation in order to increase the efficiency of scientific research. Another challenge related to data from all large-scale transportable seismic experiments is that there currently exists no system for discovering and tracking changes in station metadata. This critical information, such as station location, sensor orientation, instrument response, and clock timing data, may change over the life of an experiment and/or be subject to post-experiment correction. Yet nearly all researchers utilize metadata acquired with the downloaded data, even though subsequent metadata updates might alter or invalidate results produced with older metadata. A third long-standing issue for the seismic community is the lack of easily exchangeable seismic processing codes. This problem stems directly from the storage of seismic data as individual time series files, and the history of each researcher developing his or her preferred data file naming convention and directory organization. Because most processing codes rely on the underlying data organization structure, such codes are not easily exchanged between investigators. To address these issues, we are developing EMERALD (Explore, Manage, Edit, Reduce, & Analyze Large Datasets). The goal of the EMERALD project is to provide seismic researchers with a unified, user-friendly, extensible system for managing seismic event data, thereby increasing the efficiency of scientific enquiry. EMERALD stores seismic data and metadata in a state-of-the-art open source relational database (PostgreSQL), and can, on a timed basis or on demand, download the most recent metadata, compare it with previously acquired values, and alert the user to changes. The backend relational database is capable of easily storing and managing many millions of records. The extensible, plug-in architecture of the EMERALD system allows any researcher to contribute new visualization and processing methods written in any of 12 programming languages, and a central Internet-enabled repository for such methods provides users with the opportunity to download, use, and modify new processing methods on demand. EMERALD includes data acquisition tools allowing direct importation of seismic data, and also imports data from a number of existing seismic file formats. Pre-processed clean sets of data can be exported as standard sac files with user-defined file naming and directory organization, for use with existing processing codes. The EMERALD system incorporates existing acquisition and processing tools, including SOD, TauP, GMT, and FISSURES/DHI, making much of the functionality of those tools available in a unified system with a user-friendly web browser interface. EMERALD is now in beta test. See emerald.asu.edu or contact john.d.west@asu.edu for more details.

Best Practices for Data Publication to Facilitate Integration into NED: A Reference Guide for Authors

NASA Astrophysics Data System (ADS)

Schmitz, Marion; Mazzarella, J. M.; Madore, B. F.; Ogle, P. M.; Ebert, R.; Baker, K.; Chan, H.; Chen, X.; Fadda, D.; Frayer, C.; Jacobson, J. D.; LaGue, C.; Lo, T. M.; Pevunova, O.; Terek, S.; Steer, I.

2014-01-01

At the urging of the NASA/IPAC Extragalactic Database (NED) Users Committee, the NED Team has prepared and published on its website a new document titled "Best Practices for Data Publication to Facilitate Integration into NED: A Reference Guide for Authors" (http://ned.ipac.caltech.edu/docs/BPDP/NED_BPDP.pdf). We hope that journal publishers will incorporate links to this living document in their Instructions to Authors to provide a practical reference for authors, referees, and science editors so as to help avoid various pitfalls that often impede the interpretation of data and metadata, and also delay their integration into NED, SIMBAD, ADS and other systems. In particular, we discuss the importance of using proper naming conventions, providing the epoch and system of coordinates, including units and uncertainties, and giving sufficient metadata for the unambiguous interpretation of tabular, imaging, and spectral data. The biggest impediments to the assimilation of new data from the literature into NED are ambiguous object names and non-unique, coordinate-based identifiers. A Checklist of Recommendations will be presented which includes links to sections of the Best Practices document that provide further examples, explanation, and rationale.

The Materials Data Facility: Data Services to Advance Materials Science Research

NASA Astrophysics Data System (ADS)

Blaiszik, B.; Chard, K.; Pruyne, J.; Ananthakrishnan, R.; Tuecke, S.; Foster, I.

2016-08-01

With increasingly strict data management requirements from funding agencies and institutions, expanding focus on the challenges of research replicability, and growing data sizes and heterogeneity, new data needs are emerging in the materials community. The materials data facility (MDF) operates two cloud-hosted services, data publication and data discovery, with features to promote open data sharing, self-service data publication and curation, and encourage data reuse, layered with powerful data discovery tools. The data publication service simplifies the process of copying data to a secure storage location, assigning data a citable persistent identifier, and recording custom (e.g., material, technique, or instrument specific) and automatically-extracted metadata in a registry while the data discovery service will provide advanced search capabilities (e.g., faceting, free text range querying, and full text search) against the registered data and metadata. The MDF services empower individual researchers, research projects, and institutions to (I) publish research datasets, regardless of size, from local storage, institutional data stores, or cloud storage, without involvement of third-party publishers; (II) build, share, and enforce extensible domain-specific custom metadata schemas; (III) interact with published data and metadata via representational state transfer (REST) application program interfaces (APIs) to facilitate automation, analysis, and feedback; and (IV) access a data discovery model that allows researchers to search, interrogate, and eventually build on existing published data. We describe MDF's design, current status, and future plans.

Xeml Lab: a tool that supports the design of experiments at a graphical interface and generates computer-readable metadata files, which capture information about genotypes, growth conditions, environmental perturbations and sampling strategy.

PubMed

Hannemann, Jan; Poorter, Hendrik; Usadel, Björn; Bläsing, Oliver E; Finck, Alex; Tardieu, Francois; Atkin, Owen K; Pons, Thijs; Stitt, Mark; Gibon, Yves

2009-09-01

Data mining depends on the ability to access machine-readable metadata that describe genotypes, environmental conditions, and sampling times and strategy. This article presents Xeml Lab. The Xeml Interactive Designer provides an interactive graphical interface at which complex experiments can be designed, and concomitantly generates machine-readable metadata files. It uses a new eXtensible Mark-up Language (XML)-derived dialect termed XEML. Xeml Lab includes a new ontology for environmental conditions, called Xeml Environment Ontology. However, to provide versatility, it is designed to be generic and also accepts other commonly used ontology formats, including OBO and OWL. A review summarizing important environmental conditions that need to be controlled, monitored and captured as metadata is posted in a Wiki (http://www.codeplex.com/XeO) to promote community discussion. The usefulness of Xeml Lab is illustrated by two meta-analyses of a large set of experiments that were performed with Arabidopsis thaliana during 5 years. The first reveals sources of noise that affect measurements of metabolite levels and enzyme activities. The second shows that Arabidopsis maintains remarkably stable levels of sugars and amino acids across a wide range of photoperiod treatments, and that adjustment of starch turnover and the leaf protein content contribute to this metabolic homeostasis.

MyGeoHub: A Collaborative Geospatial Research and Education Platform

NASA Astrophysics Data System (ADS)

Kalyanam, R.; Zhao, L.; Biehl, L. L.; Song, C. X.; Merwade, V.; Villoria, N.

2017-12-01

Scientific research is increasingly collaborative and globally distributed; research groups now rely on web-based scientific tools and data management systems to simplify their day-to-day collaborative workflows. However, such tools often lack seamless interfaces, requiring researchers to contend with manual data transfers, annotation and sharing. MyGeoHub is a web platform that supports out-of-the-box, seamless workflows involving data ingestion, metadata extraction, analysis, sharing and publication. MyGeoHub is built on the HUBzero cyberinfrastructure platform and adds general-purpose software building blocks (GABBs), for geospatial data management, visualization and analysis. A data management building block iData, processes geospatial files, extracting metadata for keyword and map-based search while enabling quick previews. iData is pervasive, allowing access through a web interface, scientific tools on MyGeoHub or even mobile field devices via a data service API. GABBs includes a Python map library as well as map widgets that in a few lines of code, generate complete geospatial visualization web interfaces for scientific tools. GABBs also includes powerful tools that can be used with no programming effort. The GeoBuilder tool provides an intuitive wizard for importing multi-variable, geo-located time series data (typical of sensor readings, GPS trackers) to build visualizations supporting data filtering and plotting. MyGeoHub has been used in tutorials at scientific conferences and educational activities for K-12 students. MyGeoHub is also constantly evolving; the recent addition of Jupyter and R Shiny notebook environments enable reproducible, richly interactive geospatial analyses and applications ranging from simple pre-processing to published tools. MyGeoHub is not a monolithic geospatial science gateway, instead it supports diverse needs ranging from just a feature-rich data management system, to complex scientific tools and workflows.

Log-less metadata management on metadata server for parallel file systems.

PubMed

Liao, Jianwei; Xiao, Guoqiang; Peng, Xiaoning

2014-01-01

This paper presents a novel metadata management mechanism on the metadata server (MDS) for parallel and distributed file systems. In this technique, the client file system backs up the sent metadata requests, which have been handled by the metadata server, so that the MDS does not need to log metadata changes to nonvolatile storage for achieving highly available metadata service, as well as better performance improvement in metadata processing. As the client file system backs up certain sent metadata requests in its memory, the overhead for handling these backup requests is much smaller than that brought by the metadata server, while it adopts logging or journaling to yield highly available metadata service. The experimental results show that this newly proposed mechanism can significantly improve the speed of metadata processing and render a better I/O data throughput, in contrast to conventional metadata management schemes, that is, logging or journaling on MDS. Besides, a complete metadata recovery can be achieved by replaying the backup logs cached by all involved clients, when the metadata server has crashed or gone into nonoperational state exceptionally.

Log-Less Metadata Management on Metadata Server for Parallel File Systems

PubMed Central

Xiao, Guoqiang; Peng, Xiaoning

2014-01-01

This paper presents a novel metadata management mechanism on the metadata server (MDS) for parallel and distributed file systems. In this technique, the client file system backs up the sent metadata requests, which have been handled by the metadata server, so that the MDS does not need to log metadata changes to nonvolatile storage for achieving highly available metadata service, as well as better performance improvement in metadata processing. As the client file system backs up certain sent metadata requests in its memory, the overhead for handling these backup requests is much smaller than that brought by the metadata server, while it adopts logging or journaling to yield highly available metadata service. The experimental results show that this newly proposed mechanism can significantly improve the speed of metadata processing and render a better I/O data throughput, in contrast to conventional metadata management schemes, that is, logging or journaling on MDS. Besides, a complete metadata recovery can be achieved by replaying the backup logs cached by all involved clients, when the metadata server has crashed or gone into nonoperational state exceptionally. PMID:24892093

Learning Objects Metadata and Tools in the Area of Operations Research.

ERIC Educational Resources Information Center

Kassanke, Stephan; El-Saddik, Abdulmotaleb; Steinacker, Achim

Information technology and the Internet are making inroads into almost all areas of society. The requirements of students and professionals are fast changing, and the information society requires lifelong learning in practically all areas, especially those related to information technologies. The educational sector can profit in particular from…

Metadata Creation Tool Content Template For Data Stewards

EPA Science Inventory

A space-time Bayesian fusion model (McMillan, Holland, Morara, and Feng, 2009) is used to provide daily, gridded predictive PM_2.5 (daily average) and O₃ (daily 8-hr maximum) surfaces for 2001-2005. The fusion model uses both air quality monitoring data from ...

Linking physiological parameters to perturbations in the human exposome: Environmental exposures modify blood pressure and lung function via inflammatory cytokine pathway

EPA Science Inventory

Human biomonitoring is an indispensable tool for establishing the systemic effects from external stressors including environmental pollutants, chemicals from consumer products, and pharmaceuticals. This article uses a combination of new results and meta-data from previous work to...

The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reddy, Tatiparthi B. K.; Thomas, Alex D.; Stamatis, Dimitri

The Genomes OnLine Database (GOLD; http://www.genomesonline.org) is a comprehensive online resource to catalog and monitor genetic studies worldwide. GOLD provides up-to-date status on complete and ongoing sequencing projects along with a broad array of curated metadata. Within this paper, we report version 5 (v.5) of the database. The newly designed database schema and web user interface supports several new features including the implementation of a four level (meta)genome project classification system and a simplified intuitive web interface to access reports and launch search tools. The database currently hosts information for about 19 200 studies, 56 000 Biosamples, 56 000 sequencingmore » projects and 39 400 analysis projects. More than just a catalog of worldwide genome projects, GOLD is a manually curated, quality-controlled metadata warehouse. The problems encountered in integrating disparate and varying quality data into GOLD are briefly highlighted. Lastly, GOLD fully supports and follows the Genomic Standards Consortium (GSC) Minimum Information standards.« less

The NOAA OneStop System: From Well-Curated Metadata to Data Discovery

NASA Astrophysics Data System (ADS)

McQuinn, E.; Jakositz, A.; Caldwell, A.; Delk, Z.; Neufeld, D.; Shapiro, J.; Partee, R.; Milan, A.

2017-12-01

The NOAA OneStop project is a pathfinder in the realm of enabling users to search for, discover, and access NOAA data. As the project continues along its path to maturity, it has become evident that three areas are of utmost importance to its success in the Earth science community: ensuring quality metadata, building a robust and scalable backend architecture, and keeping the user interface simple to use. Why is this the case? Because, simply put, we are dealing with all aspects of a Big Data problem: large volumes of disparate data needing to be quickly and easily processed and retrieved. In this presentation we discuss the three key aspects of OneStop architecture and how development in each area must be done through cross-team collaboration in order to succeed. We cover aspects of the web-based user interface and OneStop API and how metadata curators and software engineers have worked together to continually iterate on an ever-improving data discovery tool meant to be used by a variety of users searching across a broad assortment of data types.

An Observation Knowledgebase for Hinode Data

NASA Astrophysics Data System (ADS)

Hurlburt, Neal E.; Freeland, S.; Green, S.; Schiff, D.; Seguin, R.; Slater, G.; Cirtain, J.

2007-05-01

We have developed a standards-based system for the Solar Optical and X Ray Telescopes on the Hinode orbiting solar observatory which can serve as part of a developing Heliophysics informatics system. Our goal is to make the scientific data acquired by Hinode more accessible and useful to scientists by allowing them to do reasoning and flexible searches on observation metadata and to ask higher-level questions of the system than previously allowed. The Hinode Observation Knowledgebase relates the intentions and goals of the observation planners (as-planned metadata) with actual observational data (as-run metadata), along with connections to related models, data products and identified features (follow-up metadata) through a citation system. Summaries of the data (both as image thumbnails and short "film strips") serve to guide researchers to the observations appropriate for their research, and these are linked directly to the data catalog for easy extraction and delivery. The semantic information of the observation (Field of view, wavelength, type of observable, average cadence etc.) is captured through simple user interfaces and encoded using the VOEvent XML standard (with the addition of some solar-related extensions). These interfaces merge metadata acquired automatically during both mission planning and an data analysis (see Seguin et. al. 2007 at this meeting) phases with that obtained directly from the planner/analyst and send them to be incorporated into the knowledgebase. The resulting information is automatically rendered into standard categories based on planned and recent observations, as well as by popularity and recommendations by the science team. They are also directly searchable through both and web-based searches and direct calls to the API. Observations details can also be rendered as RSS, iTunes and Google Earth interfaces. The resulting system provides a useful tool to researchers and can act as a demonstration for larger, more complex systems.

Augmenting Traditional Static Analysis With Commonly Available Metadata

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cook, Devin

Developers and security analysts have been using static analysis for a long time to analyze programs for defects and vulnerabilities with some success. Generally a static analysis tool is run on the source code for a given program, flagging areas of code that need to be further inspected by a human analyst. These areas may be obvious bugs like potential bu er over flows, information leakage flaws, or the use of uninitialized variables. These tools tend to work fairly well - every year they find many important bugs. These tools are more impressive considering the fact that they only examinemore » the source code, which may be very complex. Now consider the amount of data available that these tools do not analyze. There are many pieces of information that would prove invaluable for finding bugs in code, things such as a history of bug reports, a history of all changes to the code, information about committers, etc. By leveraging all this additional data, it is possible to nd more bugs with less user interaction, as well as track useful metrics such as number and type of defects injected by committer. This dissertation provides a method for leveraging development metadata to find bugs that would otherwise be difficult to find using standard static analysis tools. We showcase two case studies that demonstrate the ability to find 0day vulnerabilities in large and small software projects by finding new vulnerabilities in the cpython and Roundup open source projects.« less

The NCAR Research Data Archive's Hybrid Approach for Data Discovery and Access

NASA Astrophysics Data System (ADS)

Schuster, D.; Worley, S. J.

2013-12-01

The NCAR Research Data Archive (RDA http://rda.ucar.edu) maintains a variety of data discovery and access capabilities for it's 600+ dataset collections to support the varying needs of a diverse user community. In-house developed and standards-based community tools offer services to more than 10,000 users annually. By number of users the largest group is external and access the RDA through web based protocols; the internal NCAR HPC users are fewer in number, but typically access more data volume. This paper will detail the data discovery and access services maintained by the RDA to support both user groups, and show metrics that illustrate how the community is using the services. The distributed search capability enabled by standards-based community tools, such as Geoportal and an OAI-PMH access point that serves multiple metadata standards, provide pathways for external users to initially discover RDA holdings. From here, in-house developed web interfaces leverage primary discovery level metadata databases that support keyword and faceted searches. Internal NCAR HPC users, or those familiar with the RDA, may go directly to the dataset collection of interest and refine their search based on rich file collection metadata. Multiple levels of metadata have proven to be invaluable for discovery within terabyte-sized archives composed of many atmospheric or oceanic levels, hundreds of parameters, and often numerous grid and time resolutions. Once users find the data they want, their access needs may vary as well. A THREDDS data server running on targeted dataset collections enables remote file access through OPENDAP and other web based protocols primarily for external users. In-house developed tools give all users the capability to submit data subset extraction and format conversion requests through scalable, HPC based delayed mode batch processing. Users can monitor their RDA-based data processing progress and receive instructions on how to access the data when it is ready. External users are provided with RDA server generated scripts to download the resulting request output. Similarly they can download native dataset collection files or partial files using Wget or cURL based scripts supplied by the RDA server. Internal users can access the resulting request output or native dataset collection files directly from centralized file systems.

The myths of 'big data' in health care.

PubMed

Jacofsky, D J

2017-12-01

'Big data' is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Billions of dollars have been spent on attempts to build predictive tools from large sets of poorly controlled healthcare metadata. Companies often sell reports at a physician or facility level based on various flawed data sources, and comparative websites of 'publicly reported data' purport to educate the public. Physicians should be aware of concerns and pitfalls seen in such data definitions, data clarity, data relevance, data sources and data cleaning when evaluating analytic reports from metadata in health care. Cite this article: Bone Joint J 2017;99-B:1571-6. ©2017 The British Editorial Society of Bone & Joint Surgery.

Information integration for a sky survey by data warehousing

NASA Astrophysics Data System (ADS)

Luo, A.; Zhang, Y.; Zhao, Y.

The virtualization service of data system for a sky survey LAMOST is very important for astronomers The service needs to integrate information from data collections catalogs and references and support simple federation of a set of distributed files and associated metadata Data warehousing has been in existence for several years and demonstrated superiority over traditional relational database management systems by providing novel indexing schemes that supported efficient on-line analytical processing OLAP of large databases Now relational database systems such as Oracle etc support the warehouse capability which including extensions to the SQL language to support OLAP operations and a number of metadata management tools have been created The information integration of LAMOST by applying data warehousing is to effectively provide data and knowledge on-line

Virtual Patients on the Semantic Web: A Proof-of-Application Study

PubMed Central

Dafli, Eleni; Antoniou, Panagiotis; Ioannidis, Lazaros; Dombros, Nicholas; Topps, David

2015-01-01

Background Virtual patients are interactive computer simulations that are increasingly used as learning activities in modern health care education, especially in teaching clinical decision making. A key challenge is how to retrieve and repurpose virtual patients as unique types of educational resources between different platforms because of the lack of standardized content-retrieving and repurposing mechanisms. Semantic Web technologies provide the capability, through structured information, for easy retrieval, reuse, repurposing, and exchange of virtual patients between different systems. Objective An attempt to address this challenge has been made through the mEducator Best Practice Network, which provisioned frameworks for the discovery, retrieval, sharing, and reuse of medical educational resources. We have extended the OpenLabyrinth virtual patient authoring and deployment platform to facilitate the repurposing and retrieval of existing virtual patient material. Methods A standalone Web distribution and Web interface, which contains an extension for the OpenLabyrinth virtual patient authoring system, was implemented. This extension was designed to semantically annotate virtual patients to facilitate intelligent searches, complex queries, and easy exchange between institutions. The OpenLabyrinth extension enables OpenLabyrinth authors to integrate and share virtual patient case metadata within the mEducator3.0 network. Evaluation included 3 successive steps: (1) expert reviews; (2) evaluation of the ability of health care professionals and medical students to create, share, and exchange virtual patients through specific scenarios in extended OpenLabyrinth (OLabX); and (3) evaluation of the repurposed learning objects that emerged from the procedure. Results We evaluated 30 repurposed virtual patient cases. The evaluation, with a total of 98 participants, demonstrated the system’s main strength: the core repurposing capacity. The extensive metadata schema presentation facilitated user exploration and filtering of resources. Usability weaknesses were primarily related to standard computer applications’ ease of use provisions. Most evaluators provided positive feedback regarding educational experiences on both content and system usability. Evaluation results replicated across several independent evaluation events. Conclusions The OpenLabyrinth extension, as part of the semantic mEducator3.0 approach, is a virtual patient sharing approach that builds on a collection of Semantic Web services and federates existing sources of clinical and educational data. It is an effective sharing tool for virtual patients and has been merged into the next version of the app (OpenLabyrinth 3.3). Such tool extensions may enhance the medical education arsenal with capacities of creating simulation/game-based learning episodes, massive open online courses, curricular transformations, and a future robust infrastructure for enabling mobile learning. PMID:25616272

Virtual patients on the semantic Web: a proof-of-application study.

PubMed

Dafli, Eleni; Antoniou, Panagiotis; Ioannidis, Lazaros; Dombros, Nicholas; Topps, David; Bamidis, Panagiotis D

2015-01-22

Virtual patients are interactive computer simulations that are increasingly used as learning activities in modern health care education, especially in teaching clinical decision making. A key challenge is how to retrieve and repurpose virtual patients as unique types of educational resources between different platforms because of the lack of standardized content-retrieving and repurposing mechanisms. Semantic Web technologies provide the capability, through structured information, for easy retrieval, reuse, repurposing, and exchange of virtual patients between different systems. An attempt to address this challenge has been made through the mEducator Best Practice Network, which provisioned frameworks for the discovery, retrieval, sharing, and reuse of medical educational resources. We have extended the OpenLabyrinth virtual patient authoring and deployment platform to facilitate the repurposing and retrieval of existing virtual patient material. A standalone Web distribution and Web interface, which contains an extension for the OpenLabyrinth virtual patient authoring system, was implemented. This extension was designed to semantically annotate virtual patients to facilitate intelligent searches, complex queries, and easy exchange between institutions. The OpenLabyrinth extension enables OpenLabyrinth authors to integrate and share virtual patient case metadata within the mEducator3.0 network. Evaluation included 3 successive steps: (1) expert reviews; (2) evaluation of the ability of health care professionals and medical students to create, share, and exchange virtual patients through specific scenarios in extended OpenLabyrinth (OLabX); and (3) evaluation of the repurposed learning objects that emerged from the procedure. We evaluated 30 repurposed virtual patient cases. The evaluation, with a total of 98 participants, demonstrated the system's main strength: the core repurposing capacity. The extensive metadata schema presentation facilitated user exploration and filtering of resources. Usability weaknesses were primarily related to standard computer applications' ease of use provisions. Most evaluators provided positive feedback regarding educational experiences on both content and system usability. Evaluation results replicated across several independent evaluation events. The OpenLabyrinth extension, as part of the semantic mEducator3.0 approach, is a virtual patient sharing approach that builds on a collection of Semantic Web services and federates existing sources of clinical and educational data. It is an effective sharing tool for virtual patients and has been merged into the next version of the app (OpenLabyrinth 3.3). Such tool extensions may enhance the medical education arsenal with capacities of creating simulation/game-based learning episodes, massive open online courses, curricular transformations, and a future robust infrastructure for enabling mobile learning.

MOLES Information Model

NASA Astrophysics Data System (ADS)

Ventouras, Spiros; Lawrence, Bryan; Woolf, Andrew; Cox, Simon

2010-05-01

The Metadata Objects for Linking Environmental Sciences (MOLES) model has been developed within the Natural Environment Research Council (NERC) DataGrid project [NERC DataGrid] to fill a missing part of the ‘metadata spectrum'. It is a framework within which to encode the relationships between the tools used to obtain data, the activities which organised their use, and the datasets produced. MOLES is primarily of use to consumers of data, especially in an interdisciplinary context, to allow them to establish details of provenance, and to compare and contrast such information without recourse to discipline-specific metadata or private communications with the original investigators [Lawrence et al 2009]. MOLES is also of use to the custodians of data, providing an organising paradigm for the data and metadata. The work described in this paper is a high-level view of the structure and content of a recent major revision of MOLES (v3.3) carried out as part of a NERC DataGrid extension project. The concepts of MOLES v3.3 are rooted in the harmonised ISO model [Harmonised ISO model] - particularly in metadata standards (ISO 19115, ISO 19115-2) and the ‘Observations and Measurements' conceptual model (ISO 19156). MOLES exploits existing concepts and relationships, and specialises information in these standards. A typical sequence of data capturing involves one or more projects under which a number of activities are undertaken, using appropriate tools and methods to produce the datasets. Following this typical sequence, the relevant metadata can be partitioned into the following main sections - helpful in mapping onto the most suitable standards from the ISO 19100 series. • Project section • Activity section (including both observation acquisition and numerical computation) • Observation section (metadata regarding the methods used to obtained the data, the spatial and temporal sampling regime, quality etc.) • Observation collection section The key concepts in MOLES v3.3 are: a) the result of an observation is defined uniquely from the property (of a feature-of-interest), the sampling-feature (carrying the targeted property values), the procedure used to obtain the result and the time (discrete instant or period) at which the observation takes place. b) an ‘Acquisition' and a ‘Computation' can serve as the basis for describing any observation process chain (procedure). The ‘Acquisition' uses an instrument - sensor or human being - to produce the results and is associated with field trips, flights, cruises etc., whereas the ‘Computation' class involves specific processing steps. A process chain may consist of any combination of ‘Acquisitions' and/or ‘Computations' occurring in parallel or in any order during the data capturing sequence. c) The results can be organised in collections with significantly more flexibility than if one used the original project alone d) the structure of individual observation collections may be domain-specific, in general; however we are investigating the use of CSML (Climate Science Modelling Language) for atmospheric data The model has been tested as a desk exercise by constructing object models for scenarios from various disciplines. References NERC DATAGRID: http://ndg.nerc.ac.uk LAWRENCE ET. AL. ,Information in environmental data grids, Phil. Trans. R. Soc. A, March 2009 vol. 367 no. 1890 1003-1014 ISO HARMONISED MODEL: All relevant ISO standards for geographic metadata from the TC211 series (eg. ISO 19xxx), and is harmonised within a formal UML description in the ‘HollowWorld' packages available at https://www.seegrid.csiro.au/twiki/bin/view/AppSchemas/HollowWorld

NASA's Earth Observing Data and Information System - Supporting Interoperability through a Scalable Architecture (Invited)

NASA Astrophysics Data System (ADS)

Mitchell, A. E.; Lowe, D. R.; Murphy, K. J.; Ramapriyan, H. K.

2011-12-01

Initiated in 1990, NASA's Earth Observing System Data and Information System (EOSDIS) is currently a petabyte-scale archive of data designed to receive, process, distribute and archive several terabytes of science data per day from NASA's Earth science missions. Comprised of 12 discipline specific data centers collocated with centers of science discipline expertise, EOSDIS manages over 6800 data products from many science disciplines and sources. NASA supports global climate change research by providing scalable open application layers to the EOSDIS distributed information framework. This allows many other value-added services to access NASA's vast Earth Science Collection and allows EOSDIS to interoperate with data archives from other domestic and international organizations. EOSDIS is committed to NASA's Data Policy of full and open sharing of Earth science data. As metadata is used in all aspects of NASA's Earth science data lifecycle, EOSDIS provides a spatial and temporal metadata registry and order broker called the EOS Clearing House (ECHO) that allows efficient search and access of cross domain data and services through the Reverb Client and Application Programmer Interfaces (APIs). Another core metadata component of EOSDIS is NASA's Global Change Master Directory (GCMD) which represents more than 25,000 Earth science data set and service descriptions from all over the world, covering subject areas within the Earth and environmental sciences. With inputs from the ECHO, GCMD and Soil Moisture Active Passive (SMAP) mission metadata models, EOSDIS is developing a NASA ISO 19115 Best Practices Convention. Adoption of an international metadata standard enables a far greater level of interoperability among national and international data products. NASA recently concluded a 'Metadata Harmony Study' of EOSDIS metadata capabilities/processes of ECHO and NASA's Global Change Master Directory (GCMD), to evaluate opportunities for improved data access and use, reduce efforts by data providers and improve metadata integrity. The result was a recommendation for EOSDIS to develop a 'Common Metadata Repository (CMR)' to manage the evolution of NASA Earth Science metadata in a unified and consistent way by providing a central storage and access capability that streamlines current workflows while increasing overall data quality and anticipating future capabilities. For applications users interested in monitoring and analyzing a wide variety of natural and man-made phenomena, EOSDIS provides access to near real-time products from the MODIS, OMI, AIRS, and MLS instruments in less than 3 hours from observation. To enable interactive exploration of NASA's Earth imagery, EOSDIS is developing a set of standard services to deliver global, full-resolution satellite imagery in a highly responsive manner. EOSDIS is also playing a lead role in the development of the CEOS WGISS Integrated Catalog (CWIC), which provides search and access to holdings of participating international data providers. EOSDIS provides a platform to expose and share information on NASA Earth science tools and data via Earthdata.nasa.gov while offering a coherent and interoperable system for the NASA Earth Science Data System (ESDS) Program.

NASA's Earth Observing Data and Information System - Supporting Interoperability through a Scalable Architecture (Invited)

NASA Astrophysics Data System (ADS)

Mitchell, A. E.; Lowe, D. R.; Murphy, K. J.; Ramapriyan, H. K.

2013-12-01

Initiated in 1990, NASA's Earth Observing System Data and Information System (EOSDIS) is currently a petabyte-scale archive of data designed to receive, process, distribute and archive several terabytes of science data per day from NASA's Earth science missions. Comprised of 12 discipline specific data centers collocated with centers of science discipline expertise, EOSDIS manages over 6800 data products from many science disciplines and sources. NASA supports global climate change research by providing scalable open application layers to the EOSDIS distributed information framework. This allows many other value-added services to access NASA's vast Earth Science Collection and allows EOSDIS to interoperate with data archives from other domestic and international organizations. EOSDIS is committed to NASA's Data Policy of full and open sharing of Earth science data. As metadata is used in all aspects of NASA's Earth science data lifecycle, EOSDIS provides a spatial and temporal metadata registry and order broker called the EOS Clearing House (ECHO) that allows efficient search and access of cross domain data and services through the Reverb Client and Application Programmer Interfaces (APIs). Another core metadata component of EOSDIS is NASA's Global Change Master Directory (GCMD) which represents more than 25,000 Earth science data set and service descriptions from all over the world, covering subject areas within the Earth and environmental sciences. With inputs from the ECHO, GCMD and Soil Moisture Active Passive (SMAP) mission metadata models, EOSDIS is developing a NASA ISO 19115 Best Practices Convention. Adoption of an international metadata standard enables a far greater level of interoperability among national and international data products. NASA recently concluded a 'Metadata Harmony Study' of EOSDIS metadata capabilities/processes of ECHO and NASA's Global Change Master Directory (GCMD), to evaluate opportunities for improved data access and use, reduce efforts by data providers and improve metadata integrity. The result was a recommendation for EOSDIS to develop a 'Common Metadata Repository (CMR)' to manage the evolution of NASA Earth Science metadata in a unified and consistent way by providing a central storage and access capability that streamlines current workflows while increasing overall data quality and anticipating future capabilities. For applications users interested in monitoring and analyzing a wide variety of natural and man-made phenomena, EOSDIS provides access to near real-time products from the MODIS, OMI, AIRS, and MLS instruments in less than 3 hours from observation. To enable interactive exploration of NASA's Earth imagery, EOSDIS is developing a set of standard services to deliver global, full-resolution satellite imagery in a highly responsive manner. EOSDIS is also playing a lead role in the development of the CEOS WGISS Integrated Catalog (CWIC), which provides search and access to holdings of participating international data providers. EOSDIS provides a platform to expose and share information on NASA Earth science tools and data via Earthdata.nasa.gov while offering a coherent and interoperable system for the NASA Earth Science Data System (ESDS) Program.

RNA-Rocket: an RNA-Seq analysis resource for infectious disease research.

PubMed

Warren, Andrew S; Aurrecoechea, Cristina; Brunk, Brian; Desai, Prerak; Emrich, Scott; Giraldo-Calderón, Gloria I; Harb, Omar; Hix, Deborah; Lawson, Daniel; Machi, Dustin; Mao, Chunhong; McClelland, Michael; Nordberg, Eric; Shukla, Maulik; Vosshall, Leslie B; Wattam, Alice R; Will, Rebecca; Yoo, Hyun Seung; Sobral, Bruno

2015-05-01

RNA-Seq is a method for profiling transcription using high-throughput sequencing and is an important component of many research projects that wish to study transcript isoforms, condition specific expression and transcriptional structure. The methods, tools and technologies used to perform RNA-Seq analysis continue to change, creating a bioinformatics challenge for researchers who wish to exploit these data. Resources that bring together genomic data, analysis tools, educational material and computational infrastructure can minimize the overhead required of life science researchers. RNA-Rocket is a free service that provides access to RNA-Seq and ChIP-Seq analysis tools for studying infectious diseases. The site makes available thousands of pre-indexed genomes, their annotations and the ability to stream results to the bioinformatics resources VectorBase, EuPathDB and PATRIC. The site also provides a combination of experimental data and metadata, examples of pre-computed analysis, step-by-step guides and a user interface designed to enable both novice and experienced users of RNA-Seq data. RNA-Rocket is available at rnaseq.pathogenportal.org. Source code for this project can be found at github.com/cidvbi/PathogenPortal. anwarren@vt.edu Supplementary materials are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

GIS, geostatistics, metadata banking, and tree-based models for data analysis and mapping in environmental monitoring and epidemiology.

PubMed

Schröder, Winfried

2006-05-01

By the example of environmental monitoring, some applications of geographic information systems (GIS), geostatistics, metadata banking, and Classification and Regression Trees (CART) are presented. These tools are recommended for mapping statistically estimated hot spots of vectors and pathogens. GIS were introduced as tools for spatially modelling the real world. The modelling can be done by mapping objects according to the spatial information content of data. Additionally, this can be supported by geostatistical and multivariate statistical modelling. This is demonstrated by the example of modelling marine habitats of benthic communities and of terrestrial ecoregions. Such ecoregionalisations may be used to predict phenomena based on the statistical relation between measurements of an interesting phenomenon such as, e.g., the incidence of medically relevant species and correlated characteristics of the ecoregions. The combination of meteorological data and data on plant phenology can enhance the spatial resolution of the information on climate change. To this end, meteorological and phenological data have to be correlated. To enable this, both data sets which are from disparate monitoring networks have to be spatially connected by means of geostatistical estimation. This is demonstrated by the example of transformation of site-specific data on plant phenology into surface data. The analysis allows for spatial comparison of the phenology during the two periods 1961-1990 and 1991-2002 covering whole Germany. The changes in both plant phenology and air temperature were proved to be statistically significant. Thus, they can be combined by GIS overlay technique to enhance the spatial resolution of the information on the climate change and use them for the prediction of vector incidences at the regional scale. The localisation of such risk hot spots can be done by geometrically merging surface data on promoting factors. This is demonstrated by the example of the transfer of heavy metals through soils. The predicted hot spots of heavy metal transfer can be validated empirically by measurement data which can be inquired by a metadata base linked with a geographic information system. A corresponding strategy for the detection of vector hot spots in medical epidemiology is recommended. Data on incidences and habitats of the Anophelinae in the marsh regions of Lower Saxony (Germany) were used to calculate a habitat model by CART, which together with climate data and data on ecoregions can be further used for the prediction of habitats of medically relevant vector species. In the future, this approach should be supported by an internet-based information system consisting of three components: metadata questionnaire, metadata base, and GIS to link metadata, surface data, and measurement data on incidences and habitats of medically relevant species and related data on climate, phenology, and ecoregional characteristic conditions.

Associating uncertainty with datasets using Linked Data and allowing propagation via provenance chains

NASA Astrophysics Data System (ADS)

Car, Nicholas; Cox, Simon; Fitch, Peter

2015-04-01

With earth-science datasets increasingly being published to enable re-use in projects disassociated from the original data acquisition or generation, there is an urgent need for associated metadata to be connected, in order to guide their application. In particular, provenance traces should support the evaluation of data quality and reliability. However, while standards for describing provenance are emerging (e.g. PROV-O), these do not include the necessary statistical descriptors and confidence assessments. UncertML has a mature conceptual model that may be used to record uncertainty metadata. However, by itself UncertML does not support the representation of uncertainty of multi-part datasets, and provides no direct way of associating the uncertainty information - metadata in relation to a dataset - with dataset objects.We present a method to address both these issues by combining UncertML with PROV-O, and delivering resulting uncertainty-enriched provenance traces through the Linked Data API. UncertProv extends the PROV-O provenance ontology with an RDF formulation of the UncertML conceptual model elements, adds further elements to support uncertainty representation without a conceptual model and the integration of UncertML through links to documents. The Linked ID API provides a systematic way of navigating from dataset objects to their UncertProv metadata and back again. The Linked Data API's 'views' capability enables access to UncertML and non-UncertML uncertainty metadata representations for a dataset. With this approach, it is possible to access and navigate the uncertainty metadata associated with a published dataset using standard semantic web tools, such as SPARQL queries. Where the uncertainty data follows the UncertML model it can be automatically interpreted and may also support automatic uncertainty propagation . Repositories wishing to enable uncertainty propagation for all datasets must ensure that all elements that are associated with uncertainty (PROV-O Entity and Activity classes) have UncertML elements recorded. This methodology is intentionally flexible to allow uncertainty metadata in many forms, not limited to UncertML. While the more formal representation of uncertainty metadata is desirable (using UncertProv elements to implement the UncertML conceptual model ), this will not always be possible, and any uncertainty data stored will be better than none. Since the UncertProv ontology contains a superset of UncertML elements to facilitate the representation of non-UncertML uncertainty data, it could easily be extended to include other formal uncertainty conceptual models thus allowing non-UncertML propagation calculations.

Repository Profiles for Atmospheric and Climate Sciences: Capabilities and Trends in Data Services

NASA Astrophysics Data System (ADS)

Hou, C. Y.; Thompson, C. A.; Palmer, C. L.

2014-12-01

As digital research data proliferate and expectations for open access escalate, the landscape of data repositories is becoming more complex. For example, DataBib currently identifies 980 data repositories across the disciplines, with 117 categorized under Geosciences. In atmospheric and climate sciences, there are great expectations for the integration and reuse of data for advancing science. To realize this potential, resources are needed that explicate the range of repository options available for locating and depositing open data, their conditions of access and use, and the services and tools they provide. This study profiled 38 open digital repositories in the atmospheric and climate sciences, analyzing each on 55 criteria through content analysis of their websites. The results provide a systematic way to assess and compare capabilities, services, and institutional characteristics and identify trends across repositories. Selected results from the more detailed outcomes to be presented: Most repositories offer guidance on data format(s) for submission and dissemination. 42% offer authorization-free access. More than half use some type of data identification system such as DOIs. Nearly half offer some data processing, with a similar number providing software or tools. 78.9% request that users cite or acknowledge datasets used and the data center. Only 21.1% recommend specific metadata standards, such as ISO 19115 or Dublin Core, with more than half utilizing a customized metadata scheme. Information was rarely provided on repository certification and accreditation and uneven for transfer of rights and data security. Few provided policy information on preservation, migration, reappraisal, disposal, or long-term sustainability. As repository use increases, it will be important for institutions to make their procedures and policies explicit, to build trust with user communities and improve efficiencies in data sharing. Resources such as repository profiles will be essential for scientists to weigh options and understand trends in data services across the evolving network of repositories.

Metadata for Web Resources: How Metadata Works on the Web.

ERIC Educational Resources Information Center

Dillon, Martin

This paper discusses bibliographic control of knowledge resources on the World Wide Web. The first section sets the context of the inquiry. The second section covers the following topics related to metadata: (1) definitions of metadata, including metadata as tags and as descriptors; (2) metadata on the Web, including general metadata systems,…

Harvesting NASA's Common Metadata Repository (CMR)

NASA Technical Reports Server (NTRS)

Shum, Dana; Durbin, Chris; Norton, James; Mitchell, Andrew

2017-01-01

As part of NASA's Earth Observing System Data and Information System (EOSDIS), the Common Metadata Repository (CMR) stores metadata for over 30,000 datasets from both NASA and international providers along with over 300M granules. This metadata enables sub-second discovery and facilitates data access. While the CMR offers a robust temporal, spatial and keyword search functionality to the general public and international community, it is sometimes more desirable for international partners to harvest the CMR metadata and merge the CMR metadata into a partner's existing metadata repository. This poster will focus on best practices to follow when harvesting CMR metadata to ensure that any changes made to the CMR can also be updated in a partner's own repository. Additionally, since each partner has distinct metadata formats they are able to consume, the best practices will also include guidance on retrieving the metadata in the desired metadata format using CMR's Unified Metadata Model translation software.

Harvesting NASA's Common Metadata Repository

NASA Astrophysics Data System (ADS)

Shum, D.; Mitchell, A. E.; Durbin, C.; Norton, J.

2017-12-01

As part of NASA's Earth Observing System Data and Information System (EOSDIS), the Common Metadata Repository (CMR) stores metadata for over 30,000 datasets from both NASA and international providers along with over 300M granules. This metadata enables sub-second discovery and facilitates data access. While the CMR offers a robust temporal, spatial and keyword search functionality to the general public and international community, it is sometimes more desirable for international partners to harvest the CMR metadata and merge the CMR metadata into a partner's existing metadata repository. This poster will focus on best practices to follow when harvesting CMR metadata to ensure that any changes made to the CMR can also be updated in a partner's own repository. Additionally, since each partner has distinct metadata formats they are able to consume, the best practices will also include guidance on retrieving the metadata in the desired metadata format using CMR's Unified Metadata Model translation software.

Bridging Archival Standards: Building Software to Translate Metadata Between PDS3 and PDS4

NASA Astrophysics Data System (ADS)

De Cesare, C. M.; Padams, J. H.

2018-04-01

Transitioning datasets from PDS3 to PDS4 requires manual and detail-oriented work. To increase efficiency and reduce human error, we've built the Label Mapping Tool, which compares a PDS3 label to a PDS4 label template and outputs mappings between the two.

Video personalization for usage environment

NASA Astrophysics Data System (ADS)

Tseng, Belle L.; Lin, Ching-Yung; Smith, John R.

2002-07-01

A video personalization and summarization system is designed and implemented incorporating usage environment to dynamically generate a personalized video summary. The personalization system adopts the three-tier server-middleware-client architecture in order to select, adapt, and deliver rich media content to the user. The server stores the content sources along with their corresponding MPEG-7 metadata descriptions. Our semantic metadata is provided through the use of the VideoAnnEx MPEG-7 Video Annotation Tool. When the user initiates a request for content, the client communicates the MPEG-21 usage environment description along with the user query to the middleware. The middleware is powered by the personalization engine and the content adaptation engine. Our personalization engine includes the VideoSue Summarization on Usage Environment engine that selects the optimal set of desired contents according to user preferences. Afterwards, the adaptation engine performs the required transformations and compositions of the selected contents for the specific usage environment using our VideoEd Editing and Composition Tool. Finally, two personalization and summarization systems are demonstrated for the IBM Websphere Portal Server and for the pervasive PDA devices.

NGEE Arctic TIR and Digital Photos, Drained Thaw Lake Basin, Barrow, Alaska, July 2015

DOE Data Explorer

Shawn Serbin; Wil Lieberman-Cribbin; Kim Ely; Alistair Rogers

2016-11-01

FLIR thermal infrared (TIR), digital camera photos, and plot notes across the Barrow, Alaska DTLB site. Data were collected together with measurements of canopy spectral reflectance (see associated metadata record (NGEE Arctic HR1024i Canopy Spectral Reflectance, Drained Thaw Lake Basin, Barrow, Alaska, July 2015 ). Data contained within this archive include exported FLIR images (analyzed with FLIR-Tools), digital photos, TIR report, and sample notes. Further TIR image analysis can be conducted in FLIR-Tools.

ASDC Advances in the Utilization of Microservices and Hybrid Cloud Environments

NASA Astrophysics Data System (ADS)

Baskin, W. E.; Herbert, A.; Mazaika, A.; Walter, J.

2017-12-01

The Atmospheric Science Data Center (ASDC) is transitioning many of its software tools and applications to standalone microservices deployable in a hybrid cloud, offering benefits such as scalability and efficient environment management. This presentation features several projects the ASDC staff have implemented leveraging the OpenShift Container Application Platform and OpenStack Hybrid Cloud Environment focusing on key tools and techniques applied to: Earth Science data processing Spatial-Temporal metadata generation, validation, repair, and curation Archived Data discovery, visualization, and access

Semantic Metadata for Heterogeneous Spatial Planning Documents

NASA Astrophysics Data System (ADS)

Iwaniak, A.; Kaczmarek, I.; Łukowicz, J.; Strzelecki, M.; Coetzee, S.; Paluszyński, W.

2016-09-01

Spatial planning documents contain information about the principles and rights of land use in different zones of a local authority. They are the basis for administrative decision making in support of sustainable development. In Poland these documents are published on the Web according to a prescribed non-extendable XML schema, designed for optimum presentation to humans in HTML web pages. There is no document standard, and limited functionality exists for adding references to external resources. The text in these documents is discoverable and searchable by general-purpose web search engines, but the semantics of the content cannot be discovered or queried. The spatial information in these documents is geographically referenced but not machine-readable. Major manual efforts are required to integrate such heterogeneous spatial planning documents from various local authorities for analysis, scenario planning and decision support. This article presents results of an implementation using machine-readable semantic metadata to identify relationships among regulations in the text, spatial objects in the drawings and links to external resources. A spatial planning ontology was used to annotate different sections of spatial planning documents with semantic metadata in the Resource Description Framework in Attributes (RDFa). The semantic interpretation of the content, links between document elements and links to external resources were embedded in XHTML pages. An example and use case from the spatial planning domain in Poland is presented to evaluate its efficiency and applicability. The solution enables the automated integration of spatial planning documents from multiple local authorities to assist decision makers with understanding and interpreting spatial planning information. The approach is equally applicable to legal documents from other countries and domains, such as cultural heritage and environmental management.

Purple L1 Milestone Review Panel GPFS Functionality and Performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loewe, W E

2006-12-01

The GPFS deliverable for the Purple system requires the functionality and performance necessary for ASC I/O needs. The functionality includes POSIX and MPIIO compatibility, and multi-TB file capability across the entire machine. The bandwidth performance required is 122.15 GB/s, as necessary for productive and defensive I/O requirements, and the metadata performance requirement is 5,000 file stats per second. To determine success for this deliverable, several tools are employed. For functionality testing of POSIX, 10TB-files, and high-node-count capability, the parallel file system bandwidth performance test IOR is used. IOR is an MPI-coordinated application that can write and then read to amore » single shared file or to an individual file per process and check the data integrity of the file(s). The MPIIO functionality is tested with the MPIIO test suite from the MPICH library. Bandwidth performance is tested using IOR for the required 122.15 GB/s sustained write. All IOR tests are performanced with data checking enabled. Metadata performance is tested after ''aging'' the file system with 80% data block usage and 20% inode usage. The fdtree metadata test is expected to create/remove a large directory/file structure in under 20 minutes time, akin to interactive metadata usage. Multiple (10) instances of ''ls -lR'', each performing over 100K stats, are run concurrently in different large directories to demonstrate 5,000 stats/sec.« less

Combining Crowd and Expert Labels using Decision Theoretic Active Learning

DTIC Science & Technology

2015-10-11

meta-data such as titles, author information and keywords. Motivating Application: Biomedical Systematic Reviews Evidence - based medicine (EBM) aims to...individuals trained in evidence - based medicine ; usually MDs) reading the entire set of citations retrieved via database search to identify the small

Assessing Metadata Quality of a Federally Sponsored Health Data Repository.

PubMed

Marc, David T; Beattie, James; Herasevich, Vitaly; Gatewood, Laël; Zhang, Rui

2016-01-01

The U.S. Federal Government developed HealthData.gov to disseminate healthcare datasets to the public. Metadata is provided for each datasets and is the sole source of information to find and retrieve data. This study employed automated quality assessments of the HealthData.gov metadata published from 2012 to 2014 to measure completeness, accuracy, and consistency of applying standards. The results demonstrated that metadata published in earlier years had lower completeness, accuracy, and consistency. Also, metadata that underwent modifications following their original creation were of higher quality. HealthData.gov did not uniformly apply Dublin Core Metadata Initiative to the metadata, which is a widely accepted metadata standard. These findings suggested that the HealthData.gov metadata suffered from quality issues, particularly related to information that wasn't frequently updated. The results supported the need for policies to standardize metadata and contributed to the development of automated measures of metadata quality.

Assessing Metadata Quality of a Federally Sponsored Health Data Repository

PubMed Central

Marc, David T.; Beattie, James; Herasevich, Vitaly; Gatewood, Laël; Zhang, Rui

2016-01-01

The U.S. Federal Government developed HealthData.gov to disseminate healthcare datasets to the public. Metadata is provided for each datasets and is the sole source of information to find and retrieve data. This study employed automated quality assessments of the HealthData.gov metadata published from 2012 to 2014 to measure completeness, accuracy, and consistency of applying standards. The results demonstrated that metadata published in earlier years had lower completeness, accuracy, and consistency. Also, metadata that underwent modifications following their original creation were of higher quality. HealthData.gov did not uniformly apply Dublin Core Metadata Initiative to the metadata, which is a widely accepted metadata standard. These findings suggested that the HealthData.gov metadata suffered from quality issues, particularly related to information that wasn’t frequently updated. The results supported the need for policies to standardize metadata and contributed to the development of automated measures of metadata quality. PMID:28269883

A Methadology for Near-Real-Time Access to Environmental Data through Federation

NASA Astrophysics Data System (ADS)

Orcutt, J. A.; Rajasekar, A.; Moore, R. W.; Vernon, F.

2015-12-01

The availability of near-real-time data can be critical for response to rapid changes including violent storms, tsunamis and earthquakes. While climate changes relatively slowly, compared to a tsunami, the increasing variance in weather over time and warming must also be considered in terms of civil impacts. A simple example is the decreasing resilience of coastal communities to severe weather as sea level increases. The integration of these data for modeling and response activities in near-real-time must be pursued to make data collection practical. We present an approach to data and metadata integration that has occurred over the past 10-20 years in Earth and Ocean sciences that provide a model for the future. The NSF Data Federation Consortium (DFC) is working to integrate data and metadata from a number of fields using iRODS (Integrated Rule-Oriented Data System). iRODS is open source software for building distributed data collections. In particular, the SCION (SCIence Observatory Network) funded by the NSF provides Python-based software for data and metadata access from a variety of near-real-time data sets relevant to climate studies including weather and hazards from other observational systems. As an example, we are working on the integration of data on shore and offshore in southern California using resources from the High Performance Wireless Research and Education Network (HPWREN) and the Southern California Coastal Ocean Observing System (SCCOOS). National and International integration of near-real-time earthquake data through the Incorporated Research Institutions for Seismology (IRIS) and the International Federation of Digital Seismic Networks (FDSN) provide a well-integrated data and metadata system for both research and civil uses. ObsPy, written in Python, has proved to be a highly successful methodology for accessing global data from thousands of stations with well-developed metadata. The persistence of the data and metadata, in turn, provides long-term provenance particularly important for climate data. We discuss these various tools and the current state of efforts in broader integration of Earth data.

Managing Data, Provenance and Chaos through Standardization and Automation at the Georgia Coastal Ecosystems LTER Site

NASA Astrophysics Data System (ADS)

Sheldon, W.

2013-12-01

Managing data for a large, multidisciplinary research program such as a Long Term Ecological Research (LTER) site is a significant challenge, but also presents unique opportunities for data stewardship. LTER research is conducted within multiple organizational frameworks (i.e. a specific LTER site as well as the broader LTER network), and addresses both specific goals defined in an NSF proposal as well as broader goals of the network; therefore, every LTER data can be linked to rich contextual information to guide interpretation and comparison. The challenge is how to link the data to this wealth of contextual metadata. At the Georgia Coastal Ecosystems LTER we developed an integrated information management system (GCE-IMS) to manage, archive and distribute data, metadata and other research products as well as manage project logistics, administration and governance (figure 1). This system allows us to store all project information in one place, and provide dynamic links through web applications and services to ensure content is always up to date on the web as well as in data set metadata. The database model supports tracking changes over time in personnel roles, projects and governance decisions, allowing these databases to serve as canonical sources of project history. Storing project information in a central database has also allowed us to standardize both the formatting and content of critical project information, including personnel names, roles, keywords, place names, attribute names, units, and instrumentation, providing consistency and improving data and metadata comparability. Lookup services for these standard terms also simplify data entry in web and database interfaces. We have also coupled the GCE-IMS to our MATLAB- and Python-based data processing tools (i.e. through database connections) to automate metadata generation and packaging of tabular and GIS data products for distribution. Data processing history is automatically tracked throughout the data lifecycle, from initial import through quality control, revision and integration by our data processing system (GCE Data Toolbox for MATLAB), and included in metadata for versioned data products. This high level of automation and system integration has proven very effective in managing the chaos and scalability of our information management program.

Hyper Text Mark-up Language and Dublin Core metadata element set usage in websites of Iranian State Universities' libraries.

PubMed

Zare-Farashbandi, Firoozeh; Ramezan-Shirazi, Mahtab; Ashrafi-Rizi, Hasan; Nouri, Rasool

2014-01-01

Recent progress in providing innovative solutions in the organization of electronic resources and research in this area shows a global trend in the use of new strategies such as metadata to facilitate description, place for, organization and retrieval of resources in the web environment. In this context, library metadata standards have a special place; therefore, the purpose of the present study has been a comparative study on the Central Libraries' Websites of Iran State Universities for Hyper Text Mark-up Language (HTML) and Dublin Core metadata elements usage in 2011. The method of this study is applied-descriptive and data collection tool is the check lists created by the researchers. Statistical community includes 98 websites of the Iranian State Universities of the Ministry of Health and Medical Education and Ministry of Science, Research and Technology and method of sampling is the census. Information was collected through observation and direct visits to websites and data analysis was prepared by Microsoft Excel software, 2011. The results of this study indicate that none of the websites use Dublin Core (DC) metadata and that only a few of them have used overlaps elements between HTML meta tags and Dublin Core (DC) elements. The percentage of overlaps of DC elements centralization in the Ministry of Health were 56% for both description and keywords and, in the Ministry of Science, were 45% for the keywords and 39% for the description. But, HTML meta tags have moderate presence in both Ministries, as the most-used elements were keywords and description (56%) and the least-used elements were date and formatter (0%). It was observed that the Ministry of Health and Ministry of Science follows the same path for using Dublin Core standard on their websites in the future. Because Central Library Websites are an example of scientific web pages, special attention in designing them can help the researchers to achieve faster and more accurate information resources. Therefore, the influence of librarians' ideas on the awareness of web designers and developers will be important for using metadata elements as general, and specifically for applying such standards.

Hyper Text Mark-up Language and Dublin Core metadata element set usage in websites of Iranian State Universities’ libraries

PubMed Central

Zare-Farashbandi, Firoozeh; Ramezan-Shirazi, Mahtab; Ashrafi-Rizi, Hasan; Nouri, Rasool

2014-01-01

Introduction: Recent progress in providing innovative solutions in the organization of electronic resources and research in this area shows a global trend in the use of new strategies such as metadata to facilitate description, place for, organization and retrieval of resources in the web environment. In this context, library metadata standards have a special place; therefore, the purpose of the present study has been a comparative study on the Central Libraries’ Websites of Iran State Universities for Hyper Text Mark-up Language (HTML) and Dublin Core metadata elements usage in 2011. Materials and Methods: The method of this study is applied-descriptive and data collection tool is the check lists created by the researchers. Statistical community includes 98 websites of the Iranian State Universities of the Ministry of Health and Medical Education and Ministry of Science, Research and Technology and method of sampling is the census. Information was collected through observation and direct visits to websites and data analysis was prepared by Microsoft Excel software, 2011. Results: The results of this study indicate that none of the websites use Dublin Core (DC) metadata and that only a few of them have used overlaps elements between HTML meta tags and Dublin Core (DC) elements. The percentage of overlaps of DC elements centralization in the Ministry of Health were 56% for both description and keywords and, in the Ministry of Science, were 45% for the keywords and 39% for the description. But, HTML meta tags have moderate presence in both Ministries, as the most-used elements were keywords and description (56%) and the least-used elements were date and formatter (0%). Conclusion: It was observed that the Ministry of Health and Ministry of Science follows the same path for using Dublin Core standard on their websites in the future. Because Central Library Websites are an example of scientific web pages, special attention in designing them can help the researchers to achieve faster and more accurate information resources. Therefore, the influence of librarians’ ideas on the awareness of web designers and developers will be important for using metadata elements as general, and specifically for applying such standards. PMID:24741646

A high-precision rule-based extraction system for expanding geospatial metadata in GenBank records.

PubMed

Tahsin, Tasnia; Weissenbacher, Davy; Rivera, Robert; Beard, Rachel; Firago, Mari; Wallstrom, Garrick; Scotch, Matthew; Gonzalez, Graciela

2016-09-01

The metadata reflecting the location of the infected host (LOIH) of virus sequences in GenBank often lacks specificity. This work seeks to enhance this metadata by extracting more specific geographic information from related full-text articles and mapping them to their latitude/longitudes using knowledge derived from external geographical databases. We developed a rule-based information extraction framework for linking GenBank records to the latitude/longitudes of the LOIH. Our system first extracts existing geospatial metadata from GenBank records and attempts to improve it by seeking additional, relevant geographic information from text and tables in related full-text PubMed Central articles. The final extracted locations of the records, based on data assimilated from these sources, are then disambiguated and mapped to their respective geo-coordinates. We evaluated our approach on a manually annotated dataset comprising of 5728 GenBank records for the influenza A virus. We found the precision, recall, and f-measure of our system for linking GenBank records to the latitude/longitudes of their LOIH to be 0.832, 0.967, and 0.894, respectively. Our system had a high level of accuracy for linking GenBank records to the geo-coordinates of the LOIH. However, it can be further improved by expanding our database of geospatial data, incorporating spell correction, and enhancing the rules used for extraction. Our system performs reasonably well for linking GenBank records for the influenza A virus to the geo-coordinates of their LOIH based on record metadata and information extracted from related full-text articles. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Partnerships To Mine Unexploited Sources of Metadata.

ERIC Educational Resources Information Center

Reynolds, Regina Romano

This paper discusses the metadata created for other purposes as a potential source of bibliographic data. The first section addresses collecting metadata by means of templates, including the Nordic Metadata Project's Dublin Core Metadata Template. The second section considers potential partnerships for re-purposing metadata for bibliographic use,…

The Arctic Cooperative Data and Information System: Data Management Support for the NSF Arctic Research Program (Invited)

NASA Astrophysics Data System (ADS)

Moore, J.; Serreze, M. C.; Middleton, D.; Ramamurthy, M. K.; Yarmey, L.

2013-12-01

The NSF funds the Advanced Cooperative Arctic Data and Information System (ACADIS), url: (http://www.aoncadis.org/). It serves the growing and increasingly diverse data management needs of NSF's arctic research community. The ACADIS investigator team combines experienced data managers, curators and software engineers from the NSIDC, UCAR and NCAR. ACADIS fosters scientific synthesis and discovery by providing a secure long-term data archive to NSF investigators. The system provides discovery and access to arctic related data from this and other archives. This paper updates the technical components of ACADIS, the implementation of best practices, the value of ACADIS to the community and the major challenges facing this archive for the future in handling the diverse data coming from NSF Arctic investigators. ACADIS provides sustainable data management, data stewardship services and leadership for the NSF Arctic research community through open data sharing, adherence to best practices and standards, capitalizing on appropriate evolving technologies, community support and engagement. ACADIS leverages other pertinent projects, capitalizing on appropriate emerging technologies and participating in emerging cyberinfrastructure initiatives. The key elements of ACADIS user services to the NSF Arctic community include: data and metadata upload; support for datasets with special requirements; metadata and documentation generation; interoperability and initiatives with other archives; and science support to investigators and the community. Providing a self-service data publishing platform requiring minimal curation oversight while maintaining rich metadata for discovery, access and preservation is challenging. Implementing metadata standards are a first step towards consistent content. The ACADIS Gateway and ADE offer users choices for data discovery and access with the clear objective of increasing discovery and use of all Arctic data especially for analysis activities. Metadata is at the core of ACADIS activities, from capturing metadata at the point of data submission to ensuring interoperability , providing data citations, and supporting data discovery. ACADIS metadata efforts include: 1) Evolution of the ACADIS metadata profile to increase flexibility in search; 2) Documentation guidelines; and 3) Metadata standardization efforts. A major activity is now underway to ensure consistency in the metadata profile across all archived datasets. ACADIS is embarking on a critical activity to create Digital Object Identifiers (DOI) for all its holdings. The data services offered by ACADIS focus on meeting the needs of the data providers, providing dynamic search capabilities to peruse the ACADIS and related cyrospheric data repositories, efficient data download and some special services including dataset reformatting and visualization. The service is built around of the following key technical elements: The ACADIS Gateway housed at NCAR has been developed to support NSF Arctic data coming from AON and now broadly across PLR/ARC and related archives: The Arctic Data Explorer (ADE) developed at NSIDC is an integral service of ACADIS bringing the rich archive from NSIDC together with catalogs from ACADIS and international partners in Arctic research: and Rosetta and the Digital Object Identifier (DOI) generation scheme are tools available to the community to help publish and utilize datasets in integration and synthesis and publication.

Informatics methods to enable sharing of quantitative imaging research data.

PubMed

Levy, Mia A; Freymann, John B; Kirby, Justin S; Fedorov, Andriy; Fennessy, Fiona M; Eschrich, Steven A; Berglund, Anders E; Fenstermacher, David A; Tan, Yongqiang; Guo, Xiaotao; Casavant, Thomas L; Brown, Bartley J; Braun, Terry A; Dekker, Andre; Roelofs, Erik; Mountz, James M; Boada, Fernando; Laymon, Charles; Oborski, Matt; Rubin, Daniel L

2012-11-01

The National Cancer Institute Quantitative Research Network (QIN) is a collaborative research network whose goal is to share data, algorithms and research tools to accelerate quantitative imaging research. A challenge is the variability in tools and analysis platforms used in quantitative imaging. Our goal was to understand the extent of this variation and to develop an approach to enable sharing data and to promote reuse of quantitative imaging data in the community. We performed a survey of the current tools in use by the QIN member sites for representation and storage of their QIN research data including images, image meta-data and clinical data. We identified existing systems and standards for data sharing and their gaps for the QIN use case. We then proposed a system architecture to enable data sharing and collaborative experimentation within the QIN. There are a variety of tools currently used by each QIN institution. We developed a general information system architecture to support the QIN goals. We also describe the remaining architecture gaps we are developing to enable members to share research images and image meta-data across the network. As a research network, the QIN will stimulate quantitative imaging research by pooling data, algorithms and research tools. However, there are gaps in current functional requirements that will need to be met by future informatics development. Special attention must be given to the technical requirements needed to translate these methods into the clinical research workflow to enable validation and qualification of these novel imaging biomarkers. Copyright © 2012 Elsevier Inc. All rights reserved.

A Prototype for Content-Rich Decision-Making Support in NOAA using Data as an Asset

NASA Astrophysics Data System (ADS)

Austin, M.; Peng, G.

2015-12-01

Data Producers and Data Providers do not always collaborate to ensure that the data meets the needs of a broad range of user communities. User needs are not always considered in the beginning of the data production and delivery phases. Often data experts are required to explain or create custom output so that the data can be used by decision makers. Lack of documentation and quality information can result in poor user acceptance or data misinterpretation. This presentation will describe how new content integration tools have been created by NOAA's National Environmental Satellite, Data, and Information Service (NESDIS) to improve quality throughout the data management lifecycle. The prototype integrates contents into a decision-making support tool from NOAA's Observing System Integrated Assessment (NOSIA) Value Tree, NOAA's Data Catalog/Digital Object Identifier (DOI) projects (collection-level metadata) and Data/Stewardship Maturity Matrices (Data and Stewardship Quality Rating Information). The National Centers for Environmental Information's (NCEI) Global Historical Climatology Network-Monthly (GHCN) dataset is used as a case study to formulate/develop the prototype tool and demonstrate its power with the content-centric approach in addition to completeness of metadata elements. This demonstrates the benefits of the prototype tool in both bottom roll-up and top roll-down fashion. The prototype tool delivers a standards based methodology that allows users to determine the quality and value of data that is fit for purpose. It encourages data producers and data providers/stewards to consider users' needs prior to data creation and dissemination resulting in user driven data requirements increasing return on investment.

Linked Ocean Data

NASA Astrophysics Data System (ADS)

Leadbetter, Adam; Arko, Robert; Chandler, Cynthia; Shepherd, Adam

2014-05-01

"Linked Data" is a term used in Computer Science to encapsulate a methodology for publishing data and metadata in a structured format so that links may be created and exploited between objects. Berners-Lee (2006) outlines the following four design principles of a Linked Data system: Use Uniform Resource Identifiers (URIs) as names for things. Use HyperText Transfer Protocol (HTTP) URIs so that people can look up those names. When someone looks up a URI, provide useful information, using the standards (Resource Description Framework [RDF] and the RDF query language [SPARQL]). Include links to other URIs so that they can discover more things. In 2010, Berners-Lee revisited his original design plan for Linked Data to encourage data owners along a path to "good Linked Data". This revision involved the creation of a five star rating system for Linked Data outlined below. One star: Available on the web (in any format). Two stars: Available as machine-readable structured data (e.g. An Excel spreadsheet instead of an image scan of a table). Three stars: As two stars plus the use of a non-proprietary format (e.g. Comma Separated Values instead of Excel). Four stars: As three stars plus the use of open standards from the World Wide Web Commission (W3C) (i.e. RDF and SPARQL) to identify things, so that people can point to your data and metadata. Five stars: All the above plus link your data to other people's data to provide context Here we present work building on the SeaDataNet common vocabularies served by the NERC Vocabulary Server, connecting projects such as the Rolling Deck to Repository (R2R) and the Biological and Chemical Oceanography Data Management Office (BCO-DMO) and other vocabularies such as the Marine Metadata Interoperability Ontology Register and Repository and the NASA Global Change Master Directory to create a Linked Ocean Data cloud. Publishing the vocabularies and metadata in standard RDF XML and exposing SPARQL endpoints renders them five-star Linked Data repositories. The benefits of this approach include: increased interoperability between the metadata created by projects; improved data discovery as users of SeaDataNet, R2R and BCO-DMO terms can find data using labels with which they are familiar both standard tools and newly developed custom tools may be used to explore the data; and using standards means the custom tools are easier to develop Linked Data is a concept which has been in existence for nearly a decade, and has a simple set of formal best practices associated with it. Linked Data is increasingly being seen as a driver of the next generation of "community science" activities. While many data providers in the oceanographic domain may be unaware of Linked Data, they may also be providing it at one of its lower levels. Here we have shown that it is possible to deliver the highest standard of Linked Oceanographic Data, and some of the benefits of the approach.

A Window to the World: Lessons Learned from NASA's Collaborative Metadata Curation Effort

NASA Astrophysics Data System (ADS)

Bugbee, K.; Dixon, V.; Baynes, K.; Shum, D.; le Roux, J.; Ramachandran, R.

2017-12-01

Well written descriptive metadata adds value to data by making data easier to discover as well as increases the use of data by providing the context or appropriateness of use. While many data centers acknowledge the importance of correct, consistent and complete metadata, allocating resources to curate existing metadata is often difficult. To lower resource costs, many data centers seek guidance on best practices for curating metadata but struggle to identify those recommendations. In order to assist data centers in curating metadata and to also develop best practices for creating and maintaining metadata, NASA has formed a collaborative effort to improve the Earth Observing System Data and Information System (EOSDIS) metadata in the Common Metadata Repository (CMR). This effort has taken significant steps in building consensus around metadata curation best practices. However, this effort has also revealed gaps in EOSDIS enterprise policies and procedures within the core metadata curation task. This presentation will explore the mechanisms used for building consensus on metadata curation, the gaps identified in policies and procedures, the lessons learned from collaborating with both the data centers and metadata curation teams, and the proposed next steps for the future.

Standards-based curation of a decade-old digital repository dataset of molecular information.

PubMed

Harvey, Matthew J; Mason, Nicholas J; McLean, Andrew; Murray-Rust, Peter; Rzepa, Henry S; Stewart, James J P

2015-01-01

The desirable curation of 158,122 molecular geometries derived from the NCI set of reference molecules together with associated properties computed using the MOPAC semi-empirical quantum mechanical method and originally deposited in 2005 into the Cambridge DSpace repository as a data collection is reported. The procedures involved in the curation included annotation of the original data using new MOPAC methods, updating the syntax of the CML documents used to express the data to ensure schema conformance and adding new metadata describing the entries together with a XML schema transformation to map the metadata schema to that used by the DataCite organisation. We have adopted a granularity model in which a DataCite persistent identifier (DOI) is created for each individual molecule to enable data discovery and data metrics at this level using DataCite tools. We recommend that the future research data management (RDM) of the scientific and chemical data components associated with journal articles (the "supporting information") should be conducted in a manner that facilitates automatic periodic curation. Graphical abstractStandards and metadata-based curation of a decade-old digital repository dataset of molecular information.

A Metadata description of the data in "A metabolomic comparison of urinary changes in type 2 diabetes in mouse, rat, and human."

PubMed Central

2011-01-01

Background Metabolomics is a rapidly developing functional genomic tool that has a wide range of applications in diverse fields in biology and medicine. However, unlike transcriptomics and proteomics there is currently no central repository for the depositing of data despite efforts by the Metabolomics Standard Initiative (MSI) to develop a standardised description of a metabolomic experiment. Findings In this manuscript we describe how the MSI description has been applied to a published dataset involving the identification of cross-species metabolic biomarkers associated with type II diabetes. The study describes sample collection of urine from mice, rats and human volunteers, and the subsequent acquisition of data by high resolution 1H NMR spectroscopy. The metadata is described to demonstrate how the MSI descriptions could be applied in a manuscript and the spectra have also been made available for the mouse and rat studies to allow others to process the data. Conclusions The intention of this manuscript is to stimulate discussion as to whether the MSI description is sufficient to describe the metadata associated with metabolomic experiments and encourage others to make their data available to other researchers. PMID:21801423

New Version of SeismicHandler (SHX) based on ObsPy

NASA Astrophysics Data System (ADS)

Stammler, Klaus; Walther, Marcus

2016-04-01

The command line version of SeismicHandler (SH), a scientific analysis tool for seismic waveform data developed around 1990, has been redesigned in the recent years, based on a project funded by the Deutsche Forschungsgemeinschaft (DFG). The aim was to address new data access techniques, simplified metadata handling and a modularized software design. As a result the program was rewritten in Python in its main parts, taking advantage of simplicity of this script language and its variety of well developed software libraries, including ObsPy. SHX provides an easy access to waveforms and metadata via arclink and FDSN webservice protocols, also access to event catalogs is implemented. With single commands whole networks or stations within a certain area may be read in, the metadata are retrieved from the servers and stored in a local database. For data processing the large set of SH commands is available, as well as the SH scripting language. Via this SH language scripts or additional Python modules the command set of SHX is easily extendable. The program is open source, tested on Linux operating systems, documentation and download is found at URL "https://www.seismic-handler.org/".

Exploring Cultural Heritage Resources in a 3d Collaborative Environment

NASA Astrophysics Data System (ADS)

Respaldiza, A.; Wachowicz, M.; Vázquez Hoehne, A.

2012-06-01

Cultural heritage is a complex and diverse concept, which brings together a wide domain of information. Resources linked to a cultural heritage site may consist of physical artefacts, books, works of art, pictures, historical maps, aerial photographs, archaeological surveys and 3D models. Moreover, all these resources are listed and described by a set of a variety of metadata specifications that allow their online search and consultation on the most basic characteristics of them. Some examples include Norma ISO 19115, Dublin Core, AAT, CDWA, CCO, DACS, MARC, MoReq, MODS, MuseumDat, TGN, SPECTRUM, VRA Core and Z39.50. Gateways are in place to fit in these metadata standards into those used in a SDI (ISO 19115 or INSPIRE), but substantial work still remains to be done for the complete incorporation of cultural heritage information. Therefore, the aim of this paper is to demonstrate how the complexity of cultural heritage resources can be dealt with by a visual exploration of their metadata within a 3D collaborative environment. The 3D collaborative environments are promising tools that represent the new frontier of our capacity of learning, understanding, communicating and transmitting culture.

CI-KNOW: Cyberinfrastructure Knowledge Networks on the Web. A Social Network Enabled Recommender System for Locating Resources in Cyberinfrastructures

NASA Astrophysics Data System (ADS)

Green, H. D.; Contractor, N. S.; Yao, Y.

2006-12-01

A knowledge network is a multi-dimensional network created from the interactions and interconnections among the scientists, documents, data, analytic tools, and interactive collaboration spaces (like forums and wikis) associated with a collaborative environment. CI-KNOW is a suite of software tools that leverages automated data collection, social network theories, analysis techniques and algorithms to infer an individual's interests and expertise based on their interactions and activities within a knowledge network. The CI-KNOW recommender system mines the knowledge network associated with a scientific community's use of cyberinfrastructure tools and uses relational metadata to record connections among entities in the knowledge network. Recent developments in social network theories and methods provide the backbone for a modular system that creates recommendations from relational metadata. A network navigation portlet allows users to locate colleagues, documents, data or analytic tools in the knowledge network and to explore their networks through a visual, step-wise process. An internal auditing portlet offers administrators diagnostics to assess the growth and health of the entire knowledge network. The first instantiation of the prototype CI-KNOW system is part of the Environmental Cyberinfrastructure Demonstration project at the National Center for Supercomputing Applications, which supports the activities of hydrologic and environmental science communities (CLEANER and CUAHSI) under the umbrella of the WATERS network environmental observatory planning activities (http://cleaner.ncsa.uiuc.edu). This poster summarizes the key aspects of the CI-KNOW system, highlighting the key inputs, calculation mechanisms, and output modalities.

The MAR databases: development and implementation of databases specific for marine metagenomics.

PubMed

Klemetsen, Terje; Raknes, Inge A; Fu, Juan; Agafonov, Alexander; Balasundaram, Sudhagar V; Tartari, Giacomo; Robertsen, Espen; Willassen, Nils P

2018-01-04

We introduce the marine databases; MarRef, MarDB and MarCat (https://mmp.sfb.uit.no/databases/), which are publicly available resources that promote marine research and innovation. These data resources, which have been implemented in the Marine Metagenomics Portal (MMP) (https://mmp.sfb.uit.no/), are collections of richly annotated and manually curated contextual (metadata) and sequence databases representing three tiers of accuracy. While MarRef is a database for completely sequenced marine prokaryotic genomes, which represent a marine prokaryote reference genome database, MarDB includes all incomplete sequenced prokaryotic genomes regardless level of completeness. The last database, MarCat, represents a gene (protein) catalog of uncultivable (and cultivable) marine genes and proteins derived from marine metagenomics samples. The first versions of MarRef and MarDB contain 612 and 3726 records, respectively. Each record is built up of 106 metadata fields including attributes for sampling, sequencing, assembly and annotation in addition to the organism and taxonomic information. Currently, MarCat contains 1227 records with 55 metadata fields. Ontologies and controlled vocabularies are used in the contextual databases to enhance consistency. The user-friendly web interface lets the visitors browse, filter and search in the contextual databases and perform BLAST searches against the corresponding sequence databases. All contextual and sequence databases are freely accessible and downloadable from https://s1.sfb.uit.no/public/mar/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

An Approach to a Digital Library of Newspapers.

ERIC Educational Resources Information Center

Arambura Cabo, Maria Jose; Berlanga Llavori, Rafael

1997-01-01

Presents a new application for retrieving news from a large electronic bank of newspapers that is intended to manage past issues of newspapers. Highlights include a data model for newspapers, including metadata and metaclasses; document definition language; document retrieval language; and memory organization and indexes. (Author/LRW)

The Next Stage: Moving from Isolated Digital Collections to Interoperable Digital Libraries.

ERIC Educational Resources Information Center

Besser, Howard

2002-01-01

Presents a conceptual framework for digital library development and discusses how to move from isolated digital collections to interoperable digital libraries. Topics include a history of digital libraries; user-centered architecture; stages of technological development; standards, including metadata; and best practices. (Author/LRW)

Google Scholar's Ghost Authors

ERIC Educational Resources Information Center

Jacso, Peter

2009-01-01

In the journal "The Chronicle of Higher Education," an article by Geoffrey Nunberg criticizes Google's Book Search (GBS), emphasizing that disturbing errors are endemic. He recognizes that for mainstream "googling" purposes, "they don't really care about metadata provided by a library catalog." In perhaps his most discouraging point, linguistics…

Collection Evaluation and Evolution

NASA Technical Reports Server (NTRS)

Habermann, Ted; Kozimor, John

2017-01-01

We will review metadata evaluation tools and share results from our most recent CMR analysis. We will demonstrate results using Google spreadsheets and present new results in terms of number of records that include specific content. We will show evolution of UMM-compliance over time and also show results of comparing various CMR collections (NASA, non-NASA, and SciOps).

Embracing the Archives: How NPR Librarians Turned Their Collection into a Workflow Tool

ERIC Educational Resources Information Center

Sin, Lauren; Daugert, Katie

2013-01-01

Several years ago, National Public Radio (NPR) librarians began developing a new content management system (CMS). It was intended to offer desktop access for all NPR-produced content, including transcripts, audio, and metadata. Fast-forward to 2011, and their shiny, new database, Artemis, was ready for debut. Their next challenge: to teach a staff…

A Virtual Science Data Environment for Carbon Dioxide Observations

NASA Astrophysics Data System (ADS)

Verma, R.; Goodale, C. E.; Hart, A. F.; Law, E.; Crichton, D. J.; Mattmann, C. A.; Gunson, M. R.; Braverman, A. J.; Nguyen, H. M.; Eldering, A.; Castano, R.; Osterman, G. B.

2011-12-01

Climate science data are often distributed cross-institutionally and made available using heterogeneous interfaces. With respect to observational carbon-dioxide (CO2) records, these data span across national as well as international institutions and are typically distributed using a variety of data standards. Such an arrangement can yield challenges from a research perspective, as users often need to independently aggregate datasets as well as address the issue of data quality. To tackle this dispersion and heterogeneity of data, we have developed the CO2 Virtual Science Data Environment - a comprehensive approach to virtually integrating CO2 data and metadata from multiple missions and providing a suite of computational services that facilitate analysis, comparison, and transformation of that data. The Virtual Science Environment provides climate scientists with a unified web-based destination for discovering relevant observational data in context, and supports a growing range of online tools and services for analyzing and transforming the available data to suit individual research needs. It includes web-based tools to geographically and interactively search for CO2 observations collected from multiple airborne, space, as well as terrestrial platforms. Moreover, the data analysis services it provides over the Internet, including offering techniques such as bias estimation and spatial re-gridding, move computation closer to the data and reduce the complexity of performing these operations repeatedly and at scale. The key to enabling these services, as well as consolidating the disparate data into a unified resource, has been to focus on leveraging metadata descriptors as the foundation of our data environment. This metadata-centric architecture, which leverages the Dublin Core standard, forgoes the need to replicate remote datasets locally. Instead, the system relies upon an extensive, metadata-rich virtual data catalog allowing on-demand browsing and retrieval of CO2 records from multiple missions. In other words, key metadata information about remote CO2 records is stored locally while the data itself is preserved at its respective archive of origin. This strategy has been made possible by our method of encapsulating the heterogeneous sources of data using a common set of web-based services, including services provided by Jet Propulsion Laboratory's Climate Data Exchange (CDX). Furthermore, this strategy has enabled us to scale across missions, and to provide access to a broad array of CO2 observational data. Coupled with on-demand computational services and an intuitive web-portal interface, the CO2 Virtual Science Data Environment effectively transforms heterogeneous CO2 records from multiple sources into a unified resource for scientific discovery.

Scientific Workflows + Provenance = Better (Meta-)Data Management

NASA Astrophysics Data System (ADS)

Ludaescher, B.; Cuevas-Vicenttín, V.; Missier, P.; Dey, S.; Kianmajd, P.; Wei, Y.; Koop, D.; Chirigati, F.; Altintas, I.; Belhajjame, K.; Bowers, S.

2013-12-01

The origin and processing history of an artifact is known as its provenance. Data provenance is an important form of metadata that explains how a particular data product came about, e.g., how and when it was derived in a computational process, which parameter settings and input data were used, etc. Provenance information provides transparency and helps to explain and interpret data products. Other common uses and applications of provenance include quality control, data curation, result debugging, and more generally, 'reproducible science'. Scientific workflow systems (e.g. Kepler, Taverna, VisTrails, and others) provide controlled environments for developing computational pipelines with built-in provenance support. Workflow results can then be explained in terms of workflow steps, parameter settings, input data, etc. using provenance that is automatically captured by the system. Scientific workflows themselves provide a user-friendly abstraction of the computational process and are thus a form of ('prospective') provenance in their own right. The full potential of provenance information is realized when combining workflow-level information (prospective provenance) with trace-level information (retrospective provenance). To this end, the DataONE Provenance Working Group (ProvWG) has developed an extension of the W3C PROV standard, called D-PROV. Whereas PROV provides a 'least common denominator' for exchanging and integrating provenance information, D-PROV adds new 'observables' that described workflow-level information (e.g., the functional steps in a pipeline), as well as workflow-specific trace-level information ( timestamps for each workflow step executed, the inputs and outputs used, etc.) Using examples, we will demonstrate how the combination of prospective and retrospective provenance provides added value in managing scientific data. The DataONE ProvWG is also developing tools based on D-PROV that allow scientists to get more mileage from provenance metadata. DataONE is a federation of member nodes that store data and metadata for discovery and access. By enriching metadata with provenance information, search and reuse of data is enhanced, and the 'social life' of data (being the product of many workflow runs, different people, etc.) is revealed. We are currently prototyping a provenance repository (PBase) to demonstrate what can be achieved with advanced provenance queries. The ProvExplorer and ProPub tools support advanced ad-hoc querying and visualization of provenance as well as customized provenance publications (e.g., to address privacy issues, or to focus provenance to relevant details). In a parallel line of work, we are exploring ways to add provenance support to widely-used scripting platforms (e.g. R and Python) and then expose that information via D-PROV.

Deploying the ODISEES Ontology-guided Search in the NASA Earth Exchange (NEX)

NASA Astrophysics Data System (ADS)

Huffer, E.; Gleason, J. L.; Cotnoir, M.; Spaulding, R.; Deardorff, G.

2016-12-01

Robust, semantically rich metadata can support data discovery and access, and facilitate machine-to-machine transactions with services such as data subsetting, regridding, and reformatting. Despite this, for users not already familiar with the data in a given archive, most metadata is insufficient to help them find appropriate data for their projects. With this in mind, the Ontology-driven Interactive Search Environment (ODISEES) Data Discovery Portal was developed to enable users to find and download data variables that satisfy precise, parameter-level criteria, even when they know little or nothing about the naming conventions employed by data providers, or where suitable data might be archived. ODISEES relies on an Earth science ontology and metadata repository that provide an ontological framework for describing NASA data holdings with enough detail and fidelity to enable researchers to find, compare and evaluate individual data variables. Users can search for data by indicating the specific parameters desired, and comparing the results in a table that lets them quickly determine which data is most suitable. ODISEES and OLYMPUS, a tool for generating the semantically enhanced metadata used by ODISEES, are being developed in collaboration with the NASA Earth Exchange (NEX) project at the NASA Ames Research Center to prototype a robust data discovery and access service that could be made available to NEX users. NEX is a collaborative platform that provides researchers with access to TB to PB-scale datasets and analysis tools to operate on those data. By integrating ODISEES into the NEX Web Portal we hope to enable NEX users to locate datasets relevant to their research and download them directly into the NAS environment, where they can run applications using those datasets on the NAS supercomputers. This poster will describe the prototype integration of ODISEES into the NEX portal development environment, the mechanism implemented to use NASA APIs to retrieve data, and the approach to transfer data into the NAS supercomputing environment. Finally, we will describe the end-to-end demonstration of the capabilities implemented. This work was funded by the Advanced Information Systems Technology Program of NASA's Research Opportunities in Space and Earth Science.

Usability and Interoperability Improvements for an EASE-Grid 2.0 Passive Microwave Data Product Using CF Conventions

NASA Astrophysics Data System (ADS)

Hardman, M.; Brodzik, M. J.; Long, D. G.

2017-12-01

Beginning in 1978, the satellite passive microwave data record has been a mainstay of remote sensing of the cryosphere, providing twice-daily, near-global spatial coverage for monitoring changes in hydrologic and cryospheric parameters that include precipitation, soil moisture, surface water, vegetation, snow water equivalent, sea ice concentration and sea ice motion. Historical versions of the gridded passive microwave data sets were produced as flat binary files described in human-readable documentation. This format is error-prone and makes it difficult to reliably include all processing and provenance. Funded by NASA MEaSUREs, we have completely reprocessed the gridded data record that includes SMMR, SSM/I-SSMIS and AMSR-E. The new Calibrated Enhanced-Resolution Brightness Temperature (CETB) Earth System Data Record (ESDR) files are self-describing. Our approach to the new data set was to create netCDF4 files that use standard metadata conventions and best practices to incorporate file-level, machine- and human-readable contents, geolocation, processing and provenance metadata. We followed the flexible and adaptable Climate and Forecast (CF-1.6) Conventions with respect to their coordinate conventions and map projection parameters. Additionally, we made use of Attribute Conventions for Dataset Discovery (ACDD-1.3) that provided file-level conventions with spatio-temporal bounds that enable indexing software to search for coverage. Our CETB files also include temporal coverage and spatial resolution in the file-level metadata for human-readability. We made use of the JPL CF/ACDD Compliance Checker to guide this work. We tested our file format with real software, for example, netCDF Command-line Operators (NCO) power tools for unlimited control on spatio-temporal subsetting and concatenation of files. The GDAL tools understand the CF metadata and produce fully-compliant geotiff files from our data. ArcMap can then reproject the geotiff files on-the-fly and work with other geolocated data such as coastlines, with no special work required. We expect this combination of standards and well-tested interoperability to significantly improve the usability of this important ESDR for the Earth Science community.

Publication of sensor data in the long-term environmental sub-observatory TERENO Northeast

NASA Astrophysics Data System (ADS)

Stender, Vivien; Ulbricht, Damian; Klump, Jens

2017-04-01

Terrestrial Environmental Observatories (TERENO) is an interdisciplinary and long-term research project spanning an Earth observation network across Germany. It includes four test sites within Germany from the North German lowlands to the Bavarian Alps and is operated by six research centers of the Helmholtz Association. TERENO Northeast is one of the sub-observatories of TERENO and is operated by the German Research Centre for Geosciences GFZ in Potsdam. This observatory investigates geoecological processes in the northeastern lowland of Germany by collecting large amounts of environmentally relevant data. The success of long-term projects like TERENO depends on well-organized data management, data exchange between the partners involved and on the availability of the captured data. Data discovery and dissemination are facilitated not only through data portals of the regional TERENO observatories but also through a common spatial data infrastructure TEODOOR (TEreno Online Data repOsitORry). TEODOOR bundles the data provided by the different web services of the single observatories and provides tools for data discovery, visualization and data access. The TERENO Northeast data infrastructure integrates data from more than 200 instruments and makes data available through standard web services. TEODOOR accesses the OGC Sensor Web Enablement (SWE) interfaces offered by the regional observatories. In addition to the SWE interface, TERENO Northeast also publishes time series of environmental sensor data through the DOI registration service at GFZ Potsdam. This service uses the DataCite infrastructure to make research data citable and is able to keep and disseminate metadata popular to the geosciences [1]. The metadata required by DataCite are created in an automated process by extracting information from the SWE SensorML metadata. The GFZ data management tool kit panMetaDocs is used to manage and archive file based datasets and to register Digital Object Identifiers (DOI) for published data. In this presentation we will report on current advances in publication of time series data from environmental sensor networks. [1]http://doidb.wdc-terra.org/oaip/oai?verb=ListRecords&metadataPrefix=iso19139&set=DOIDB.TERENO

ISO 19115 Experiences in NASA's Earth Observing System (EOS) ClearingHOuse (ECHO)

NASA Astrophysics Data System (ADS)

Cechini, M. F.; Mitchell, A.

2011-12-01

Metadata is an important entity in the process of cataloging, discovering, and describing earth science data. As science research and the gathered data increases in complexity, so does the complexity and importance of descriptive metadata. To meet these growing needs, the metadata models required utilize richer and more mature metadata attributes. Categorizing, standardizing, and promulgating these metadata models to a politically, geographically, and scientifically diverse community is a difficult process. An integral component of metadata management within NASA's Earth Observing System Data and Information System (EOSDIS) is the Earth Observing System (EOS) ClearingHOuse (ECHO). ECHO is the core metadata repository for the EOSDIS data centers providing a centralized mechanism for metadata and data discovery and retrieval. ECHO has undertaken an internal restructuring to meet the changing needs of scientists, the consistent advancement in technology, and the advent of new standards such as ISO 19115. These improvements were based on the following tenets for data discovery and retrieval: + There exists a set of 'core' metadata fields recommended for data discovery. + There exists a set of users who will require the entire metadata record for advanced analysis. + There exists a set of users who will require a 'core' set metadata fields for discovery only. + There will never be a cessation of new formats or a total retirement of all old formats. + Users should be presented metadata in a consistent format of their choosing. In order to address the previously listed items, ECHO's new metadata processing paradigm utilizes the following approach: + Identify a cross-format set of 'core' metadata fields necessary for discovery. + Implement format-specific indexers to extract the 'core' metadata fields into an optimized query capability. + Archive the original metadata in its entirety for presentation to users requiring the full record. + Provide on-demand translation of 'core' metadata to any supported result format. Lessons learned by the ECHO team while implementing its new metadata approach to support usage of the ISO 19115 standard will be presented. These lessons learned highlight some discovered strengths and weaknesses in the ISO 19115 standard as it is introduced to an existing metadata processing system.

Creating context for the experiment record. User-defined metadata: investigations into metadata usage in the LabTrove ELN.

PubMed

Willoughby, Cerys; Bird, Colin L; Coles, Simon J; Frey, Jeremy G

2014-12-22

The drive toward more transparency in research, the growing willingness to make data openly available, and the reuse of data to maximize the return on research investment all increase the importance of being able to find information and make links to the underlying data. The use of metadata in Electronic Laboratory Notebooks (ELNs) to curate experiment data is an essential ingredient for facilitating discovery. The University of Southampton has developed a Web browser-based ELN that enables users to add their own metadata to notebook entries. A survey of these notebooks was completed to assess user behavior and patterns of metadata usage within ELNs, while user perceptions and expectations were gathered through interviews and user-testing activities within the community. The findings indicate that while some groups are comfortable with metadata and are able to design a metadata structure that works effectively, many users are making little attempts to use it, thereby endangering their ability to recover data in the future. A survey of patterns of metadata use in these notebooks, together with feedback from the user community, indicated that while a few groups are comfortable with metadata and are able to design a metadata structure that works effectively, many users adopt a "minimum required" approach to metadata. To investigate whether the patterns of metadata use in LabTrove were unusual, a series of surveys were undertaken to investigate metadata usage in a variety of platforms supporting user-defined metadata. These surveys also provided the opportunity to investigate whether interface designs in these other environments might inform strategies for encouraging metadata creation and more effective use of metadata in LabTrove.

Metadata squared: enhancing its usability for volunteered geographic information and the GeoWeb

USGS Publications Warehouse

Poore, Barbara S.; Wolf, Eric B.; Sui, Daniel Z.; Elwood, Sarah; Goodchild, Michael F.

2013-01-01

The Internet has brought many changes to the way geographic information is created and shared. One aspect that has not changed is metadata. Static spatial data quality descriptions were standardized in the mid-1990s and cannot accommodate the current climate of data creation where nonexperts are using mobile phones and other location-based devices on a continuous basis to contribute data to Internet mapping platforms. The usability of standard geospatial metadata is being questioned by academics and neogeographers alike. This chapter analyzes current discussions of metadata to demonstrate how the media shift that is occurring has affected requirements for metadata. Two case studies of metadata use are presented—online sharing of environmental information through a regional spatial data infrastructure in the early 2000s, and new types of metadata that are being used today in OpenStreetMap, a map of the world created entirely by volunteers. Changes in metadata requirements are examined for usability, the ease with which metadata supports coproduction of data by communities of users, how metadata enhances findability, and how the relationship between metadata and data has changed. We argue that traditional metadata associated with spatial data infrastructures is inadequate and suggest several research avenues to make this type of metadata more interactive and effective in the GeoWeb.

The role of metadata in managing large environmental science datasets. Proceedings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Melton, R.B.; DeVaney, D.M.; French, J. C.

1995-06-01

The purpose of this workshop was to bring together computer science researchers and environmental sciences data management practitioners to consider the role of metadata in managing large environmental sciences datasets. The objectives included: establishing a common definition of metadata; identifying categories of metadata; defining problems in managing metadata; and defining problems related to linking metadata with primary data.

Gene Ontology Consortium: going forward.

PubMed

2015-01-01

The Gene Ontology (GO; http://www.geneontology.org) is a community-based bioinformatics resource that supplies information about gene product function using ontologies to represent biological knowledge. Here we describe improvements and expansions to several branches of the ontology, as well as updates that have allowed us to more efficiently disseminate the GO and capture feedback from the research community. The Gene Ontology Consortium (GOC) has expanded areas of the ontology such as cilia-related terms, cell-cycle terms and multicellular organism processes. We have also implemented new tools for generating ontology terms based on a set of logical rules making use of templates, and we have made efforts to increase our use of logical definitions. The GOC has a new and improved web site summarizing new developments and documentation, serving as a portal to GO data. Users can perform GO enrichment analysis, and search the GO for terms, annotations to gene products, and associated metadata across multiple species using the all-new AmiGO 2 browser. We encourage and welcome the input of the research community in all biological areas in our continued effort to improve the Gene Ontology. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Towards Text Copyright Detection Using Metadata in Web Applications

ERIC Educational Resources Information Center

Poulos, Marios; Korfiatis, Nikolaos; Bokos, George

2011-01-01

Purpose: This paper aims to present the semantic content identifier (SCI), a permanent identifier, computed through a linear-time onion-peeling algorithm that enables the extraction of semantic features from a text, and the integration of this information within the permanent identifier. Design/methodology/approach: The authors employ SCI to…

Accessing Digital Libraries: A Study of ARL Members' Digital Projects

ERIC Educational Resources Information Center

Kahl, Chad M.; Williams, Sarah C.

2006-01-01

To ensure efficient access to and integrated searching capabilities for their institution's new digital library projects, the authors studied Web sites of the Association of Research Libraries' (ARL) 111 academic, English-language libraries. Data were gathered on 1117 digital projects, noting library Web site and project access, metadata, and…

Use of a Knowledge Management System in Waste Management Projects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gruendler, D.; Boetsch, W.U.; Holzhauer, U.

2006-07-01

In Germany the knowledge management system 'WasteInfo' about waste management and disposal issues has been developed and implemented. Beneficiaries of 'WasteInfo' are official decision makers having access to a large information pool. The information pool is fed by experts, so called authors This means compiling of information, evaluation and assigning of appropriate properties (metadata) to this information. The knowledge management system 'WasteInfo' has been introduced at the WM04, the operation of 'WasteInfo' at the WM05. The recent contribution describes the additional advantage of the KMS being used as a tool for the dealing with waste management projects. This specific aspectmore » will be demonstrated using a project concerning a comparative analysis of the implementation of repositories in six countries using nuclear power as examples: The information of 'WasteInfo' is assigned to categories and structured according to its origin and type of publication. To use 'WasteInfo' as a tool for the processing the projects, a suitable set of categories has to be developed for each project. Apart from technical and scientific aspects, the selected project deals with repository strategies and policies in various countries, with the roles of applicants and authorities in licensing procedures, with safety philosophy and with socio-economic concerns. This new point of view has to be modelled in the categories. Similar to this, new sources of information such as local and regional dailies or particular web-sites have to be taken into consideration. In this way 'WasteInfo' represents an open document which reflects the current status of the respective repository policy in several countries. Information with particular meaning for the German repository planning is marked and by this may influence the German strategy. (authors)« less

Development of RESTful services and map-based user interface tools for access and delivery of data and metadata from the Marine-Geo Digital Library

NASA Astrophysics Data System (ADS)

Morton, J. J.; Ferrini, V. L.

2015-12-01

The Marine Geoscience Data System (MGDS, www.marine-geo.org) operates an interactive digital data repository and metadata catalog that provides access to a variety of marine geology and geophysical data from throughout the global oceans. Its Marine-Geo Digital Library includes common marine geophysical data types and supporting data and metadata, as well as complementary long-tail data. The Digital Library also includes community data collections and custom data portals for the GeoPRISMS, MARGINS and Ridge2000 programs, for active source reflection data (Academic Seismic Portal), and for marine data acquired by the US Antarctic Program (Antarctic and Southern Ocean Data Portal). Ensuring that these data are discoverable not only through our own interfaces but also through standards-compliant web services is critical for enabling investigators to find data of interest.Over the past two years, MGDS has developed several new RESTful web services that enable programmatic access to metadata and data holdings. These web services are compliant with the EarthCube GeoWS Building Blocks specifications and are currently used to drive our own user interfaces. New web applications have also been deployed to provide a more intuitive user experience for searching, accessing and browsing metadata and data. Our new map-based search interface combines components of the Google Maps API with our web services for dynamic searching and exploration of geospatially constrained data sets. Direct introspection of nearly all data formats for hundreds of thousands of data files curated in the Marine-Geo Digital Library has allowed for precise geographic bounds, which allow geographic searches to an extent not previously possible. All MGDS map interfaces utilize the web services of the Global Multi-Resolution Topography (GMRT) synthesis for displaying global basemap imagery and for dynamically provide depth values at the cursor location.

Building Format-Agnostic Metadata Repositories

NASA Astrophysics Data System (ADS)

Cechini, M.; Pilone, D.

2010-12-01

This presentation will discuss the problems that surround persisting and discovering metadata in multiple formats; a set of tenets that must be addressed in a solution; and NASA’s Earth Observing System (EOS) ClearingHOuse’s (ECHO) proposed approach. In order to facilitate cross-discipline data analysis, Earth Scientists will potentially interact with more than one data source. The most common data discovery paradigm relies on services and/or applications facilitating the discovery and presentation of metadata. What may not be common are the formats in which the metadata are formatted. As the number of sources and datasets utilized for research increases, it becomes more likely that a researcher will encounter conflicting metadata formats. Metadata repositories, such as the EOS ClearingHOuse (ECHO), along with data centers, must identify ways to address this issue. In order to define the solution to this problem, the following tenets are identified: - There exists a set of ‘core’ metadata fields recommended for data discovery. - There exists a set of users who will require the entire metadata record for advanced analysis. - There exists a set of users who will require a ‘core’ set of metadata fields for discovery only. - There will never be a cessation of new formats or a total retirement of all old formats. - Users should be presented metadata in a consistent format. ECHO has undertaken an effort to transform its metadata ingest and discovery services in order to support the growing set of metadata formats. In order to address the previously listed items, ECHO’s new metadata processing paradigm utilizes the following approach: - Identify a cross-format set of ‘core’ metadata fields necessary for discovery. - Implement format-specific indexers to extract the ‘core’ metadata fields into an optimized query capability. - Archive the original metadata in its entirety for presentation to users requiring the full record. - Provide on-demand translation of ‘core’ metadata to any supported result format. With this identified approach, the Earth Scientist is provided with a consistent data representation as they interact with a variety of datasets that utilize multiple metadata formats. They are then able to focus their efforts on the more critical research activities which they are undertaking.

Making Metadata Better with CMR and MMT

NASA Technical Reports Server (NTRS)

Gilman, Jason Arthur; Shum, Dana

2016-01-01

Ensuring complete, consistent and high quality metadata is a challenge for metadata providers and curators. The CMR and MMT systems provide providers and curators options to build in metadata quality from the start and also assess and improve the quality of already existing metadata.

Evolution in Metadata Quality: Common Metadata Repository's Role in NASA Curation Efforts

NASA Technical Reports Server (NTRS)

Gilman, Jason; Shum, Dana; Baynes, Katie

2016-01-01

Metadata Quality is one of the chief drivers of discovery and use of NASA EOSDIS (Earth Observing System Data and Information System) data. Issues with metadata such as lack of completeness, inconsistency, and use of legacy terms directly hinder data use. As the central metadata repository for NASA Earth Science data, the Common Metadata Repository (CMR) has a responsibility to its users to ensure the quality of CMR search results. This poster covers how we use humanizers, a technique for dealing with the symptoms of metadata issues, as well as our plans for future metadata validation enhancements. The CMR currently indexes 35K collections and 300M granules.

Experiences of building a medical data acquisition system based on two-level modeling.

PubMed

Li, Bei; Li, Jianbin; Lan, Xiaoyun; An, Ying; Gao, Wuqiang; Jiang, Yuqiao

2018-04-01

Compared to traditional software development strategies, the two-level modeling approach is more flexible and applicable to build an information system in the medical domain. However, the standards of two-level modeling such as openEHR appear complex to medical professionals. This study aims to investigate, implement, and improve the two-level modeling approach, and discusses the experience of building a unified data acquisition system for four affiliated university hospitals based on this approach. After the investigation, we simplified the approach of archetype modeling and developed a medical data acquisition system where medical experts can define the metadata for their own specialties by using a visual easy-to-use tool. The medical data acquisition system for multiple centers, clinical specialties, and diseases has been developed, and integrates the functions of metadata modeling, form design, and data acquisition. To date, 93,353 data items and 6,017 categories for 285 specific diseases have been created by medical experts, and over 25,000 patients' information has been collected. OpenEHR is an advanced two-level modeling method for medical data, but its idea to separate domain knowledge and technical concern is not easy to realize. Moreover, it is difficult to reach an agreement on archetype definition. Therefore, we adopted simpler metadata modeling, and employed What-You-See-Is-What-You-Get (WYSIWYG) tools to further improve the usability of the system. Compared with the archetype definition, our approach lowers the difficulty. Nevertheless, to build such a system, every participant should have some knowledge in both medicine and information technology domains, as these interdisciplinary talents are necessary. Copyright © 2018 Elsevier B.V. All rights reserved.

The National Extreme Events Data and Research Center (NEED)

NASA Astrophysics Data System (ADS)

Gulledge, J.; Kaiser, D. P.; Wilbanks, T. J.; Boden, T.; Devarakonda, R.

2014-12-01

The Climate Change Science Institute at Oak Ridge National Laboratory (ORNL) is establishing the National Extreme Events Data and Research Center (NEED), with the goal of transforming how the United States studies and prepares for extreme weather events in the context of a changing climate. NEED will encourage the myriad, distributed extreme events research communities to move toward the adoption of common practices and will develop a new database compiling global historical data on weather- and climate-related extreme events (e.g., heat waves, droughts, hurricanes, etc.) and related information about impacts, costs, recovery, and available research. Currently, extreme event information is not easy to access and is largely incompatible and inconsistent across web sites. NEED's database development will take into account differences in time frames, spatial scales, treatments of uncertainty, and other parameters and variables, and leverage informatics tools developed at ORNL (i.e., the Metadata Editor [1] and Mercury [2]) to generate standardized, robust documentation for each database along with a web-searchable catalog. In addition, NEED will facilitate convergence on commonly accepted definitions and standards for extreme events data and will enable integrated analyses of coupled threats, such as hurricanes/sea-level rise/flooding and droughts/wildfires. Our goal and vision is that NEED will become the premiere integrated resource for the general study of extreme events. References: [1] Devarakonda, Ranjeet, et al. "OME: Tool for generating and managing metadata to handle BigData." Big Data (Big Data), 2014 IEEE International Conference on. IEEE, 2014. [2] Devarakonda, Ranjeet, et al. "Mercury: reusable metadata management, data discovery and access system." Earth Science Informatics 3.1-2 (2010): 87-94.

The VIMS Data Explorer: A tool for locating and visualizing hyperspectral data

NASA Astrophysics Data System (ADS)

Pasek, V. D.; Lytle, D. M.; Brown, R. H.

2016-12-01

Since successfully entering Saturn's orbit during Summer 2004 there have been over 300,000 hyperspectral data cubes returned from the visible and infrared mapping spectrometer (VIMS) instrument onboard the Cassini spacecraft. The VIMS Science Investigation is a multidisciplinary effort that uses these hyperspectral data to study a variety of scientific problems, including surface characterizations of the icy satellites and atmospheric analyses of Titan and Saturn. Such investigations may need to identify thousands of exemplary data cubes for analysis and can span many years in scope. Here we describe the VIMS data explorer (VDE) application, currently employed by the VIMS Investigation to search for and visualize data. The VDE application facilitates real-time inspection of the entire VIMS hyperspectral dataset, the construction of in situ maps, and markers to save and recall work. The application relies on two databases to provide comprehensive search capabilities. The first database contains metadata for every cube. These metadata searches are used to identify records based on parameters such as target, observation name, or date taken; they fall short in utility for some investigations. The cube metadata contains no target geometry information. Through the introduction of a post-calibration pixel database, the VDE tool enables users to greatly expand their searching capabilities. Users can select favorable cubes for further processing into 2-D and 3-D interactive maps, aiding in the data interpretation and selection process. The VDE application enables efficient search, visualization, and access to VIMS hyperspectral data. It is simple to use, requiring nothing more than a browser for access. Hyperspectral bands can be individually selected or combined to create real-time color images, a technique commonly employed by hyperspectral researchers to highlight compositional differences.

Visualization Beyond the Map: The Challenges of Managing Data for Re-Use

NASA Astrophysics Data System (ADS)

Allison, M. D.; Groman, R. C.; Chandler, C. L.; Galvarino, C. R.; Wiebe, P. H.; Glover, D. M.

2012-12-01

The Biological and Chemical Oceanography Data Management Office (BCO-DMO) makes data publicly accessible via both a text-based and a geospatial interface, the latter using the Open Geospatial Consortium (OGC) compliant open-source MapServer software originally from the University of Minnesota. Making data available for reuse by the widest variety of users is one of the overriding goals of BCO-DMO and one of our greatest challenges. The biogeochemical, ecological and physical data we manage are extremely heterogeneous. Although it is not possible to be all things to all people, we are actively working on ways to make the data re-usable by the most people. Looking at data in a different way is one of the underpinnings of data re-use and the easier we can make data accessible, the more the community of users will benefit. We can help the user determine usefulness by providing some specific tools. Sufficiently well-informed metadata can often be enough to determine fitness for purpose, but many times our geospatial interface to the data and metadata is more compelling. Displaying the data visually in as many ways as possible enables the scientist, teacher or manager to decide if the data are useful and then being able to download the data right away with no login required is very attractive. We will present ways of visualizing different kinds of data and discuss using metadata to drive the visualization tools. We will also discuss our attempts to work with data providers to organize their data in ways to make them reusable to the largest audience and to solicit input from data users about the effectiveness of our solutions.

Practical Steps toward Computational Unification: Helpful Perspectives for New Systems, Adding Functionality to Existing Ones

NASA Astrophysics Data System (ADS)

Troy, R. M.

2005-12-01

With ever increasing amounts of Earth-Science funding being diverted to the war in Iraq, the Earth-Science community must now more than ever wring every bit of utility out of every dollar. We're not likely to get funded any projects perceived by others as "pie in the sky", so we have to look at already funded programs within our community and directing new programs in a unifying direction. We have not yet begun the transition to a computationally unifying, general-purpose Earth Science computing paradigm, though it was proposed at the Fall 2002 AGU meeting in San Francisco, and perhaps earlier. Encouragingly, we do see a recognition that more commonality is needed as various projects have as funded goals the addition of the processing and dissemination of new datatypes, or data-sets, if you prefer, to their existing repertoires. Unfortunately, the timelines projected for adding a datatype to an existing system are typically estimated at around two years each. Further, many organizations have the perception that they can only use their dollars to support exclusively their own needs as they don't have the money to support the goals of others, thus overlooking opportunities to satisfy their own needs while at the same time aiding the creation of a global GeoScience cyber-infrastructure. While Computational Unification appears to be an unfunded, impossible dream, at least for now, individual projects can take steps that are compatible with a unified community and can help build one over time. This session explores these opportunities. The author will discuss the issues surrounding this topic, outlining alternative perspectives on the points of difficulty, and proposing straight-forward solutions which every Earth Science data processing system should consider. Sub-topics include distributed meta-data, distributed processing, distributed data objects, interdisciplinary concerns, and scientific defensibility with an overall emphasis on how previously written processes and functions may be integrated into a system efficiently, with minimal effort, and with an eye toward an eventual Computational Unification of the Earth Sciences. A fundamental to such systems is meta-data which describe not only the content of data but also how intricate relationships are represented and used to good advantage. Retrieval techniques will be discussed including trade-offs in using externally managed meta-data versus embedded meta-data, how the two may be integrated, and how "simplifying assumptions" may or may not actually be helpful. The perspectives presented in this talk or poster session are based upon the experience of the Sequoia 2000 and BigSur research projects at the University of California, Berkeley, which sought to unify NASA's Mission To Planet Earth's EOS-DIS, and on-going experience developed by Science Tools corporation, of which the author is a principal. NOTE: These ideas are most easily shared in the form of a talk, and we suspect that this session will generate a lot of interest. We would therefore prefer to have this session accepted as a talk as opposed to a poster session.

Evolving from bioinformatics in-the-small to bioinformatics in-the-large.

PubMed

Parker, D Stott; Gorlick, Michael M; Lee, Christopher J

2003-01-01

We argue the significance of a fundamental shift in bioinformatics, from in-the-small to in-the-large. Adopting a large-scale perspective is a way to manage the problems endemic to the world of the small-constellations of incompatible tools for which the effort required to assemble an integrated system exceeds the perceived benefit of the integration. Where bioinformatics in-the-small is about data and tools, bioinformatics in-the-large is about metadata and dependencies. Dependencies represent the complexities of large-scale integration, including the requirements and assumptions governing the composition of tools. The popular make utility is a very effective system for defining and maintaining simple dependencies, and it offers a number of insights about the essence of bioinformatics in-the-large. Keeping an in-the-large perspective has been very useful to us in large bioinformatics projects. We give two fairly different examples, and extract lessons from them showing how it has helped. These examples both suggest the benefit of explicitly defining and managing knowledge flows and knowledge maps (which represent metadata regarding types, flows, and dependencies), and also suggest approaches for developing bioinformatics database systems. Generally, we argue that large-scale engineering principles can be successfully adapted from disciplines such as software engineering and data management, and that having an in-the-large perspective will be a key advantage in the next phase of bioinformatics development.

Retinal Connectomics: Towards Complete, Accurate Networks

PubMed Central

Marc, Robert E.; Jones, Bryan W.; Watt, Carl B.; Anderson, James R.; Sigulinsky, Crystal; Lauritzen, Scott

2013-01-01

Connectomics is a strategy for mapping complex neural networks based on high-speed automated electron optical imaging, computational assembly of neural data volumes, web-based navigational tools to explore 1012–1015 byte (terabyte to petabyte) image volumes, and annotation and markup tools to convert images into rich networks with cellular metadata. These collections of network data and associated metadata, analyzed using tools from graph theory and classification theory, can be merged with classical systems theory, giving a more completely parameterized view of how biologic information processing systems are implemented in retina and brain. Networks have two separable features: topology and connection attributes. The first findings from connectomics strongly validate the idea that the topologies complete retinal networks are far more complex than the simple schematics that emerged from classical anatomy. In particular, connectomics has permitted an aggressive refactoring of the retinal inner plexiform layer, demonstrating that network function cannot be simply inferred from stratification; exposing the complex geometric rules for inserting different cells into a shared network; revealing unexpected bidirectional signaling pathways between mammalian rod and cone systems; documenting selective feedforward systems, novel candidate signaling architectures, new coupling motifs, and the highly complex architecture of the mammalian AII amacrine cell. This is but the beginning, as the underlying principles of connectomics are readily transferrable to non-neural cell complexes and provide new contexts for assessing intercellular communication. PMID:24016532

Metadata: Standards for Retrieving WWW Documents (and Other Digitized and Non-Digitized Resources)

NASA Astrophysics Data System (ADS)

Rusch-Feja, Diann

The use of metadata for indexing digitized and non-digitized resources for resource discovery in a networked environment is being increasingly implemented all over the world. Greater precision is achieved using metadata than relying on universal search engines and furthermore, meta-data can be used as filtering mechanisms for search results. An overview of various metadata sets is given, followed by a more focussed presentation of Dublin Core Metadata including examples of sub-elements and qualifiers. Especially the use of the Dublin Core Relation element provides connections between the metadata of various related electronic resources, as well as the metadata for physical, non-digitized resources. This facilitates more comprehensive search results without losing precision and brings together different genres of information which would otherwise be only searchable in separate databases. Furthermore, the advantages of Dublin Core Metadata in comparison with library cataloging and the use of universal search engines are discussed briefly, followed by a listing of types of implementation of Dublin Core Metadata.

Metadata mapping and reuse in caBIG.

PubMed

Kunz, Isaac; Lin, Ming-Chin; Frey, Lewis

2009-02-05

This paper proposes that interoperability across biomedical databases can be improved by utilizing a repository of Common Data Elements (CDEs), UML model class-attributes and simple lexical algorithms to facilitate the building domain models. This is examined in the context of an existing system, the National Cancer Institute (NCI)'s cancer Biomedical Informatics Grid (caBIG). The goal is to demonstrate the deployment of open source tools that can be used to effectively map models and enable the reuse of existing information objects and CDEs in the development of new models for translational research applications. This effort is intended to help developers reuse appropriate CDEs to enable interoperability of their systems when developing within the caBIG framework or other frameworks that use metadata repositories. The Dice (di-grams) and Dynamic algorithms are compared and both algorithms have similar performance matching UML model class-attributes to CDE class object-property pairs. With algorithms used, the baselines for automatically finding the matches are reasonable for the data models examined. It suggests that automatic mapping of UML models and CDEs is feasible within the caBIG framework and potentially any framework that uses a metadata repository. This work opens up the possibility of using mapping algorithms to reduce cost and time required to map local data models to a reference data model such as those used within caBIG. This effort contributes to facilitating the development of interoperable systems within caBIG as well as other metadata frameworks. Such efforts are critical to address the need to develop systems to handle enormous amounts of diverse data that can be leveraged from new biomedical methodologies.

New Web Services for Broader Access to National Deep Submergence Facility Data Resources Through the Interdisciplinary Earth Data Alliance

NASA Astrophysics Data System (ADS)

Ferrini, V. L.; Grange, B.; Morton, J. J.; Soule, S. A.; Carbotte, S. M.; Lehnert, K.

2016-12-01

The National Deep Submergence Facility (NDSF) operates the Human Occupied Vehicle (HOV) Alvin, the Remotely Operated Vehicle (ROV) Jason, and the Autonomous Underwater Vehicle (AUV) Sentry. These vehicles are deployed throughout the global oceans to acquire sensor data and physical samples for a variety of interdisciplinary science programs. As part of the EarthCube Integrative Activity Alliance Testbed Project (ATP), new web services were developed to improve access to existing online NDSF data and metadata resources. These services make use of tools and infrastructure developed by the Interdisciplinary Earth Data Alliance (IEDA) and enable programmatic access to metadata and data resources as well as the development of new service-driven user interfaces. The Alvin Frame Grabber and Jason Virtual Van enable the exploration of frame-grabbed images derived from video cameras on NDSF dives. Metadata available for each image includes time and vehicle position, data from environmental sensors, and scientist-generated annotations, and data are organized and accessible by cruise and/or dive. A new FrameGrabber web service and service-driven user interface were deployed to offer integrated access to these data resources through a single API and allows users to search across content curated in both systems. In addition, a new NDSF Dive Metadata web service and service-driven user interface was deployed to provide consolidated access to basic information about each NDSF dive (e.g. vehicle name, dive ID, location, etc), which is important for linking distributed data resources curated in different data systems.

Data Management Rubric for Video Data in Organismal Biology

PubMed Central

Brainerd, Elizabeth L.; Blob, Richard W.; Hedrick, Tyson L.; Creamer, Andrew T.; Müller, Ulrike K.

2017-01-01

Synopsis Standards-based data management facilitates data preservation, discoverability, and access for effective data reuse within research groups and across communities of researchers. Data sharing requires community consensus on standards for data management, such as storage and formats for digital data preservation, metadata (i.e., contextual data about the data) that should be recorded and stored, and data access. Video imaging is a valuable tool for measuring time-varying phenotypes in organismal biology, with particular application for research in functional morphology, comparative biomechanics, and animal behavior. The raw data are the videos, but videos alone are not sufficient for scientific analysis. Nearly endless videos of animals can be found on YouTube and elsewhere on the web, but these videos have little value for scientific analysis because essential metadata such as true frame rate, spatial calibration, genus and species, weight, age, etc. of organisms, are generally unknown. We have embarked on a project to build community consensus on video data management and metadata standards for organismal biology research. We collected input from colleagues at early stages, organized an open workshop, “Establishing Standards for Video Data Management,” at the Society for Integrative and Comparative Biology meeting in January 2017, and then collected two more rounds of input on revised versions of the standards. The result we present here is a rubric consisting of nine standards for video data management, with three levels within each standard: good, better, and best practices. The nine standards are: (1) data storage; (2) video file formats; (3) metadata linkage; (4) video data and metadata access; (5) contact information and acceptable use; (6) camera settings; (7) organism(s); (8) recording conditions; and (9) subject matter/topic. The first four standards address data preservation and interoperability for sharing, whereas standards 5–9 establish minimum metadata standards for organismal biology video, and suggest additional metadata that may be useful for some studies. This rubric was developed with substantial input from researchers and students, but still should be viewed as a living document that should be further refined and updated as technology and research practices change. The audience for these standards includes researchers, journals, and granting agencies, and also the developers and curators of databases that may contribute to video data sharing efforts. We offer this project as an example of building community consensus for data management, preservation, and sharing standards, which may be useful for future efforts by the organismal biology research community. PMID:28881939

Department of the Interior metadata implementation guide—Framework for developing the metadata component for data resource management

USGS Publications Warehouse

Obuch, Raymond C.; Carlino, Jennifer; Zhang, Lin; Blythe, Jonathan; Dietrich, Christopher; Hawkinson, Christine

2018-04-12

The Department of the Interior (DOI) is a Federal agency with over 90,000 employees across 10 bureaus and 8 agency offices. Its primary mission is to protect and manage the Nation’s natural resources and cultural heritage; provide scientific and other information about those resources; and honor its trust responsibilities or special commitments to American Indians, Alaska Natives, and affiliated island communities. Data and information are critical in day-to-day operational decision making and scientific research. DOI is committed to creating, documenting, managing, and sharing high-quality data and metadata in and across its various programs that support its mission. Documenting data through metadata is essential in realizing the value of data as an enterprise asset. The completeness, consistency, and timeliness of metadata affect users’ ability to search for and discover the most relevant data for the intended purpose; and facilitates the interoperability and usability of these data among DOI bureaus and offices. Fully documented metadata describe data usability, quality, accuracy, provenance, and meaning.Across DOI, there are different maturity levels and phases of information and metadata management implementations. The Department has organized a committee consisting of bureau-level points-of-contacts to collaborate on the development of more consistent, standardized, and more effective metadata management practices and guidance to support this shared mission and the information needs of the Department. DOI’s metadata implementation plans establish key roles and responsibilities associated with metadata management processes, procedures, and a series of actions defined in three major metadata implementation phases including: (1) Getting started—Planning Phase, (2) Implementing and Maintaining Operational Metadata Management Phase, and (3) the Next Steps towards Improving Metadata Management Phase. DOI’s phased approach for metadata management addresses some of the major data and metadata management challenges that exist across the diverse missions of the bureaus and offices. All employees who create, modify, or use data are involved with data and metadata management. Identifying, establishing, and formalizing the roles and responsibilities associated with metadata management are key to institutionalizing a framework of best practices, methodologies, processes, and common approaches throughout all levels of the organization; these are the foundation for effective data resource management. For executives and managers, metadata management strengthens their overarching views of data assets, holdings, and data interoperability; and clarifies how metadata management can help accelerate the compliance of multiple policy mandates. For employees, data stewards, and data professionals, formalized metadata management will help with the consistency of definitions, and approaches addressing data discoverability, data quality,  and data lineage. In addition to data professionals and others  associated with information technology; data stewards and program subject matter experts take on important metadata management roles and responsibilities as data flow through their respective business and science-related workflows.  The responsibilities of establishing, practicing, and  governing the actions associated with their specific metadata management roles are critical to successful metadata implementation.

SeaDataNet - Pan-European infrastructure for marine and ocean data management: Unified access to distributed data sets

NASA Astrophysics Data System (ADS)

Schaap, D. M. A.; Maudire, G.

2009-04-01

SeaDataNet is an Integrated research Infrastructure Initiative (I3) in EU FP6 (2006 - 2011) to provide the data management system adapted both to the fragmented observation system and the users need for an integrated access to data, meta-data, products and services. Therefore SeaDataNet insures the long term archiving of the large number of multidisciplinary data (i.e. temperature, salinity current, sea level, chemical, physical and biological properties) collected by many different sensors installed on board of research vessels, satellite and the various platforms of the marine observing system. The SeaDataNet project started in 2006, but builds upon earlier data management infrastructure projects, undertaken over a period of 20 years by an expanding network of oceanographic data centres from the countries around all European seas. Its predecessor project Sea-Search had a strict focus on metadata. SeaDataNet maintains significant interest in the further development of the metadata infrastructure, but its primary objective is the provision of easy data access and generic data products. SeaDataNet is a distributed infrastructure that provides transnational access to marine data, meta-data, products and services through 40 interconnected Trans National Data Access Platforms (TAP) from 35 countries around the Black Sea, Mediterranean, North East Atlantic, North Sea, Baltic and Arctic regions. These include: National Oceanographic Data Centres (NODC's) Satellite Data Centres. Furthermore the SeaDataNet consortium comprises a number of expert modelling centres, SME's experts in IT, and 3 international bodies (ICES, IOC and JRC). Planning: The SeaDataNet project is delivering and operating the infrastructure in 3 versions: Version 0: maintenance and further development of the metadata systems developed by the Sea-Search project plus the development of a new metadata system for indexing and accessing to individual data objects managed by the SeaDataNet data centres. This is known as the Common Data Index (CDI) V0 system Version 1: harmonisation and upgrading of the metadatabases through adoption of the ISO 19115 metadata standard and provision of transparent data access and download services from all partner data centres through upgrading the Common Data Index and deployment of a data object delivery service. Version 2: adding data product services and OGC compliant viewing services and further virtualisation of data access. SeaDataNet Version 0: The SeaDataNet portal has been set up at http://www.seadatanet.org and it provides a platform for all SeaDataNet services and standards as well as background information about the project and its partners. It includes discovery services via the following catalogues: CSR - Cruise Summary Reports of research vessels; EDIOS - Locations and details of monitoring stations and networks / programmes; EDMED - High level inventory of Marine Environmental Data sets collected and managed by research institutes and organisations; EDMERP - Marine Environmental Research Projects ; EDMO - Marine Organisations. These catalogues are interrelated, where possible, to facilitate cross searching and context searching. These catalogues connect to the Common Data Index (CDI). Common Data Index (CDI) The CDI gives detailed insight in available datasets at partners databases and paves the way to direct online data access or direct online requests for data access / data delivery. The CDI V0 metadatabase contains more than 340.000 individual data entries from 36 CDI partners from 29 countries across Europe, covering a broad scope and range of data, held by these organisations. For purposes of standardisation and international exchange the ISO19115 metadata standard has been adopted. The CDI format is defined as a dedicated subset of this standard. A CDI XML format supports the exchange between CDI-partners and the central CDI manager, and ensures interoperability with other systems and networks. CDI XML entries are generated by participating data centres, directly from their databases. CDI-partners can make use of dedicated SeaDataNet Tools to generate CDI XML files automatically. Approach for SeaDataNet V1 and V2: The approach for SeaDataNet V1 and V2, which is in line with the INSPIRE Directive, comprises the following services: Discovery services = Metadata directories Security services = Authentication, Authorization & Accounting (AAA) Delivery services = Data access & downloading of datasets Viewing services = Visualisation of metadata, data and data products Product services = Generic and standard products Monitoring services = Statistics on usage and performance of the system Maintenance services = Updating of metadata by SeaDataNet partners The services will be operated over a distributed network of interconnected Data Centres accessed through a central Portal. In addition to service access the portal will provide information on data management standards, tools and protocols. The architecture has been designed to provide a coherent system based on V1 services, whilst leaving the pathway open for later extension with V2 services. For the implementation, a range of technical components have been defined. Some are already operational with the remainder in the final stages of development and testing. These make use of recent web technologies, and also comprise Java components, to provide multi-platform support and syntactic interoperability. To facilitate sharing of resources and interoperability, SeaDataNet has adopted SOAP Web Service technology. The SeaDataNet architecture and components have been designed to handle all kinds of oceanographic and marine environmental data including both in-situ measurements and remote sensing observations. The V1 technical development is ready and the V1 system is now being implemented and adopted by all participating data centres in SeaDataNet. Interoperability: Interoperability is the key to distributed data management system success and it is achieved in SeaDataNet V1 by: Using common quality control protocols and flag scale Using controlled vocabularies from a single source that have been developed using international content governance Adopting the ISO 19115 metadata standard for all metadata directories Providing XML Validation Services to quality control the metadata maintenance, including field content verification based on Schematron. Providing standard metadata entry tools Using harmonised Data Transport Formats (NetCDF, ODV ASCII and MedAtlas ASCII) for data sets delivery Adopting of OGC standards for mapping and viewing services Using SOAP Web Services in the SeaDataNet architecture SeaDataNet V1 Delivery Services: An important objective of the V1 system is to provide transparent access to the distributed data sets via a unique user interface at the SeaDataNet portal and download service. In the SeaDataNet V1 architecture the Common Data Index (CDI) V1 provides the link between discovery and delivery. The CDI user interface enables users to have a detailed insight of the availability and geographical distribution of marine data, archived at the connected data centres, and it provides the means for downloading data sets in common formats via a transaction mechanism. The SeaDataNet portal provides registered users access to these distributed data sets via the CDI V1 Directory and a shopping basket mechanism. This allows registered users to locate data of interest and submit their data requests. The requests are forwarded automatically from the portal to the relevant SeaDataNet data centres. This process is controlled via the Request Status Manager (RSM) Web Service at the portal and a Download Manager (DM) java software module, implemented at each of the data centres. The RSM also enables registered users to check regularly the status of their requests and download data sets, after access has been granted. Data centres can follow all transactions for their data sets online and can handle requests which require their consent. The actual delivery of data sets is done between the user and the selected data centre. The CDI V1 system is now being populated by all participating data centres in SeaDataNet, thereby phasing out CDI V0. 0.1 SeaDataNet Partners: IFREMER (France), MARIS (Netherlands), HCMR/HNODC (Greece), ULg (Belgium), OGS (Italy), NERC/BODC (UK), BSH/DOD (Germany), SMHI (Sweden), IEO (Spain), RIHMI/WDC (Russia), IOC (International), ENEA (Italy), INGV (Italy), METU (Turkey), CLS (France), AWI (Germany), IMR (Norway), NERI (Denmark), ICES (International), EC-DG JRC (International), MI (Ireland), IHPT (Portugal), RIKZ (Netherlands), RBINS/MUMM (Belgium), VLIZ (Belgium), MRI (Iceland), FIMR (Finland ), IMGW (Poland), MSI (Estonia), IAE/UL (Latvia), CMR (Lithuania), SIO/RAS (Russia), MHI/DMIST (Ukraine), IO/BAS (Bulgaria), NIMRD (Romania), TSU (Georgia), INRH (Morocco), IOF (Croatia), PUT (Albania), NIB (Slovenia), UoM (Malta), OC/UCY (Cyprus), IOLR (Israel), NCSR/NCMS (Lebanon), CNR-ISAC (Italy), ISMAL (Algeria), INSTM (Tunisia)

A Grid Metadata Service for Earth and Environmental Sciences

NASA Astrophysics Data System (ADS)

Fiore, Sandro; Negro, Alessandro; Aloisio, Giovanni

2010-05-01

Critical challenges for climate modeling researchers are strongly connected with the increasingly complex simulation models and the huge quantities of produced datasets. Future trends in climate modeling will only increase computational and storage requirements. For this reason the ability to transparently access to both computational and data resources for large-scale complex climate simulations must be considered as a key requirement for Earth Science and Environmental distributed systems. From the data management perspective (i) the quantity of data will continuously increases, (ii) data will become more and more distributed and widespread, (iii) data sharing/federation will represent a key challenging issue among different sites distributed worldwide, (iv) the potential community of users (large and heterogeneous) will be interested in discovery experimental results, searching of metadata, browsing collections of files, compare different results, display output, etc.; A key element to carry out data search and discovery, manage and access huge and distributed amount of data is the metadata handling framework. What we propose for the management of distributed datasets is the GRelC service (a data grid solution focusing on metadata management). Despite the classical approaches, the proposed data-grid solution is able to address scalability, transparency, security and efficiency and interoperability. The GRelC service we propose is able to provide access to metadata stored in different and widespread data sources (relational databases running on top of MySQL, Oracle, DB2, etc. leveraging SQL as query language, as well as XML databases - XIndice, eXist, and libxml2 based documents, adopting either XPath or XQuery) providing a strong data virtualization layer in a grid environment. Such a technological solution for distributed metadata management leverages on well known adopted standards (W3C, OASIS, etc.); (ii) supports role-based management (based on VOMS), which increases flexibility and scalability; (iii) provides full support for Grid Security Infrastructure, which means (authorization, mutual authentication, data integrity, data confidentiality and delegation); (iv) is compatible with existing grid middleware such as gLite and Globus and finally (v) is currently adopted at the Euro-Mediterranean Centre for Climate Change (CMCC - Italy) to manage the entire CMCC data production activity as well as in the international Climate-G testbed.

Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Fei; Maslov, Sergei; Yoo, Shinjae

Here, transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metadata or differences in annotation styles by different labs. In this study, we carefully selected and integrated 6,057 Arabidopsis microarray expression samples from 304 experiments deposited to NCBI GEO. Metadata such as tissue type, growth condition, and developmental stage were manually curated for each sample. We then studied global expression landscape of the integrated dataset andmore » found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome compared to aerial tissues, but the transcriptome of cultured root is more similar to those of aerial tissues as the former samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating re-use of plant transcriptome data. As a proof of principle we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified accuracy of our predictions with samples’ metadata provided by authors.« less

Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis

DOE PAGES

He, Fei; Maslov, Sergei; Yoo, Shinjae; ...

2016-05-25

Here, transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metadata or differences in annotation styles by different labs. In this study, we carefully selected and integrated 6,057 Arabidopsis microarray expression samples from 304 experiments deposited to NCBI GEO. Metadata such as tissue type, growth condition, and developmental stage were manually curated for each sample. We then studied global expression landscape of the integrated dataset andmore » found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome compared to aerial tissues, but the transcriptome of cultured root is more similar to those of aerial tissues as the former samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating re-use of plant transcriptome data. As a proof of principle we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified accuracy of our predictions with samples’ metadata provided by authors.« less

The Use of Virtual Globes as a Spatial Teaching Tool with Suggestions for Metadata Standards

ERIC Educational Resources Information Center

Schultz, Richard B.; Kerski, Joseph J.; Patterson, Todd C.

2008-01-01

Virtual Globe software has become extremely popular both inside and outside of educational settings. This software allows users to explore the Earth in three dimensions while streaming satellite imagery, elevation, and other data from the Internet. Virtual Globes, such as Google Earth, NASA World Wind, and ESRI's ArcGIS Explorer can be effectively…

A Quantitative Experimental Study of the Effectiveness of Systems to Identify Network Attackers

ERIC Educational Resources Information Center

Handorf, C. Russell

2016-01-01

This study analyzed the meta-data collected from a honeypot that was run by the Federal Bureau of Investigation for a period of 5 years. This analysis compared the use of existing industry methods and tools, such as Intrusion Detection System alerts, network traffic flow and system log traffic, within the Open Source Security Information Manager…

The CARMEN software as a service infrastructure.

PubMed

Weeks, Michael; Jessop, Mark; Fletcher, Martyn; Hodge, Victoria; Jackson, Tom; Austin, Jim

2013-01-28

The CARMEN platform allows neuroscientists to share data, metadata, services and workflows, and to execute these services and workflows remotely via a Web portal. This paper describes how we implemented a service-based infrastructure into the CARMEN Virtual Laboratory. A Software as a Service framework was developed to allow generic new and legacy code to be deployed as services on a heterogeneous execution framework. Users can submit analysis code typically written in Matlab, Python, C/C++ and R as non-interactive standalone command-line applications and wrap them as services in a form suitable for deployment on the platform. The CARMEN Service Builder tool enables neuroscientists to quickly wrap their analysis software for deployment to the CARMEN platform, as a service without knowledge of the service framework or the CARMEN system. A metadata schema describes each service in terms of both system and user requirements. The search functionality allows services to be quickly discovered from the many services available. Within the platform, services may be combined into more complicated analyses using the workflow tool. CARMEN and the service infrastructure are targeted towards the neuroscience community; however, it is a generic platform, and can be targeted towards any discipline.

GraphMeta: Managing HPC Rich Metadata in Graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Dong; Chen, Yong; Carns, Philip

High-performance computing (HPC) systems face increasingly critical metadata management challenges, especially in the approaching exascale era. These challenges arise not only from exploding metadata volumes, but also from increasingly diverse metadata, which contains data provenance and arbitrary user-defined attributes in addition to traditional POSIX metadata. This ‘rich’ metadata is becoming critical to supporting advanced data management functionality such as data auditing and validation. In our prior work, we identified a graph-based model as a promising solution to uniformly manage HPC rich metadata due to its flexibility and generality. However, at the same time, graph-based HPC rich metadata anagement also introducesmore » significant challenges to the underlying infrastructure. In this study, we first identify the challenges on the underlying infrastructure to support scalable, high-performance rich metadata management. Based on that, we introduce GraphMeta, a graphbased engine designed for this use case. It achieves performance scalability by introducing a new graph partitioning algorithm and a write-optimal storage engine. We evaluate GraphMeta under both synthetic and real HPC metadata workloads, compare it with other approaches, and demonstrate its advantages in terms of efficiency and usability for rich metadata management in HPC systems.« less

Tools in a clinical information system supporting clinical trials at a Swiss University Hospital.

PubMed

Weisskopf, Michael; Bucklar, Guido; Blaser, Jürg

2014-12-01

Issues concerning inadequate source data of clinical trials rank second in the most common findings by regulatory authorities. The increasing use of electronic clinical information systems by healthcare providers offers an opportunity to facilitate and improve the conduct of clinical trials and the source documentation. We report on a number of tools implemented into the clinical information system of a university hospital to support clinical research. In 2011/2012, a set of tools was developed in the clinical information system of the University Hospital Zurich to support clinical research, including (1) a trial registry for documenting metadata on the clinical trials conducted at the hospital, (2) a patient-trial-assignment-tool to tag patients in the electronic medical charts as participants of specific trials, (3) medical record templates for the documentation of study visits and trial-related procedures, (4) online queries on trials and trial participants, (5) access to the electronic medical records for clinical monitors, (6) an alerting tool to notify of hospital admissions of trial participants, (7) queries to identify potentially eligible patients in the planning phase as trial feasibility checks and during the trial as recruitment support, and (8) order sets to facilitate the complete and accurate performance of study visit procedures. The number of approximately 100 new registrations per year in the voluntary trial registry in the clinical information system now matches the numbers of the existing mandatory trial registry of the hospital. Likewise, the yearly numbers of patients tagged as trial participants as well as the use of the standardized trial record templates increased to 2408 documented trial enrolments and 190 reports generated/month in the year 2013. Accounts for 32 clinical monitors have been established in the first 2 years monitoring a total of 49 trials in 16 clinical departments. A total of 15 months after adding the optional feature of hospital admission alerts of trial participants, 107 running trials have activated this option, including 48 out of 97 studies (49.5%) registered in the year 2013, generating approximately 85 alerts per month. The popularity of the presented tools in the clinical information system illustrates their potential to facilitate the conduct of clinical trials. The tools also allow for enhanced transparency on trials conducted at the hospital. Future studies on monitoring and inspection findings will have to evaluate their impact on quality and safety. © The Author(s) 2014.

Metadata (MD)

Treesearch

Robert E. Keane

2006-01-01

The Metadata (MD) table in the FIREMON database is used to record any information about the sampling strategy or data collected using the FIREMON sampling procedures. The MD method records metadata pertaining to a group of FIREMON plots, such as all plots in a specific FIREMON project. FIREMON plots are linked to metadata using a unique metadata identifier that is...

Sharing brain mapping statistical results with the neuroimaging data model

PubMed Central

Maumet, Camille; Auer, Tibor; Bowring, Alexander; Chen, Gang; Das, Samir; Flandin, Guillaume; Ghosh, Satrajit; Glatard, Tristan; Gorgolewski, Krzysztof J.; Helmer, Karl G.; Jenkinson, Mark; Keator, David B.; Nichols, B. Nolan; Poline, Jean-Baptiste; Reynolds, Richard; Sochat, Vanessa; Turner, Jessica; Nichols, Thomas E.

2016-01-01

Only a tiny fraction of the data and metadata produced by an fMRI study is finally conveyed to the community. This lack of transparency not only hinders the reproducibility of neuroimaging results but also impairs future meta-analyses. In this work we introduce NIDM-Results, a format specification providing a machine-readable description of neuroimaging statistical results along with key image data summarising the experiment. NIDM-Results provides a unified representation of mass univariate analyses including a level of detail consistent with available best practices. This standardized representation allows authors to relay methods and results in a platform-independent regularized format that is not tied to a particular neuroimaging software package. Tools are available to export NIDM-Result graphs and associated files from the widely used SPM and FSL software packages, and the NeuroVault repository can import NIDM-Results archives. The specification is publically available at: http://nidm.nidash.org/specs/nidm-results.html. PMID:27922621

jmzTab: a java interface to the mzTab data standard.

PubMed

Xu, Qing-Wei; Griss, Johannes; Wang, Rui; Jones, Andrew R; Hermjakob, Henning; Vizcaíno, Juan Antonio

2014-06-01

mzTab is the most recent standard format developed by the Proteomics Standards Initiative. mzTab is a flexible tab-delimited file that can capture identification and quantification results coming from MS-based proteomics and metabolomics approaches. We here present an open-source Java application programming interface for mzTab called jmzTab. The software allows the efficient processing of mzTab files, providing read and write capabilities, and is designed to be embedded in other software packages. The second key feature of the jmzTab model is that it provides a flexible framework to maintain the logical integrity between the metadata and the table-based sections in the mzTab files. In this article, as two example implementations, we also describe two stand-alone tools that can be used to validate mzTab files and to convert PRIDE XML files to mzTab. The library is freely available at http://mztab.googlecode.com. © 2014 The Authors PROTEOMICS Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

An overview of the NASA Langley Atmospheric Data Center: Online tools to effectively disseminate Earth science data products

NASA Astrophysics Data System (ADS)

Parker, L.; Dye, R. A.; Perez, J.; Rinsland, P.

2012-12-01

Over the past decade the Atmospheric Science Data Center (ASDC) at NASA Langley Research Center has archived and distributed a variety of satellite mission and aircraft campaign data sets. These datasets posed unique challenges to the user community at large due to the sheer volume and variety of the data and the lack of intuitive features in the order tools available to the investigator. Some of these data sets also lack sufficient metadata to provide rudimentary data discovery. To meet the needs of emerging users, the ASDC addressed issues in data discovery and delivery through the use of standards in data and access methods, and distribution through appropriate portals. The ASDC is currently undergoing a refresh of its webpages and Ordering Tools that will leverage updated collection level metadata in an effort to enhance the user experience. The ASDC is now providing search and subset capability to key mission satellite data sets. The ASDC has collaborated with Science Teams to accommodate prospective science users in the climate and modeling communities. The ASDC is using a common framework that enables more rapid development and deployment of search and subset tools that provide enhanced access features for the user community. Features of the Search and Subset web application enables a more sophisticated approach to selecting and ordering data subsets by parameter, date, time, and geographic area. The ASDC has also applied key practices from satellite missions to the multi-campaign aircraft missions executed for Earth Venture-1 and MEaSUReS

The RD-Connect Registry & Biobank Finder: a tool for sharing aggregated data and metadata among rare disease researchers.

PubMed

Gainotti, Sabina; Torreri, Paola; Wang, Chiuhui Mary; Reihs, Robert; Mueller, Heimo; Heslop, Emma; Roos, Marco; Badowska, Dorota Mazena; de Paulis, Federico; Kodra, Yllka; Carta, Claudio; Martìn, Estrella Lopez; Miller, Vanessa Rangel; Filocamo, Mirella; Mora, Marina; Thompson, Mark; Rubinstein, Yaffa; Posada de la Paz, Manuel; Monaco, Lucia; Lochmüller, Hanns; Taruscio, Domenica

2018-05-01

In rare disease (RD) research, there is a huge need to systematically collect biomaterials, phenotypic, and genomic data in a standardized way and to make them findable, accessible, interoperable and reusable (FAIR). RD-Connect is a 6 years global infrastructure project initiated in November 2012 that links genomic data with patient registries, biobanks, and clinical bioinformatics tools to create a central research resource for RDs. Here, we present RD-Connect Registry & Biobank Finder, a tool that helps RD researchers to find RD biobanks and registries and provide information on the availability and accessibility of content in each database. The finder concentrates information that is currently sparse on different repositories (inventories, websites, scientific journals, technical reports, etc.), including aggregated data and metadata from participating databases. Aggregated data provided by the finder, if appropriately checked, can be used by researchers who are trying to estimate the prevalence of a RD, to organize a clinical trial on a RD, or to estimate the volume of patients seen by different clinical centers. The finder is also a portal to other RD-Connect tools, providing a link to the RD-Connect Sample Catalogue, a large inventory of RD biological samples available in participating biobanks for RD research. There are several kinds of users and potential uses for the RD-Connect Registry & Biobank Finder, including researchers collaborating with academia and the industry, dealing with the questions of basic, translational, and/or clinical research. As of November 2017, the finder is populated with aggregated data for 222 registries and 21 biobanks.

A Folksonomy-Based Lightweight Resource Annotation Metadata Schema for Personalized Hypermedia Learning Resource Delivery

ERIC Educational Resources Information Center

Lau, Simon Boung-Yew; Lee, Chien-Sing; Singh, Yashwant Prasad

2015-01-01

With the proliferation of social Web applications, users can now collaboratively author, share and access hypermedia learning resources, contributing to richer learning experiences outside formal education. These resources may or may not be educational. However, they can be harnessed for educational purposes by adapting and personalizing them to…

Semantic Overlays in Educational Content Networks--The hylOs Approach

ERIC Educational Resources Information Center

Engelhardt, Michael; Hildebrand, Arne; Lange, Dagmar; Schmidt, Thomas C.

2006-01-01

Purpose: The paper aims to introduce an educational content management system, Hypermedia Learning Objects System (hylOs), which is fully compliant to the IEEE LOM eLearning object metadata standard. Enabled through an advanced authoring toolset, hylOs allows the definition of instructional overlays of a given eLearning object mesh.…

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Science.gov Websites

: + Advanced Search × Advanced Search All Fields: Title: Full Text: Bibliographic Data: Creator / Author: Name discoverable at no charge to users. DOE PAGES offers free public access to the best available full-text version and distributed content, with PAGES maintaining a permanent archive of all full text and metadata. In

The Arctic Observing Network (AON)Cooperative Arctic Data and Information Service (CADIS)

NASA Astrophysics Data System (ADS)

Moore, J.; Fetterer, F.; Middleton, D.; Ramamurthy, M.; Barry, R.

2007-12-01

The Arctic Observing Network (AON) is intended to be a federation of 34 land, atmosphere and ocean observation sites, some already operating and some newly funded by the U.S. National Science Foundation. This International Polar Year (IPY) initiative will acquire a major portion of the data coming from the interagency Study of Environmental Arctic Change (SEARCH). AON will succeed in supporting the science envisioned by its planners only if it functions as a system and not as a collection of independent observation programs. Development and implementation of a comprehensive data management strategy will key a key to the success of this effort. AON planners envision an ideal data management system that includes a portal through which scientists can submit metadata and datasets at a single location; search the complete archive and find all data relevant to a location or process; all data have browse imagery and complete documentation; time series or fields can be plotted on line, and all data are in a relational database so that multiple data sets and sources can be queried and retrieved. The Cooperative Arctic Data and Information Service (CADIS) will provide near-real-time data delivery, a long-term repository for data, a portal for data discovery, and tools to manipulate data by building on existing tools like the Unidata Integrated Data Viewer (IDV). Our approach to the data integration challenge is to start by asking investigators to provide metadata via a general purpose user interface. An entry tool assists PIs in writing metadata and submitting data. Data can be submitted to the archive in NetCDF with Climate and Forecast conventions or in one of several other standard formats where possible. CADIS is a joint effort of the University Corporation for Atmospheric Research (UCAR), the National Snow and Ice Data Center (NSIDC), and the National Center for Atmospheric Research (NCAR). In the first year, we are concentrating on establishing metadata protocols that are compatible with international standards, and on demonstrating data submission, search and visualization tools with a subset of AON data. These capabilities will be expanded in years 2 and 3. By working with AON investigators and by using evolving conventions for in situ data formats as they mature, we hope to bring CADIS to the full level of data integration imagined by AON planners. The CADIS development will be described in terms of challenges, implementation strategies and progress to date. The developers are making a conscious effort to integrate this system and its data holdings with the complementary efforts in the SEARCH and IPY programs. The interdisciplinary content of the data, the variations in format and documentation, as well as its geographic coverage across the Arctic Basin all impact the form and effectiveness of the CADIS system architecture. The clever solutions to the complexity of implementing a comprehensive data management strategy implied in this diversity will be a focus of the presentation.

Fast processing of digital imaging and communications in medicine (DICOM) metadata using multiseries DICOM format.

PubMed

Ismail, Mahmoud; Philbin, James

2015-04-01

The digital imaging and communications in medicine (DICOM) information model combines pixel data and its metadata in a single object. There are user scenarios that only need metadata manipulation, such as deidentification and study migration. Most picture archiving and communication system use a database to store and update the metadata rather than updating the raw DICOM files themselves. The multiseries DICOM (MSD) format separates metadata from pixel data and eliminates duplicate attributes. This work promotes storing DICOM studies in MSD format to reduce the metadata processing time. A set of experiments are performed that update the metadata of a set of DICOM studies for deidentification and migration. The studies are stored in both the traditional single frame DICOM (SFD) format and the MSD format. The results show that it is faster to update studies' metadata in MSD format than in SFD format because the bulk data is separated in MSD and is not retrieved from the storage system. In addition, it is space efficient to store the deidentified studies in MSD format as it shares the same bulk data object with the original study. In summary, separation of metadata from pixel data using the MSD format provides fast metadata access and speeds up applications that process only the metadata.

Transforming Dermatologic Imaging for the Digital Era: Metadata and Standards.

PubMed

Caffery, Liam J; Clunie, David; Curiel-Lewandrowski, Clara; Malvehy, Josep; Soyer, H Peter; Halpern, Allan C

2018-01-17

Imaging is increasingly being used in dermatology for documentation, diagnosis, and management of cutaneous disease. The lack of standards for dermatologic imaging is an impediment to clinical uptake. Standardization can occur in image acquisition, terminology, interoperability, and metadata. This paper presents the International Skin Imaging Collaboration position on standardization of metadata for dermatologic imaging. Metadata is essential to ensure that dermatologic images are properly managed and interpreted. There are two standards-based approaches to recording and storing metadata in dermatologic imaging. The first uses standard consumer image file formats, and the second is the file format and metadata model developed for the Digital Imaging and Communication in Medicine (DICOM) standard. DICOM would appear to provide an advantage over using consumer image file formats for metadata as it includes all the patient, study, and technical metadata necessary to use images clinically. Whereas, consumer image file formats only include technical metadata and need to be used in conjunction with another actor-for example, an electronic medical record-to supply the patient and study metadata. The use of DICOM may have some ancillary benefits in dermatologic imaging including leveraging DICOM network and workflow services, interoperability of images and metadata, leveraging existing enterprise imaging infrastructure, greater patient safety, and better compliance to legislative requirements for image retention.

Fast processing of digital imaging and communications in medicine (DICOM) metadata using multiseries DICOM format

PubMed Central

Ismail, Mahmoud; Philbin, James

2015-01-01

Abstract. The digital imaging and communications in medicine (DICOM) information model combines pixel data and its metadata in a single object. There are user scenarios that only need metadata manipulation, such as deidentification and study migration. Most picture archiving and communication system use a database to store and update the metadata rather than updating the raw DICOM files themselves. The multiseries DICOM (MSD) format separates metadata from pixel data and eliminates duplicate attributes. This work promotes storing DICOM studies in MSD format to reduce the metadata processing time. A set of experiments are performed that update the metadata of a set of DICOM studies for deidentification and migration. The studies are stored in both the traditional single frame DICOM (SFD) format and the MSD format. The results show that it is faster to update studies’ metadata in MSD format than in SFD format because the bulk data is separated in MSD and is not retrieved from the storage system. In addition, it is space efficient to store the deidentified studies in MSD format as it shares the same bulk data object with the original study. In summary, separation of metadata from pixel data using the MSD format provides fast metadata access and speeds up applications that process only the metadata. PMID:26158117

ISO, FGDC, DIF and Dublin Core - Making Sense of Metadata Standards for Earth Science Data

NASA Astrophysics Data System (ADS)

Jones, P. R.; Ritchey, N. A.; Peng, G.; Toner, V. A.; Brown, H.

2014-12-01

Metadata standards provide common definitions of metadata fields for information exchange across user communities. Despite the broad adoption of metadata standards for Earth science data, there are still heterogeneous and incompatible representations of information due to differences between the many standards in use and how each standard is applied. Federal agencies are required to manage and publish metadata in different metadata standards and formats for various data catalogs. In 2014, the NOAA National Climatic data Center (NCDC) managed metadata for its scientific datasets in ISO 19115-2 in XML, GCMD Directory Interchange Format (DIF) in XML, DataCite Schema in XML, Dublin Core in XML, and Data Catalog Vocabulary (DCAT) in JSON, with more standards and profiles of standards planned. Of these standards, the ISO 19115-series metadata is the most complete and feature-rich, and for this reason it is used by NCDC as the source for the other metadata standards. We will discuss the capabilities of metadata standards and how these standards are being implemented to document datasets. Successful implementations include developing translations and displays using XSLTs, creating links to related data and resources, documenting dataset lineage, and establishing best practices. Benefits, gaps, and challenges will be highlighted with suggestions for improved approaches to metadata storage and maintenance.

Oceans 2.0: a Data Management Infrastructure as a Platform

NASA Astrophysics Data System (ADS)

Pirenne, B.; Guillemot, E.

2012-04-01

Oceans 2.0: a Data Management Infrastructure as a Platform Benoît Pirenne, Associate Director, IT, NEPTUNE Canada Eric Guillemot, Manager, Software Development, NEPTUNE Canada The Data Management and Archiving System (DMAS) serving the needs of a number of undersea observing networks such as VENUS and NEPTUNE Canada was conceived from the beginning as a Service-Oriented Infrastructure. Its core functional elements (data acquisition, transport, archiving, retrieval and processing) can interact with the outside world using Web Services. Those Web Services can be exploited by a variety of higher level applications. Over the years, DMAS has developed Oceans 2.0: an environment where these techniques are implemented. The environment thereby becomes a platform in that it allows for easy addition of new and advanced features that build upon the tools at the core of the system. The applications that have been developed include: data search and retrieval, including options such as data product generation, data decimation or averaging, etc. dynamic infrastructure description (search all observatory metadata) and visualization data visualization, including dynamic scalar data plots, integrated fast video segment search and viewing Building upon these basic applications are new concepts, coming from the Web 2.0 world that DMAS has added: They allow people equipped only with a web browser to collaborate and contribute their findings or work results to the wider community. Examples include: addition of metadata tags to any part of the infrastructure or to any data item (annotations) ability to edit and execute, share and distribute Matlab code on-line, from a simple web browser, with specific calls within the code to access data ability to interactively and graphically build pipeline processing jobs that can be executed on the cloud web-based, interactive instrument control tools that allow users to truly share the use of the instruments and communicate with each other and last but not least: a public tool in the form of a game, that crowd-sources the inventory of the underwater video archive content, thereby adding tremendous amounts of metadata Beyond those tools that represent the functionality presently available to users, a number of the Web Services dedicated to data access are being exposed for anyone to use. This allows not only for ad hoc data access by individuals who need non-interactive access, but will foster the development of new applications in a variety of areas.

From the inside-out: Retrospectives on a metadata improvement process to advance the discoverability of NASÁs earth science data

NASA Astrophysics Data System (ADS)

Hernández, B. E.; Bugbee, K.; le Roux, J.; Beaty, T.; Hansen, M.; Staton, P.; Sisco, A. W.

2017-12-01

Earth observation (EO) data collected as part of NASA's Earth Observing System Data and Information System (EOSDIS) is now searchable via the Common Metadata Repository (CMR). The Analysis and Review of CMR (ARC) Team at Marshall Space Flight Center has been tasked with reviewing all NASA metadata records in the CMR ( 7,000 records). Each collection level record and constituent granule level metadata are reviewed for both completeness as well as compliance with the CMR's set of metadata standards, as specified in the Unified Metadata Model (UMM). NASA's Distributed Active Archive Centers (DAACs) have been harmonizing priority metadata records within the context of the inter-agency federal Big Earth Data Initiative (BEDI), which seeks to improve the discoverability, accessibility, and usability of EO data. Thus, the first phase of this project constitutes reviewing BEDI metadata records, while the second phase will constitute reviewing the remaining non-BEDI records in CMR. This presentation will discuss the ARC team's findings in terms of the overall quality of BEDI records across all DAACs as well as compliance with UMM standards. For instance, only a fifth of the collection-level metadata fields needed correction, compared to a quarter of the granule-level fields. It should be noted that the degree to which DAACs' metadata did not comply with the UMM standards may reflect multiple factors, such as recent changes in the UMM standards, and the utilization of different metadata formats (e.g. DIF 10, ECHO 10, ISO 19115-1) across the DAACs. Insights, constructive criticism, and lessons learned from this metadata review process will be contributed from both ORNL and SEDAC. Further inquiry along such lines may lead to insights which may improve the metadata curation process moving forward. In terms of the broader implications for metadata compliance with the UMM standards, this research has shown that a large proportion of the prioritized collections have already been made compliant, although the process of improving metadata quality is ongoing and iterative. Further research is also warranted into whether or not the gains in metadata quality are also driving gains in data use.

Forum Guide to Metadata: The Meaning behind Education Data. NFES 2009-805

ERIC Educational Resources Information Center

National Forum on Education Statistics, 2009

2009-01-01

The purpose of this guide is to empower people to more effectively use data as information. To accomplish this, the publication explains what metadata are; why metadata are critical to the development of sound education data systems; what components comprise a metadata system; what value metadata bring to data management and use; and how to…

Metadata Effectiveness in Internet Discovery: An Analysis of Digital Collection Metadata Elements and Internet Search Engine Keywords

ERIC Educational Resources Information Center

Yang, Le

2016-01-01

This study analyzed digital item metadata and keywords from Internet search engines to learn what metadata elements actually facilitate discovery of digital collections through Internet keyword searching and how significantly each metadata element affects the discovery of items in a digital repository. The study found that keywords from Internet…

ESGF and WDCC: The Double Structure of the Digital Data Storage at DKRZ

NASA Astrophysics Data System (ADS)

Toussaint, F.; Höck, H.

2016-12-01

Since a couple of years, Digital Repositories of climate science face new challenges: International projects are global collaborations. The data storage in parallel moved to federated, distributed storage systems like ESGF. For the long term archival storage (LTA) on the other hand, communities, funders, and data users make stronger demands for data and metadata quality to facilitate data use and reuse. At DKRZ, this situation led to a twofold data dissemination system - a situation which has influence on administration, workflows, and sustainability of the data. The ESGF system is focused on the needs of users as partners in global projects. It includes replication tools, detailed global project standards, and efficient search for the data to download. In contrast, DKRZ's classical CERA LTA storage aims for long term data holding and data curation as well as for data reuse requiring high metadata quality standards. In addition, for LTA data a Digital Object Identifier publication service for the direct integration of research data in scientific publications has been implemented. The editorial process at DKRZ-LTA ensures the quality of metadata and research data. The DOI and a citation code are provided and afterwards registered under DataCite's (datacite.org) regulations. In the overall data life cycle continuous reliability of the data and metadata quality is essential to allow for data handling at Petabytes level, data long term usability, and adequate publication of the results. These considerations lead to the question "What is quality" - with respect to data, to the repository itself, to the publisher, and the user? Global consensus is needed for these assessments as the phases of the end to end workflow gear into each other: For data and metadata, checks need to go hand in hand with the processes of production and storage. The results can be judged following a Quality Maturity Matrix (QMM). Repositories can be certified according to their trustworthiness. For the publication of any scientific conclusions, scientific community, funders, media, and policy makers ask for the publisher's impact in terms of readers' credit, run, and presentation quality. The paper describes the data life cycle. Emphasis is put on the different levels of quality assessment which at DKRZ ensure the data and metadata quality.

Automated Database Mediation Using Ontological Metadata Mappings

PubMed Central

Marenco, Luis; Wang, Rixin; Nadkarni, Prakash

2009-01-01

Objective To devise an automated approach for integrating federated database information using database ontologies constructed from their extended metadata. Background One challenge of database federation is that the granularity of representation of equivalent data varies across systems. Dealing effectively with this problem is analogous to dealing with precoordinated vs. postcoordinated concepts in biomedical ontologies. Model Description The authors describe an approach based on ontological metadata mapping rules defined with elements of a global vocabulary, which allows a query specified at one granularity level to fetch data, where possible, from databases within the federation that use different granularities. This is implemented in OntoMediator, a newly developed production component of our previously described Query Integrator System. OntoMediator's operation is illustrated with a query that accesses three geographically separate, interoperating databases. An example based on SNOMED also illustrates the applicability of high-level rules to support the enforcement of constraints that can prevent inappropriate curator or power-user actions. Summary A rule-based framework simplifies the design and maintenance of systems where categories of data must be mapped to each other, for the purpose of either cross-database query or for curation of the contents of compositional controlled vocabularies. PMID:19567801

Enhanced Management of and Access to Hurricane Sandy Ocean and Coastal Mapping Data

NASA Astrophysics Data System (ADS)

Eakins, B.; Neufeld, D.; Varner, J. D.; McLean, S. J.

2014-12-01

NOAA's National Geophysical Data Center (NGDC) has significantly improved the discovery and delivery of its geophysical data holdings, initially targeting ocean and coastal mapping (OCM) data in the U.S. coastal region impacted by Hurricane Sandy in 2012. We have developed a browser-based, interactive interface that permits users to refine their initial map-driven data-type choices prior to bulk download (e.g., by selecting individual surveys), including the ability to choose ancillary files, such as reports or derived products. Initial OCM data types now available in a U.S. East Coast map viewer, as well as underlying web services, include: NOS hydrographic soundings and multibeam sonar bathymetry. Future releases will include trackline geophysics, airborne topographic and bathymetric-topographic lidar, bottom sample descriptions, and digital elevation models.This effort also includes working collaboratively with other NOAA offices and partners to develop automated methods to receive and verify data, stage data for archive, and notify data providers when ingest and archive are completed. We have also developed improved metadata tools to parse XML and auto-populate OCM data catalogs, support the web-based creation and editing of ISO-compliant metadata records, and register metadata in appropriate data portals. This effort supports a variety of NOAA mission requirements, from safe navigation to coastal flood forecasting and habitat characterization.

Metadata-driven Delphi rating on the Internet.

PubMed

Deshpande, Aniruddha M; Shiffman, Richard N; Nadkarni, Prakash M

2005-01-01

Paper-based data collection and analysis for consensus development is inefficient and error-prone. Computerized techniques that could improve efficiency, however, have been criticized as costly, inconvenient and difficult to use. We designed and implemented a metadata-driven Web-based Delphi rating and analysis tool, employing the flexible entity-attribute-value schema to create generic, reusable software. The software can be applied to various domains by altering the metadata; the programming code remains intact. This approach greatly reduces the marginal cost of re-using the software. We implemented our software to prepare for the Conference on Guidelines Standardization. Twenty-three invited experts completed the first round of the Delphi rating on the Web. For each participant, the software generated individualized reports that described the median rating and the disagreement index (calculated from the Interpercentile Range Adjusted for Symmetry) as defined by the RAND/UCLA Appropriateness Method. We evaluated the software with a satisfaction survey using a five-level Likert scale. The panelists felt that Web data entry was convenient (median 4, interquartile range [IQR] 4.0-5.0), acceptable (median 4.5, IQR 4.0-5.0) and easily accessible (median 5, IQR 4.0-5.0). We conclude that Web-based Delphi rating for consensus development is a convenient and acceptable alternative to the traditional paper-based method.

Overview of FEED, the feeding experiments end-user database.

PubMed

Wall, Christine E; Vinyard, Christopher J; Williams, Susan H; Gapeyev, Vladimir; Liu, Xianhua; Lapp, Hilmar; German, Rebecca Z

2011-08-01

The Feeding Experiments End-user Database (FEED) is a research tool developed by the Mammalian Feeding Working Group at the National Evolutionary Synthesis Center that permits synthetic, evolutionary analyses of the physiology of mammalian feeding. The tasks of the Working Group are to compile physiologic data sets into a uniform digital format stored at a central source, develop a standardized terminology for describing and organizing the data, and carry out a set of novel analyses using FEED. FEED contains raw physiologic data linked to extensive metadata. It serves as an archive for a large number of existing data sets and a repository for future data sets. The metadata are stored as text and images that describe experimental protocols, research subjects, and anatomical information. The metadata incorporate controlled vocabularies to allow consistent use of the terms used to describe and organize the physiologic data. The planned analyses address long-standing questions concerning the phylogenetic distribution of phenotypes involving muscle anatomy and feeding physiology among mammals, the presence and nature of motor pattern conservation in the mammalian feeding muscles, and the extent to which suckling constrains the evolution of feeding behavior in adult mammals. We expect FEED to be a growing digital archive that will facilitate new research into understanding the evolution of feeding anatomy.

Automated DICOM metadata and volumetric anatomical information extraction for radiation dosimetry

NASA Astrophysics Data System (ADS)

Papamichail, D.; Ploussi, A.; Kordolaimi, S.; Karavasilis, E.; Papadimitroulas, P.; Syrgiamiotis, V.; Efstathopoulos, E.

2015-09-01

Patient-specific dosimetry calculations based on simulation techniques have as a prerequisite the modeling of the modality system and the creation of voxelized phantoms. This procedure requires the knowledge of scanning parameters and patients’ information included in a DICOM file as well as image segmentation. However, the extraction of this information is complicated and time-consuming. The objective of this study was to develop a simple graphical user interface (GUI) to (i) automatically extract metadata from every slice image of a DICOM file in a single query and (ii) interactively specify the regions of interest (ROI) without explicit access to the radiology information system. The user-friendly application developed in Matlab environment. The user can select a series of DICOM files and manage their text and graphical data. The metadata are automatically formatted and presented to the user as a Microsoft Excel file. The volumetric maps are formed by interactively specifying the ROIs and by assigning a specific value in every ROI. The result is stored in DICOM format, for data and trend analysis. The developed GUI is easy, fast and and constitutes a very useful tool for individualized dosimetry. One of the future goals is to incorporate a remote access to a PACS server functionality.

Simple, Script-Based Science Processing Archive

NASA Technical Reports Server (NTRS)

Lynnes, Christopher; Hegde, Mahabaleshwara; Barth, C. Wrandle

2007-01-01

The Simple, Scalable, Script-based Science Processing (S4P) Archive (S4PA) is a disk-based archival system for remote sensing data. It is based on the data-driven framework of S4P and is used for data transfer, data preprocessing, metadata generation, data archive, and data distribution. New data are automatically detected by the system. S4P provides services such as data access control, data subscription, metadata publication, data replication, and data recovery. It comprises scripts that control the data flow. The system detects the availability of data on an FTP (file transfer protocol) server, initiates data transfer, preprocesses data if necessary, and archives it on readily available disk drives with FTP and HTTP (Hypertext Transfer Protocol) access, allowing instantaneous data access. There are options for plug-ins for data preprocessing before storage. Publication of metadata to external applications such as the Earth Observing System Clearinghouse (ECHO) is also supported. S4PA includes a graphical user interface for monitoring the system operation and a tool for deploying the system. To ensure reliability, S4P continuously checks stored data for integrity, Further reliability is provided by tape backups of disks made once a disk partition is full and closed. The system is designed for low maintenance, requiring minimal operator oversight.

Automated Feature and Event Detection with SDO AIA and HMI Data

NASA Astrophysics Data System (ADS)

Davey, Alisdair; Martens, P. C. H.; Attrill, G. D. R.; Engell, A.; Farid, S.; Grigis, P. C.; Kasper, J.; Korreck, K.; Saar, S. H.; Su, Y.; Testa, P.; Wills-Davey, M.; Savcheva, A.; Bernasconi, P. N.; Raouafi, N.-E.; Delouille, V. A.; Hochedez, J. F..; Cirtain, J. W.; Deforest, C. E.; Angryk, R. A.; de Moortel, I.; Wiegelmann, T.; Georgouli, M. K.; McAteer, R. T. J.; Hurlburt, N.; Timmons, R.

The Solar Dynamics Observatory (SDO) represents a new frontier in quantity and quality of solar data. At about 1.5 TB/day, the data will not be easily digestible by solar physicists using the same methods that have been employed for images from previous missions. In order for solar scientists to use the SDO data effectively they need meta-data that will allow them to identify and retrieve data sets that address their particular science questions. We are building a comprehensive computer vision pipeline for SDO, abstracting complete metadata on many of the features and events detectable on the Sun without human intervention. Our project unites more than a dozen individual, existing codes into a systematic tool that can be used by the entire solar community. The feature finding codes will run as part of the SDO Event Detection System (EDS) at the Joint Science Operations Center (JSOC; joint between Stanford and LMSAL). The metadata produced will be stored in the Heliophysics Event Knowledgebase (HEK), which will be accessible on-line for the rest of the world directly or via the Virtual Solar Observatory (VSO) . Solar scientists will be able to use the HEK to select event and feature data to download for science studies.

CMO: Cruise Metadata Organizer for JAMSTEC Research Cruises

NASA Astrophysics Data System (ADS)

Fukuda, K.; Saito, H.; Hanafusa, Y.; Vanroosebeke, A.; Kitayama, T.

2011-12-01

JAMSTEC's Data Research Center for Marine-Earth Sciences manages and distributes a wide variety of observational data and samples obtained from JAMSTEC research vessels and deep sea submersibles. Generally, metadata are essential to identify data and samples were obtained. In JAMSTEC, cruise metadata include cruise information such as cruise ID, name of vessel, research theme, and diving information such as dive number, name of submersible and position of diving point. They are submitted by chief scientists of research cruises in the Microsoft Excel° spreadsheet format, and registered into a data management database to confirm receipt of observational data files, cruise summaries, and cruise reports. The cruise metadata are also published via "JAMSTEC Data Site for Research Cruises" within two months after end of cruise. Furthermore, these metadata are distributed with observational data, images and samples via several data and sample distribution websites after a publication moratorium period. However, there are two operational issues in the metadata publishing process. One is that duplication efforts and asynchronous metadata across multiple distribution websites due to manual metadata entry into individual websites by administrators. The other is that differential data types or representation of metadata in each website. To solve those problems, we have developed a cruise metadata organizer (CMO) which allows cruise metadata to be connected from the data management database to several distribution websites. CMO is comprised of three components: an Extensible Markup Language (XML) database, an Enterprise Application Integration (EAI) software, and a web-based interface. The XML database is used because of its flexibility for any change of metadata. Daily differential uptake of metadata from the data management database to the XML database is automatically processed via the EAI software. Some metadata are entered into the XML database using the web-based interface by a metadata editor in CMO as needed. Then daily differential uptake of metadata from the XML database to databases in several distribution websites is automatically processed using a convertor defined by the EAI software. Currently, CMO is available for three distribution websites: "Deep Sea Floor Rock Sample Database GANSEKI", "Marine Biological Sample Database", and "JAMSTEC E-library of Deep-sea Images". CMO is planned to provide "JAMSTEC Data Site for Research Cruises" with metadata in the future.

Towards Data Value-Level Metadata for Clinical Studies.

PubMed

Zozus, Meredith Nahm; Bonner, Joseph

2017-01-01

While several standards for metadata describing clinical studies exist, comprehensive metadata to support traceability of data from clinical studies has not been articulated. We examine uses of metadata in clinical studies. We examine and enumerate seven sources of data value-level metadata in clinical studies inclusive of research designs across the spectrum of the National Institutes of Health definition of clinical research. The sources of metadata inform categorization in terms of metadata describing the origin of a data value, the definition of a data value, and operations to which the data value was subjected. The latter is further categorized into information about changes to a data value, movement of a data value, retrieval of a data value, and data quality checks, constraints or assessments to which the data value was subjected. The implications of tracking and managing data value-level metadata are explored.

Sea Level Station Metadata for Tsunami Detection, Warning and Research

NASA Astrophysics Data System (ADS)

Stroker, K. J.; Marra, J.; Kari, U. S.; Weinstein, S. A.; Kong, L.

2007-12-01

The devastating earthquake and tsunami of December 26, 2004 has greatly increased recognition of the need for water level data both from the coasts and the deep-ocean. In 2006, the National Oceanic and Atmospheric Administration (NOAA) completed a Tsunami Data Management Report describing the management of data required to minimize the impact of tsunamis in the United States. One of the major gaps defined in this report is the access to global coastal water level data. NOAA's National Geophysical Data Center (NGDC) and National Climatic Data Center (NCDC) are working cooperatively to bridge this gap. NOAA relies on a network of global data, acquired and processed in real-time to support tsunami detection and warning, as well as high-quality global databases of archived data to support research and advanced scientific modeling. In 2005, parties interested in enhancing the access and use of sea level station data united under the NOAA NCDC's Integrated Data and Environmental Applications (IDEA) Center's Pacific Region Integrated Data Enterprise (PRIDE) program to develop a distributed metadata system describing sea level stations (Kari et. al., 2006; Marra et.al., in press). This effort started with pilot activities in a regional framework and is targeted at tsunami detection and warning systems being developed by various agencies. It includes development of the components of a prototype sea level station metadata web service and accompanying Google Earth-based client application, which use an XML-based schema to expose, at a minimum, information in the NOAA National Weather Service (NWS) Pacific Tsunami Warning Center (PTWC) station database needed to use the PTWC's Tide Tool application. As identified in the Tsunami Data Management Report, the need also exists for long-term retention of the sea level station data. NOAA envisions that the retrospective water level data and metadata will also be available through web services, using an XML-based schema. Five high-priority metadata requirements identified at a water level workshop held at the XXIV IUGG Meeting in Perugia will be addressed: consistent, validated, and well defined numbers (e.g. amplitude); exact location of sea level stations; a complete record of sea level data stored in the archive; identifying high-priority sea level stations; and consistent definitions. NOAA's National Geophysical Data Center (NGDC) and co-located World Data Center for Solid Earth Geophysics (including tsunamis) would hold the archive of the sea level station data and distribute the standard metadata. Currently, NGDC is also archiving and distributing the DART buoy deep-ocean water level data and metadata in standards based formats. Kari, Uday S., John J. Marra, Stuart A. Weinstein, 2006 A Tsunami Focused Data Sharing Framework For Integration of Databases that Describe Water Level Station Specifications. AGU Fall Meeting, 2006. San Francisco, California. Marra, John, J., Uday S. Kari, and Stuart A. Weinstein (in press). A Tsunami Detection and Warning-focused Sea Level Station Metadata Web Service. IUGG XXIV, July 2-13, 2007. Perugia, Italy.

XCEDE: An Extensible Schema For Biomedical Data

PubMed Central

Gadde, Syam; Aucoin, Nicole; Grethe, Jeffrey S.; Keator, David B.; Marcus, Daniel S.; Pieper, Steve

2013-01-01

The XCEDE (XML-based Clinical and Experimental Data Exchange) XML schema, developed by members of the BIRN (Biomedical Informatics Research Network), provides an extensive metadata hierarchy for storing, describing and documenting the data generated by scientific studies. Currently at version 2.0, the XCEDE schema serves as a specification for the exchange of scientific data between databases, analysis tools, and web services. It provides a structured metadata hierarchy, storing information relevant to various aspects of an experiment (project, subject, protocol, etc.). Each hierarchy level also provides for the storage of data provenance information allowing for a traceable record of processing and/or changes to the underlying data. The schema is extensible to support the needs of various data modalities and to express types of data not originally envisioned by the developers. The latest version of the XCEDE schema and manual are available from http://www.xcede.org/ PMID:21479735

A publication database for optical long baseline interferometry

NASA Astrophysics Data System (ADS)

Malbet, Fabien; Mella, Guillaume; Lawson, Peter; Taillifet, Esther; Lafrasse, Sylvain

2010-07-01

Optical long baseline interferometry is a technique that has generated almost 850 refereed papers to date. The targets span a large variety of objects from planetary systems to extragalactic studies and all branches of stellar physics. We have created a database hosted by the JMMC and connected to the Optical Long Baseline Interferometry Newsletter (OLBIN) web site using MySQL and a collection of XML or PHP scripts in order to store and classify these publications. Each entry is defined by its ADS bibcode, includes basic ADS informations and metadata. The metadata are specified by tags sorted in categories: interferometric facilities, instrumentation, wavelength of operation, spectral resolution, type of measurement, target type, and paper category, for example. The whole OLBIN publication list has been processed and we present how the database is organized and can be accessed. We use this tool to generate statistical plots of interest for the community in optical long baseline interferometry.

GEOmetadb: powerful alternative search engine for the Gene Expression Omnibus

PubMed Central

Zhu, Yuelin; Davis, Sean; Stephens, Robert; Meltzer, Paul S.; Chen, Yidong

2008-01-01

The NCBI Gene Expression Omnibus (GEO) represents the largest public repository of microarray data. However, finding data in GEO can be challenging. We have developed GEOmetadb in an attempt to make querying the GEO metadata both easier and more powerful. All GEO metadata records as well as the relationships between them are parsed and stored in a local MySQL database. A powerful, flexible web search interface with several convenient utilities provides query capabilities not available via NCBI tools. In addition, a Bioconductor package, GEOmetadb that utilizes a SQLite export of the entire GEOmetadb database is also available, rendering the entire GEO database accessible with full power of SQL-based queries from within R. Availability: The web interface and SQLite databases available at http://gbnci.abcc.ncifcrf.gov/geo/. The Bioconductor package is available via the Bioconductor project. The corresponding MATLAB implementation is also available at the same website. Contact: yidong@mail.nih.gov PMID:18842599

Managing Complex Change in Clinical Study Metadata

PubMed Central

Brandt, Cynthia A.; Gadagkar, Rohit; Rodriguez, Cesar; Nadkarni, Prakash M.

2004-01-01

In highly functional metadata-driven software, the interrelationships within the metadata become complex, and maintenance becomes challenging. We describe an approach to metadata management that uses a knowledge-base subschema to store centralized information about metadata dependencies and use cases involving specific types of metadata modification. Our system borrows ideas from production-rule systems in that some of this information is a high-level specification that is interpreted and executed dynamically by a middleware engine. Our approach is implemented in TrialDB, a generic clinical study data management system. We review approaches that have been used for metadata management in other contexts and describe the features, capabilities, and limitations of our system. PMID:15187070

A Digital Broadcast Item (DBI) enabling metadata repository for digital, interactive television (digiTV) feedback channel networks

NASA Astrophysics Data System (ADS)

Lugmayr, Artur R.; Mailaparampil, Anurag; Tico, Florina; Kalli, Seppo; Creutzburg, Reiner

2003-01-01

Digital television (digiTV) is an additional multimedia environment, where metadata is one key element for the description of arbitrary content. This implies adequate structures for content description, which is provided by XML metadata schemes (e.g. MPEG-7, MPEG-21). Content and metadata management is the task of a multimedia repository, from which digiTV clients - equipped with an Internet connection - can access rich additional multimedia types over an "All-HTTP" protocol layer. Within this research work, we focus on conceptual design issues of a metadata repository for the storage of metadata, accessible from the feedback channel of a local set-top box. Our concept describes the whole heterogeneous life-cycle chain of XML metadata from the service provider to the digiTV equipment, device independent representation of content, accessing and querying the metadata repository, management of metadata related to digiTV, and interconnection of basic system components (http front-end, relational database system, and servlet container). We present our conceptual test configuration of a metadata repository that is aimed at a real-world deployment, done within the scope of the future interaction (fiTV) project at the Digital Media Institute (DMI) Tampere (www.futureinteraction.tv).

Improving Access to NASA Earth Science Data through Collaborative Metadata Curation

NASA Astrophysics Data System (ADS)

Sisco, A. W.; Bugbee, K.; Shum, D.; Baynes, K.; Dixon, V.; Ramachandran, R.

2017-12-01

The NASA-developed Common Metadata Repository (CMR) is a high-performance metadata system that currently catalogs over 375 million Earth science metadata records. It serves as the authoritative metadata management system of NASA's Earth Observing System Data and Information System (EOSDIS), enabling NASA Earth science data to be discovered and accessed by a worldwide user community. The size of the EOSDIS data archive is steadily increasing, and the ability to manage and query this archive depends on the input of high quality metadata to the CMR. Metadata that does not provide adequate descriptive information diminishes the CMR's ability to effectively find and serve data to users. To address this issue, an innovative and collaborative review process is underway to systematically improve the completeness, consistency, and accuracy of metadata for approximately 7,000 data sets archived by NASA's twelve EOSDIS data centers, or Distributed Active Archive Centers (DAACs). The process involves automated and manual metadata assessment of both collection and granule records by a team of Earth science data specialists at NASA Marshall Space Flight Center. The team communicates results to DAAC personnel, who then make revisions and reingest improved metadata into the CMR. Implementation of this process relies on a network of interdisciplinary collaborators leveraging a variety of communication platforms and long-range planning strategies. Curating metadata at this scale and resolving metadata issues through community consensus improves the CMR's ability to serve current and future users and also introduces best practices for stewarding the next generation of Earth Observing System data. This presentation will detail the metadata curation process, its outcomes thus far, and also share the status of ongoing curation activities.

Arc-An OAI Service Provider for Digital Library Federation; Kepler-An OAI Data/Service Provider for the Individual; Information Objects and Rights Management: A Mediation-Based Approach to DRM Interoperability; Automated Name Authority Control and Enhanced Searching in the Levy Collection; Renardus Project Developments and the Wider Digital Library Context.

ERIC Educational Resources Information Center

Liu, Xiaoming; Maly, Kurt; Zubair, Mohammad; Nelson, Michael L.; Erickson, John S.; DiLauro, Tim; Choudhury, G. Sayeed; Patton, Mark; Warner, James W.; Brown, Elizabeth W.; Heery, Rachel; Carpenter, Leona; Day, Michael

2001-01-01

Includes five articles that discuss the OAI (Open Archive Initiative), an interface between data providers and service providers; information objects and digital rights management interoperability; digitizing library collections, including automated name authority control, metadata, and text searching engines; and building digital library services…

Automatic Inference of Cryptographic Key Length Based on Analysis of Proof Tightness

DTIC Science & Technology

2016-06-01

within an attack tree structure, then expand attack tree methodology to include cryptographic reductions. We then provide the algorithms for...maintaining and automatically reasoning about these expanded attack trees . We provide a software tool that utilizes machine-readable proof and attack metadata...and the attack tree methodology to provide rapid and precise answers regarding security parameters and effective security. This eliminates the need

A Study on the Use of a Metadata Schema for Characterizing School Education STEM Lessons Plans by STEM Teachers

ERIC Educational Resources Information Center

Zervas, Panagiotis; Tsourlidaki, Eleftheria; Cao, Yiwei; Sotiriou, Sofoklis; Sampson, Demetrios G.; Faltin, Nils

2016-01-01

Online labs (OLs) constitute digital educational tools which can have a significant role in supporting science, technology, engineering and mathematics (STEM) teachers in their daily teaching practice. Designing STEM lessons supported by specific OLs is a challenging task and thus, it is useful for STEM teachers to be able to share their lesson…

Improving Data Discovery, Access, and Analysis to More Than Three Decades of Oceanographic and Geomorphologic Observations

NASA Astrophysics Data System (ADS)

Forte, M.; Hesser, T.; Knee, K.; Ingram, I.; Hathaway, K. K.; Brodie, K. L.; Spore, N.; Bird, A.; Fratantonio, R.; Dopsovic, R.; Keith, A.; Gadomski, K.

2016-02-01

The U.S. Army Engineer Research and Development Center's (USACE ERDC) Coastal and Hydraulics Laboratory (CHL) Coastal Observations and Analysis Branch (COAB) Measurements Program has a 35-year record of coastal observations. These datasets include oceanographic point source measurements, Real-Time Kinematic (RTK) GPS bathymetry surveys, and remote sensing data from both the Field Research Facility (FRF) in Duck, NC and from other project and experiment sites around the nation. The data has been used to support a variety of USACE mission areas, including coastal wave model development, beach and bar response, coastal project design, coastal storm surge, and other coastal hazard investigations. Furthermore these data have been widely used by a number of federal and state agencies, academic institutions, and private industries in hundreds of scientific and engineering investigations, publications, conference presentations and model advancement studies. A limiting factor to the use of FRF data has been rapid, reliable access and publicly available metadata for each data type. The addition of web tools, accessible data files, and well-documented metadata will open the door to much future collaboration. With the help of industry partner RPS ASA and the U.S. Army Corps of Engineers Mobile District Spatial Data Branch, a Data Integration Framework (DIF) was developed. The DIF represents a combination of processes, standards, people, and tools used to transform disconnected enterprise data into useful, easily accessible information for analysis and reporting. A front-end data portal connects the user to the framework that integrates both oceanographic observation and geomorphology measurements using a combination of ESRI and open-source technology while providing a seamless data discovery, access, and analysis experience to the user. The user interface was built with ESRI's JavaScript API and all project metadata is managed using Geoportal. The geomorphology data is made available through ArcGIS Server, while the oceanographic data sets have been formatted to netCDF4 and made available through a THREDDS server. Additional web tools run alongside the THREDDS server to provide rapid statistical calculations and plotting, allowing for user defined data access and visualization.

Empowering file-based radio production through media asset management systems

NASA Astrophysics Data System (ADS)

Muylaert, Bjorn; Beckers, Tom

2006-10-01

In recent years, IT-based production and archiving of media has matured to a level which enables broadcasters to switch over from tape- or CD-based to file-based workflows for the production of their radio and television programs. This technology is essential for the future of broadcasters as it provides the flexibility and speed of execution the customer demands by enabling, among others, concurrent access and production, faster than real-time ingest, edit during ingest, centrally managed annotation and quality preservation of media. In terms of automation of program production, the radio department is the most advanced within the VRT, the Flemish broadcaster. Since a couple of years ago, the radio department has been working with digital equipment and producing its programs mainly on standard IT equipment. Historically, the shift from analogue to digital based production has been a step by step process initiated and coordinated by each radio station separately, resulting in a multitude of tools and metadata collections, some of them developed in-house, lacking integration. To make matters worse, each of those stations adopted a slightly different production methodology. The planned introduction of a company-wide Media Asset Management System allows a coordinated overhaul to a unified production architecture. Benefits include the centralized ingest and annotation of audio material and the uniform, integrated (in terms of IT infrastructure) workflow model. Needless to say, the ingest strategy, metadata management and integration with radio production systems play a major role in the level of success of any improvement effort. This paper presents a data model for audio-specific concepts relevant to radio production. It includes an investigation of ingest techniques and strategies. Cooperation with external, professional production tools is demonstrated through a use-case scenario: the integration of an existing, multi-track editing tool with a commercially available Media Asset Management System. This will enable an uncomplicated production chain, with a recognizable look and feel for all system users, regardless of their affiliated radio station, as well as central retrieval and storage of information and metadata.

QualityML: a dictionary for quality metadata encoding

NASA Astrophysics Data System (ADS)

Ninyerola, Miquel; Sevillano, Eva; Serral, Ivette; Pons, Xavier; Zabala, Alaitz; Bastin, Lucy; Masó, Joan

2014-05-01

The scenario of rapidly growing geodata catalogues requires tools focused on facilitate users the choice of products. Having quality fields populated in metadata allow the users to rank and then select the best fit-for-purpose products. In this direction, we have developed the QualityML (http://qualityml.geoviqua.org), a dictionary that contains hierarchically structured concepts to precisely define and relate quality levels: from quality classes to quality measurements. Generically, a quality element is the path that goes from the higher level (quality class) to the lowest levels (statistics or quality metrics). This path is used to encode quality of datasets in the corresponding metadata schemas. The benefits of having encoded quality, in the case of data producers, are related with improvements in their product discovery and better transmission of their characteristics. In the case of data users, particularly decision-makers, they would find quality and uncertainty measures to take the best decisions as well as perform dataset intercomparison. Also it allows other components (such as visualization, discovery, or comparison tools) to be quality-aware and interoperable. On one hand, the QualityML is a profile of the ISO geospatial metadata standards providing a set of rules for precisely documenting quality indicator parameters that is structured in 6 levels. On the other hand, QualityML includes semantics and vocabularies for the quality concepts. Whenever possible, if uses statistic expressions from the UncertML dictionary (http://www.uncertml.org) encoding. However it also extends UncertML to provide list of alternative metrics that are commonly used to quantify quality. A specific example, based on a temperature dataset, is shown below. The annual mean temperature map has been validated with independent in-situ measurements to obtain a global error of 0.5 ° C. Level 0: Quality class (e.g., Thematic accuracy) Level 1: Quality indicator (e.g., Quantitative attribute correctness) Level 2: Measurement field (e.g., DifferentialErrors1D) Level 3: Statistic or Metric (e.g., Half-lengthConfidenceInterval) Level 4: Units (e.g. Celsius degrees) Level 5: Value (e.g.0.5) Level 6: Specifications. Additional information on how the measurement took place, citation of the reference data, the traceability of the process and a publication describing the validation process encoded using new 19157 elements or the GeoViQua (http://www.geoviqua.org) Quality Model (PQM-UQM) extensions to the ISO models. Finally, keep in mind, that QualityML is not just suitable for encoding dataset level but also considers pixel and object level uncertainties. This is done by link the metadata quality descriptions with layers representing not just the data but the uncertainty values associated with each geospatial element.

New Solutions for Enabling Discovery of User-Centric Virtual Data Products in NASA's Common Metadata Repository

NASA Astrophysics Data System (ADS)

Pilone, D.; Gilman, J.; Baynes, K.; Shum, D.

2015-12-01

This talk introduces a new NASA Earth Observing System Data and Information System (EOSDIS) capability to automatically generate and maintain derived, Virtual Product information allowing DAACs and Data Providers to create tailored and more discoverable variations of their products. After this talk the audience will be aware of the new EOSDIS Virtual Product capability, applications of it, and how to take advantage of it. Much of the data made available in the EOSDIS are organized for generation and archival rather than for discovery and use. The EOSDIS Common Metadata Repository (CMR) is launching a new capability providing automated generation and maintenance of user-oriented Virtual Product information. DAACs can easily surface variations on established data products tailored to specific uses cases and users, leveraging DAAC exposed services such as custom ordering or access services like OPeNDAP for on-demand product generation and distribution. Virtual Data Products enjoy support for spatial and temporal information, keyword discovery, association with imagery, and are fully discoverable by tools such as NASA Earthdata Search, Worldview, and Reverb. Virtual Product generation has applicability across many use cases: - Describing derived products such as Surface Kinetic Temperature information (AST_08) from source products (ASTER L1A) - Providing streamlined access to data products (e.g. AIRS) containing many (>800) data variables covering an enormous variety of physical measurements - Attaching additional EOSDIS offerings such as Visual Metadata, external services, and documentation metadata - Publishing alternate formats for a product (e.g. netCDF for HDF products) with the actual conversion happening on request - Publishing granules to be modified by on-the-fly services, like GES-DISC's Data Quality Screening Service - Publishing "bundled" products where granules from one product correspond to granules from one or more other related products

Metadata mapping and reuse in caBIG™

PubMed Central

Kunz, Isaac; Lin, Ming-Chin; Frey, Lewis

2009-01-01

Background This paper proposes that interoperability across biomedical databases can be improved by utilizing a repository of Common Data Elements (CDEs), UML model class-attributes and simple lexical algorithms to facilitate the building domain models. This is examined in the context of an existing system, the National Cancer Institute (NCI)'s cancer Biomedical Informatics Grid (caBIG™). The goal is to demonstrate the deployment of open source tools that can be used to effectively map models and enable the reuse of existing information objects and CDEs in the development of new models for translational research applications. This effort is intended to help developers reuse appropriate CDEs to enable interoperability of their systems when developing within the caBIG™ framework or other frameworks that use metadata repositories. Results The Dice (di-grams) and Dynamic algorithms are compared and both algorithms have similar performance matching UML model class-attributes to CDE class object-property pairs. With algorithms used, the baselines for automatically finding the matches are reasonable for the data models examined. It suggests that automatic mapping of UML models and CDEs is feasible within the caBIG™ framework and potentially any framework that uses a metadata repository. Conclusion This work opens up the possibility of using mapping algorithms to reduce cost and time required to map local data models to a reference data model such as those used within caBIG™. This effort contributes to facilitating the development of interoperable systems within caBIG™ as well as other metadata frameworks. Such efforts are critical to address the need to develop systems to handle enormous amounts of diverse data that can be leveraged from new biomedical methodologies. PMID:19208192

Reviving legacy clay mineralogy data and metadata through the IEDA-CCNY Data Internship Program

NASA Astrophysics Data System (ADS)

Palumbo, R. V.; Randel, C.; Ismail, A.; Block, K. A.; Cai, Y.; Carter, M.; Hemming, S. R.; Lehnert, K.

2016-12-01

Reconstruction of past climate and ocean circulation using ocean sediment cores relies on the use of multiple climate proxies measured on well-studied cores. Preserving all the information collected on a sediment core is crucial for the success of future studies using these unique and important samples. Clay mineralogy is a powerful tool to study weathering processes and sedimentary provenance. In his pioneering dissertation, Pierre Biscaye (1964, Yale University) established the X-Ray Diffraction (XRD) method for quantitative clay mineralogy analyses in ocean sediments and presented data for 500 core-top samples throughout the Atlantic Ocean and its neighboring seas. Unfortunately, the data only exists in analog format, which has discouraged scientists from reusing the data, apart from replication of the published maps. Archiving and preserving this dataset and making it publicly available in a digital format, linked with the metadata from the core repository will allow the scientific community to use these data to generate new findings. Under the supervision of Sidney Hemming and members of the Interdisciplinary Earth Data Alliance (IEDA) team, IEDA-CCNY interns digitized the data and metadata from Biscaye's dissertation and linked them with additional sample metadata using IGSN (International Geo-Sample Number). After compilation and proper documentation of the dataset, it was published in the EarthChem Library where the dataset will be openly accessible, and citable with a persistent DOI (Digital Object Identifier). During this internship, the students read peer-reviewed articles, interacted with active scientists in the field and acquired knowledge about XRD methods and the data generated, as well as its applications. They also learned about existing and emerging best practices in data publication and preservation. Data rescue projects are a fun and interactive way for students to become engaged in the field.

A general concept for consistent documentation of computational analyses

PubMed Central

Müller, Fabian; Nordström, Karl; Lengauer, Thomas; Schulz, Marcel H.

2015-01-01

The ever-growing amount of data in the field of life sciences demands standardized ways of high-throughput computational analysis. This standardization requires a thorough documentation of each step in the computational analysis to enable researchers to understand and reproduce the results. However, due to the heterogeneity in software setups and the high rate of change during tool development, reproducibility is hard to achieve. One reason is that there is no common agreement in the research community on how to document computational studies. In many cases, simple flat files or other unstructured text documents are provided by researchers as documentation, which are often missing software dependencies, versions and sufficient documentation to understand the workflow and parameter settings. As a solution we suggest a simple and modest approach for documenting and verifying computational analysis pipelines. We propose a two-part scheme that defines a computational analysis using a Process and an Analysis metadata document, which jointly describe all necessary details to reproduce the results. In this design we separate the metadata specifying the process from the metadata describing an actual analysis run, thereby reducing the effort of manual documentation to an absolute minimum. Our approach is independent of a specific software environment, results in human readable XML documents that can easily be shared with other researchers and allows an automated validation to ensure consistency of the metadata. Because our approach has been designed with little to no assumptions concerning the workflow of an analysis, we expect it to be applicable in a wide range of computational research fields. Database URL: http://deep.mpi-inf.mpg.de/DAC/cmds/pub/pyvalid.zip PMID:26055099

The Computational Infrastructure for Geodynamics: An Example of Software Curation and Citation in the Geodynamics Community

NASA Astrophysics Data System (ADS)

Hwang, L.; Kellogg, L. H.

2017-12-01

Curation of software promotes discoverability and accessibility and works hand in hand with scholarly citation to ascribe value to, and provide recognition for software development. To meet this challenge, the Computational Infrastructure for Geodynamics (CIG) maintains a community repository built on custom and open tools to promote discovery, access, identification, credit, and provenance of research software for the geodynamics community. CIG (geodynamics.org) originated from recognition of the tremendous effort required to develop sound software and the need to reduce duplication of effort and to sustain community codes. CIG curates software across 6 domains and has developed and follows software best practices that include establishing test cases, documentation, and a citable publication for each software package. CIG software landing web pages provide access to current and past releases; many are also accessible through the CIG community repository on github. CIG has now developed abc - attribution builder for citation to enable software users to give credit to software developers. abc uses zenodo as an archive and as the mechanism to obtain a unique identifier (DOI) for scientific software. To assemble the metadata, we searched the software's documentation and research publications and then requested the primary developers to verify. In this process, we have learned that each development community approaches software attribution differently. The metadata gathered is based on guidelines established by groups such as FORCE11 and OntoSoft. The rollout of abc is gradual as developers are forward-looking, rarely willing to go back and archive prior releases in zenodo. Going forward all actively developed packages will utilize the zenodo and github integration to automate the archival process when a new release is issued. How to handle legacy software, multi-authored libraries, and assigning roles to software remain open issues.

[Construction of chemical information database based on optical structure recognition technique].

PubMed

Lv, C Y; Li, M N; Zhang, L R; Liu, Z M

2018-04-18

To create a protocol that could be used to construct chemical information database from scientific literature quickly and automatically. Scientific literature, patents and technical reports from different chemical disciplines were collected and stored in PDF format as fundamental datasets. Chemical structures were transformed from published documents and images to machine-readable data by using the name conversion technology and optical structure recognition tool CLiDE. In the process of molecular structure information extraction, Markush structures were enumerated into well-defined monomer molecules by means of QueryTools in molecule editor ChemDraw. Document management software EndNote X8 was applied to acquire bibliographical references involving title, author, journal and year of publication. Text mining toolkit ChemDataExtractor was adopted to retrieve information that could be used to populate structured chemical database from figures, tables, and textual paragraphs. After this step, detailed manual revision and annotation were conducted in order to ensure the accuracy and completeness of the data. In addition to the literature data, computing simulation platform Pipeline Pilot 7.5 was utilized to calculate the physical and chemical properties and predict molecular attributes. Furthermore, open database ChEMBL was linked to fetch known bioactivities, such as indications and targets. After information extraction and data expansion, five separate metadata files were generated, including molecular structure data file, molecular information, bibliographical references, predictable attributes and known bioactivities. Canonical simplified molecular input line entry specification as primary key, metadata files were associated through common key nodes including molecular number and PDF number to construct an integrated chemical information database. A reasonable construction protocol of chemical information database was created successfully. A total of 174 research articles and 25 reviews published in Marine Drugs from January 2015 to June 2016 collected as essential data source, and an elementary marine natural product database named PKU-MNPD was built in accordance with this protocol, which contained 3 262 molecules and 19 821 records. This data aggregation protocol is of great help for the chemical information database construction in accuracy, comprehensiveness and efficiency based on original documents. The structured chemical information database can facilitate the access to medical intelligence and accelerate the transformation of scientific research achievements.

USGIN ISO metadata profile

NASA Astrophysics Data System (ADS)

Richard, S. M.

2011-12-01

The USGIN project has drafted and is using a specification for use of ISO 19115/19/39 metadata, recommendations for simple metadata content, and a proposal for a URI scheme to identify resources using resolvable http URI's(see http://lab.usgin.org/usgin-profiles). The principal target use case is a catalog in which resources can be registered and described by data providers for discovery by users. We are currently using the ESRI Geoportal (Open Source), with configuration files for the USGIN profile. The metadata offered by the catalog must provide sufficient content to guide search engines to locate requested resources, to describe the resource content, provenance, and quality so users can determine if the resource will serve for intended usage, and finally to enable human users and sofware clients to obtain or access the resource. In order to achieve an operational federated catalog system, provisions in the ISO specification must be restricted and usage clarified to reduce the heterogeneity of 'standard' metadata and service implementations such that a single client can search against different catalogs, and the metadata returned by catalogs can be parsed reliably to locate required information. Usage of the complex ISO 19139 XML schema allows for a great deal of structured metadata content, but the heterogenity in approaches to content encoding has hampered development of sophisticated client software that can take advantage of the rich metadata; the lack of such clients in turn reduces motivation for metadata producers to produce content-rich metadata. If the only significant use of the detailed, structured metadata is to format into text for people to read, then the detailed information could be put in free text elements and be just as useful. In order for complex metadata encoding and content to be useful, there must be clear and unambiguous conventions on the encoding that are utilized by the community that wishes to take advantage of advanced metadata content. The use cases for the detailed content must be well understood, and the degree of metadata complexity should be determined by requirements for those use cases. The ISO standard provides sufficient flexibility that relatively simple metadata records can be created that will serve for text-indexed search/discovery, resource evaluation by a user reading text content from the metadata, and access to the resource via http, ftp, or well-known service protocols (e.g. Thredds; OGC WMS, WFS, WCS).

An Approach to Information Management for AIR7000 with Metadata and Ontologies

DTIC Science & Technology

2009-10-01

metadata. We then propose an approach based on Semantic Technologies including the Resource Description Framework (RDF) and Upper Ontologies, for the...mandating specific metadata schemas can result in interoperability problems. For example, many standards within the ADO mandate the use of XML for metadata...such problems, we propose an archi- tecture in which different metadata schemes can inter operate. By using RDF (Resource Description Framework ) as a

Predicting structured metadata from unstructured metadata

PubMed Central

Posch, Lisa; Panahiazar, Maryam; Dumontier, Michel; Gevaert, Olivier

2016-01-01

Enormous amounts of biomedical data have been and are being produced by investigators all over the world. However, one crucial and limiting factor in data reuse is accurate, structured and complete description of the data or data about the data—defined as metadata. We propose a framework to predict structured metadata terms from unstructured metadata for improving quality and quantity of metadata, using the Gene Expression Omnibus (GEO) microarray database. Our framework consists of classifiers trained using term frequency-inverse document frequency (TF-IDF) features and a second approach based on topics modeled using a Latent Dirichlet Allocation model (LDA) to reduce the dimensionality of the unstructured data. Our results on the GEO database show that structured metadata terms can be the most accurately predicted using the TF-IDF approach followed by LDA both outperforming the majority vote baseline. While some accuracy is lost by the dimensionality reduction of LDA, the difference is small for elements with few possible values, and there is a large improvement over the majority classifier baseline. Overall this is a promising approach for metadata prediction that is likely to be applicable to other datasets and has implications for researchers interested in biomedical metadata curation and metadata prediction. Database URL: http://www.yeastgenome.org/ PMID:28637268

Pragmatic Metadata Management for Integration into Multiple Spatial Data Infrastructure Systems and Platforms

NASA Astrophysics Data System (ADS)

Benedict, K. K.; Scott, S.

2013-12-01

While there has been a convergence towards a limited number of standards for representing knowledge (metadata) about geospatial (and other) data objects and collections, there exist a variety of community conventions around the specific use of those standards and within specific data discovery and access systems. This combination of limited (but multiple) standards and conventions creates a challenge for system developers that aspire to participate in multiple data infrastrucutres, each of which may use a different combination of standards and conventions. While Extensible Markup Language (XML) is a shared standard for encoding most metadata, traditional direct XML transformations (XSLT) from one standard to another often result in an imperfect transfer of information due to incomplete mapping from one standard's content model to another. This paper presents the work at the University of New Mexico's Earth Data Analysis Center (EDAC) in which a unified data and metadata management system has been developed in support of the storage, discovery and access of heterogeneous data products. This system, the Geographic Storage, Transformation and Retrieval Engine (GSTORE) platform has adopted a polyglot database model in which a combination of relational and document-based databases are used to store both data and metadata, with some metadata stored in a custom XML schema designed as a superset of the requirements for multiple target metadata standards: ISO 19115-2/19139/19110/19119, FGCD CSDGM (both with and without remote sensing extensions) and Dublin Core. Metadata stored within this schema is complemented by additional service, format and publisher information that is dynamically "injected" into produced metadata documents when they are requested from the system. While mapping from the underlying common metadata schema is relatively straightforward, the generation of valid metadata within each target standard is necessary but not sufficient for integration into multiple data infrastructures, as has been demonstrated through EDAC's testing and deployment of metadata into multiple external systems: Data.Gov, the GEOSS Registry, the DataONE network, the DSpace based institutional repository at UNM and semantic mediation systems developed as part of the NASA ACCESS ELSeWEB project. Each of these systems requires valid metadata as a first step, but to make most effective use of the delivered metadata each also has a set of conventions that are specific to the system. This presentation will provide an overview of the underlying metadata management model, the processes and web services that have been developed to automatically generate metadata in a variety of standard formats and highlight some of the specific modifications made to the output metadata content to support the different conventions used by the multiple metadata integration endpoints.

Proceeding of the ACM/IEEE-CS Joint Conference on Digital Libraries (1st, Roanoke, Virginia, June 24-28, 2001).

ERIC Educational Resources Information Center

Association for Computing Machinery, New York, NY.

Papers in this Proceedings of the ACM/IEEE-CS Joint Conference on Digital Libraries (Roanoke, Virginia, June 24-28, 2001) discuss: automatic genre analysis; text categorization; automated name authority control; automatic event generation; linked active content; designing e-books for legal research; metadata harvesting; mapping the…

A Tsunami-Focused Tide Station Data Sharing Framework

NASA Astrophysics Data System (ADS)

Kari, U. S.; Marra, J. J.; Weinstein, S. A.

2006-12-01

The Indian Ocean Tsunami of 26 December 2004 made it clear that information about tide stations that could be used to support detection and warning (such as location, collection and transmission capabilities, operator identification) are insufficiently known or not readily accessible. Parties interested in addressing this problem united under the Pacific Region Data Integrated Data Enterprise (PRIDE), and in 2005 began a multiyear effort to develop a distributed metadata system describing tide stations starting with pilot activities in a regional framework and focusing on tsunami detection and warning systems being developed by various agencies. First, a plain semantic description of the tsunami-focused tide station metadata was developed. The semantic metadata description was, in turn, developed into a formal metadata schema championed by International Tsunami Information Centre (ITIC) as part of a larger effort to develop a prototype web service under the PRIDE program in 2005. Under the 2006 PRIDE program the formal metadata schema was then expanded to corral input parameters for the TideTool application used by Pacific Tsunami Warning Center (PTWC) to drill down into wave activity at a tide station that is located using a web service developed on this metadata schema. This effort contributed to formalization of web service dissemination of PTWC watch and warning tsunami bulletins. During this time, the data content and sharing issues embodied in this schema have been discussed at various forums. The result is that the various stakeholders have different data provider and user perspectives (semantic content) and also exchange formats (not limited to just XML). The challenge then, is not only to capture all data requirements, but also to have formal representation that is easily transformed into any specified format. The latest revision of the tide gauge schema (Version 0.3), begins to address this challenge. It encompasses a broader range of provider and user perspectives, such as station operators, warning system managers, disaster managers, other marine hazard warning systems (such as storm surges and sea level change monitoring and research. In the next revision(s), we hope to take into account various relevant standards, including specifically, the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) Framework, that will serve all prospective stakeholders in the most useful (extensible, scalable) manner. This is because Sensor ML has addressed many of the challenges we face already, through very useful fundamental modeling consideration and data types that are particular to sensors in general, with perhaps some extension needed for tide gauges. As a result of developing this schema, and associated client application architectures, we hope to have a much more distributed network of data providers, who are able to contribute to a global tide station metadata from the comfort of their own Information Technology (IT) departments.

Why can't I manage my digital images like MP3s? The evolution and intent of multimedia metadata

NASA Astrophysics Data System (ADS)

Goodrum, Abby; Howison, James

2005-01-01

This paper considers the deceptively simple question: Why can't digital images be managed in the simple and effective manner in which digital music files are managed? We make the case that the answer is different treatments of metadata in different domains with different goals. A central difference between the two formats stems from the fact that digital music metadata lookup services are collaborative and automate the movement from a digital file to the appropriate metadata, while image metadata services do not. To understand why this difference exists we examine the divergent evolution of metadata standards for digital music and digital images and observed that the processes differ in interesting ways according to their intent. Specifically music metadata was developed primarily for personal file management and community resource sharing, while the focus of image metadata has largely been on information retrieval. We argue that lessons from MP3 metadata can assist individuals facing their growing personal image management challenges. Our focus therefore is not on metadata for cultural heritage institutions or the publishing industry, it is limited to the personal libraries growing on our hard-drives. This bottom-up approach to file management combined with p2p distribution radically altered the music landscape. Might such an approach have a similar impact on image publishing? This paper outlines plans for improving the personal management of digital images-doing image metadata and file management the MP3 way-and considers the likelihood of success.

Why can't I manage my digital images like MP3s? The evolution and intent of multimedia metadata

NASA Astrophysics Data System (ADS)

Goodrum, Abby; Howison, James

2004-12-01

This paper considers the deceptively simple question: Why can"t digital images be managed in the simple and effective manner in which digital music files are managed? We make the case that the answer is different treatments of metadata in different domains with different goals. A central difference between the two formats stems from the fact that digital music metadata lookup services are collaborative and automate the movement from a digital file to the appropriate metadata, while image metadata services do not. To understand why this difference exists we examine the divergent evolution of metadata standards for digital music and digital images and observed that the processes differ in interesting ways according to their intent. Specifically music metadata was developed primarily for personal file management and community resource sharing, while the focus of image metadata has largely been on information retrieval. We argue that lessons from MP3 metadata can assist individuals facing their growing personal image management challenges. Our focus therefore is not on metadata for cultural heritage institutions or the publishing industry, it is limited to the personal libraries growing on our hard-drives. This bottom-up approach to file management combined with p2p distribution radically altered the music landscape. Might such an approach have a similar impact on image publishing? This paper outlines plans for improving the personal management of digital images-doing image metadata and file management the MP3 way-and considers the likelihood of success.

The Role of Metadata Standards in EOSDIS Search and Retrieval Applications

NASA Technical Reports Server (NTRS)

Pfister, Robin

1999-01-01

Metadata standards play a critical role in data search and retrieval systems. Metadata tie software to data so the data can be processed, stored, searched, retrieved and distributed. Without metadata these actions are not possible. The process of populating metadata to describe science data is an important service to the end user community so that a user who is unfamiliar with the data, can easily find and learn about a particular dataset before an order decision is made. Once a good set of standards are in place, the accuracy with which data search can be performed depends on the degree to which metadata standards are adhered during product definition. NASA's Earth Observing System Data and Information System (EOSDIS) provides examples of how metadata standards are used in data search and retrieval.

openPDS: protecting the privacy of metadata through SafeAnswers.

PubMed

de Montjoye, Yves-Alexandre; Shmueli, Erez; Wang, Samuel S; Pentland, Alex Sandy

2014-01-01

The rise of smartphones and web services made possible the large-scale collection of personal metadata. Information about individuals' location, phone call logs, or web-searches, is collected and used intensively by organizations and big data researchers. Metadata has however yet to realize its full potential. Privacy and legal concerns, as well as the lack of technical solutions for personal metadata management is preventing metadata from being shared and reconciled under the control of the individual. This lack of access and control is furthermore fueling growing concerns, as it prevents individuals from understanding and managing the risks associated with the collection and use of their data. Our contribution is two-fold: (1) we describe openPDS, a personal metadata management framework that allows individuals to collect, store, and give fine-grained access to their metadata to third parties. It has been implemented in two field studies; (2) we introduce and analyze SafeAnswers, a new and practical way of protecting the privacy of metadata at an individual level. SafeAnswers turns a hard anonymization problem into a more tractable security one. It allows services to ask questions whose answers are calculated against the metadata instead of trying to anonymize individuals' metadata. The dimensionality of the data shared with the services is reduced from high-dimensional metadata to low-dimensional answers that are less likely to be re-identifiable and to contain sensitive information. These answers can then be directly shared individually or in aggregate. openPDS and SafeAnswers provide a new way of dynamically protecting personal metadata, thereby supporting the creation of smart data-driven services and data science research.

openPDS: Protecting the Privacy of Metadata through SafeAnswers

PubMed Central

de Montjoye, Yves-Alexandre; Shmueli, Erez; Wang, Samuel S.; Pentland, Alex Sandy

2014-01-01

The rise of smartphones and web services made possible the large-scale collection of personal metadata. Information about individuals' location, phone call logs, or web-searches, is collected and used intensively by organizations and big data researchers. Metadata has however yet to realize its full potential. Privacy and legal concerns, as well as the lack of technical solutions for personal metadata management is preventing metadata from being shared and reconciled under the control of the individual. This lack of access and control is furthermore fueling growing concerns, as it prevents individuals from understanding and managing the risks associated with the collection and use of their data. Our contribution is two-fold: (1) we describe openPDS, a personal metadata management framework that allows individuals to collect, store, and give fine-grained access to their metadata to third parties. It has been implemented in two field studies; (2) we introduce and analyze SafeAnswers, a new and practical way of protecting the privacy of metadata at an individual level. SafeAnswers turns a hard anonymization problem into a more tractable security one. It allows services to ask questions whose answers are calculated against the metadata instead of trying to anonymize individuals' metadata. The dimensionality of the data shared with the services is reduced from high-dimensional metadata to low-dimensional answers that are less likely to be re-identifiable and to contain sensitive information. These answers can then be directly shared individually or in aggregate. openPDS and SafeAnswers provide a new way of dynamically protecting personal metadata, thereby supporting the creation of smart data-driven services and data science research. PMID:25007320

Progress in defining a standard for file-level metadata

NASA Technical Reports Server (NTRS)

Williams, Joel; Kobler, Ben

1996-01-01

In the following narrative, metadata required to locate a file on tape or collection of tapes will be referred to as file-level metadata. This paper discribes the rationale for and the history of the effort to define a standard for this metadata.

Achieving interoperability for metadata registries using comparative object modeling.

PubMed

Park, Yu Rang; Kim, Ju Han

2010-01-01

Achieving data interoperability between organizations relies upon agreed meaning and representation (metadata) of data. For managing and registering metadata, many organizations have built metadata registries (MDRs) in various domains based on international standard for MDR framework, ISO/IEC 11179. Following this trend, two pubic MDRs in biomedical domain have been created, United States Health Information Knowledgebase (USHIK) and cancer Data Standards Registry and Repository (caDSR), from U.S. Department of Health & Human Services and National Cancer Institute (NCI), respectively. Most MDRs are implemented with indiscriminate extending for satisfying organization-specific needs and solving semantic and structural limitation of ISO/IEC 11179. As a result it is difficult to address interoperability among multiple MDRs. In this paper, we propose an integrated metadata object model for achieving interoperability among multiple MDRs. To evaluate this model, we developed an XML Schema Definition (XSD)-based metadata exchange format. We created an XSD-based metadata exporter, supporting both the integrated metadata object model and organization-specific MDR formats.

Request queues for interactive clients in a shared file system of a parallel computing system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bent, John M.; Faibish, Sorin

Interactive requests are processed from users of log-in nodes. A metadata server node is provided for use in a file system shared by one or more interactive nodes and one or more batch nodes. The interactive nodes comprise interactive clients to execute interactive tasks and the batch nodes execute batch jobs for one or more batch clients. The metadata server node comprises a virtual machine monitor; an interactive client proxy to store metadata requests from the interactive clients in an interactive client queue; a batch client proxy to store metadata requests from the batch clients in a batch client queue;more » and a metadata server to store the metadata requests from the interactive client queue and the batch client queue in a metadata queue based on an allocation of resources by the virtual machine monitor. The metadata requests can be prioritized, for example, based on one or more of a predefined policy and predefined rules.« less

A future Outlook: Web based Simulation of Hydrodynamic models

NASA Astrophysics Data System (ADS)

Islam, A. S.; Piasecki, M.

2003-12-01

Despite recent advances to present simulation results as 3D graphs or animation contours, the modeling user community still faces some shortcomings when trying to move around and analyze data. Typical problems include the lack of common platforms with standard vocabulary to exchange simulation results from different numerical models, insufficient descriptions about data (metadata), lack of robust search and retrieval tools for data, and difficulties to reuse simulation domain knowledge. This research demonstrates how to create a shared simulation domain in the WWW and run a number of models through multi-user interfaces. Firstly, meta-datasets have been developed to describe hydrodynamic model data based on geographic metadata standard (ISO 19115) that has been extended to satisfy the need of the hydrodynamic modeling community. The Extended Markup Language (XML) is used to publish this metadata by the Resource Description Framework (RDF). Specific domain ontology for Web Based Simulation (WBS) has been developed to explicitly define vocabulary for the knowledge based simulation system. Subsequently, this knowledge based system is converted into an object model using Meta Object Family (MOF). The knowledge based system acts as a Meta model for the object oriented system, which aids in reusing the domain knowledge. Specific simulation software has been developed based on the object oriented model. Finally, all model data is stored in an object relational database. Database back-ends help store, retrieve and query information efficiently. This research uses open source software and technology such as Java Servlet and JSP, Apache web server, Tomcat Servlet Engine, PostgresSQL databases, Protégé ontology editor, RDQL and RQL for querying RDF in semantic level, Jena Java API for RDF. Also, we use international standards such as the ISO 19115 metadata standard, and specifications such as XML, RDF, OWL, XMI, and UML. The final web based simulation product is deployed as Web Archive (WAR) files which is platform and OS independent and can be used by Windows, UNIX, or Linux. Keywords: Apache, ISO 19115, Java Servlet, Jena, JSP, Metadata, MOF, Linux, Ontology, OWL, PostgresSQL, Protégé, RDF, RDQL, RQL, Tomcat, UML, UNIX, Windows, WAR, XML

Large-Scale Data Collection Metadata Management at the National Computation Infrastructure

NASA Astrophysics Data System (ADS)

Wang, J.; Evans, B. J. K.; Bastrakova, I.; Ryder, G.; Martin, J.; Duursma, D.; Gohar, K.; Mackey, T.; Paget, M.; Siddeswara, G.

2014-12-01

Data Collection management has become an essential activity at the National Computation Infrastructure (NCI) in Australia. NCI's partners (CSIRO, Bureau of Meteorology, Australian National University, and Geoscience Australia), supported by the Australian Government and Research Data Storage Infrastructure (RDSI), have established a national data resource that is co-located with high-performance computing. This paper addresses the metadata management of these data assets over their lifetime. NCI manages 36 data collections (10+ PB) categorised as earth system sciences, climate and weather model data assets and products, earth and marine observations and products, geosciences, terrestrial ecosystem, water management and hydrology, astronomy, social science and biosciences. The data is largely sourced from NCI partners, the custodians of many of the national scientific records, and major research community organisations. The data is made available in a HPC and data-intensive environment - a ~56000 core supercomputer, virtual labs on a 3000 core cloud system, and data services. By assembling these large national assets, new opportunities have arisen to harmonise the data collections, making a powerful cross-disciplinary resource.To support the overall management, a Data Management Plan (DMP) has been developed to record the workflows, procedures, the key contacts and responsibilities. The DMP has fields that can be exported to the ISO19115 schema and to the collection level catalogue of GeoNetwork. The subset or file level metadata catalogues are linked with the collection level through parent-child relationship definition using UUID. A number of tools have been developed that support interactive metadata management, bulk loading of data, and support for computational workflows or data pipelines. NCI creates persistent identifiers for each of the assets. The data collection is tracked over its lifetime, and the recognition of the data providers, data owners, data generators and data aggregators are updated. A Digital Object Identifier is assigned using the Australian National Data Service (ANDS). Once the data has been quality assured, a DOI is minted and the metadata record updated. NCI's data citation policy establishes the relationship between research outcomes, data providers, and the data.

IGSN e.V.: Registration and Identification Services for Physical Samples in the Digital Universe

NASA Astrophysics Data System (ADS)

Lehnert, K. A.; Klump, J.; Arko, R. A.; Bristol, S.; Buczkowski, B.; Chan, C.; Chan, S.; Conze, R.; Cox, S. J.; Habermann, T.; Hangsterfer, A.; Hsu, L.; Milan, A.; Miller, S. P.; Noren, A. J.; Richard, S. M.; Valentine, D. W.; Whitenack, T.; Wyborn, L. A.; Zaslavsky, I.

2011-12-01

The International Geo Sample Number (IGSN) is a unique identifier for samples and specimens collected from our natural environment. It was developed by the System for Earth Sample Registration SESAR to overcome the problem of ambiguous naming of samples that has limited the ability to share, link, and integrate data for samples across Geoscience data systems. Over the past 5 years, SESAR has made substantial progress in implementing the IGSN for sample and data management, working with Geoscience researchers, Geoinformatics specialists, and sample curators to establish metadata requirements, registration procedures, and best practices for the use of the IGSN. The IGSN is now recognized as the primary solution for sample identification and registration, and supported by a growing user community of investigators, repositories, science programs, and data systems. In order to advance broad disciplinary and international implementation of the IGSN, SESAR organized a meeting of international leaders in Geoscience informatics in 2011 to develop a consensus strategy for the long-term operations of the registry with approaches for sustainable operation, organizational structure, governance, and funding. The group endorsed an internationally unified approach for registration and discovery of physical specimens in the Geosciences, and refined the existing SESAR architecture to become a modular and scalable approach, separating the IGSN Registry from a central Sample Metadata Clearinghouse (SESAR), and introducing 'Local Registration Agents' that provide registration services to specific disciplinary or organizational communities, with tools for metadata submission and management, and metadata archiving. Development and implementation of the new IGSN architecture is underway with funding provided by the US NSF Office of International Science and Engineering. A formal governance structure is being established for the IGSN model, consisting of (a) an international not-for-profit organization, the IGSN e.V. (e.V. = 'Eingetragener Verein', legal status for a registered voluntary association in Germany), that defines the IGSN scope and syntax and maintains the IGSN Handle system, and (b) a Science Advisory Board that guides policies, technology, and best practices of the SESAR Sample Metadata Clearinghouse and Local Registration Agents. The IGSN e.V. is being incorporated in Germany at the GFZ Potsdam, a founding event is planned for the AGU Fall Meeting.

Catalog Federation and Interoperability for Geoinformatics

NASA Astrophysics Data System (ADS)

Memon, A.; Lin, K.; Baru, C.

2008-12-01

With the increasing proliferation of online resources in the geosciences, including data, tools, and software services, there is also a proliferation of catalogs containing metadata that describe these resources. To realize the vision articulated in the NSF Workshop on Building a National Geoinformatics System, March 2007-where a user can sit at a terminal and easily search, discover, integrate and use distributed geoscience resources-it will be essential that a search request be able to traverse these multiple metadata catalogs. In this paper, we describe our effort at prototyping catalog interoperability across multiple metadata catalogs. An example of a metadata catalog is the one employed in the GEON Project (www.geongrid.org). The central GEON catalog can be searched using spatial, temporal, and other metadata-based search criteria. The search can be invoked as a Web service and, therefore, can be imbedded in any software application. There has been a requirement from some of the GEON collaborators (for example, at the University of Hyderabad, India and the Navajo Technical College, New Mexico) to deploy their own catalogs, to store information about their resources locally, while they publish some of this information for broader access and use. Thus, a search must now be able to span multiple, independent GEON catalogs. Next, some of our collaborators-e.g. GEO Grid (Global Earth Observations Grid) in Japan-are implementing the Catalog Services for the Web (CS-W) standard for their catalog, thereby requiring the search to span across catalogs implemented using the CS-W standard as well. Finally, we have recently deployed a search service to access all EarthScope data products, which are distributed across organizations in Seattle, WA (IRIS), Boulder, CO (UNAVCO), and Potsdam, Germany (ICDP/GFZ). This service essentially implements a virtual catalog (the actual catalogs and data are stored at the remote locations). So, there is the need to incorporate such 3rd party searches within a broader search function, such as GEONsearch in the GEON Portal. We will discuss technical issues involved in designing and deploying such a multi-catalog search service in GEON.

The Global Genome Biodiversity Network (GGBN) Data Standard specification.

PubMed

Droege, G; Barker, K; Seberg, O; Coddington, J; Benson, E; Berendsohn, W G; Bunk, B; Butler, C; Cawsey, E M; Deck, J; Döring, M; Flemons, P; Gemeinholzer, B; Güntsch, A; Hollowell, T; Kelbert, P; Kostadinov, I; Kottmann, R; Lawlor, R T; Lyal, C; Mackenzie-Dodds, J; Meyer, C; Mulcahy, D; Nussbeck, S Y; O'Tuama, É; Orrell, T; Petersen, G; Robertson, T; Söhngen, C; Whitacre, J; Wieczorek, J; Yilmaz, P; Zetzsche, H; Zhang, Y; Zhou, X

2016-01-01

Genomic samples of non-model organisms are becoming increasingly important in a broad range of studies from developmental biology, biodiversity analyses, to conservation. Genomic sample definition, description, quality, voucher information and metadata all need to be digitized and disseminated across scientific communities. This information needs to be concise and consistent in today's ever-increasing bioinformatic era, for complementary data aggregators to easily map databases to one another. In order to facilitate exchange of information on genomic samples and their derived data, the Global Genome Biodiversity Network (GGBN) Data Standard is intended to provide a platform based on a documented agreement to promote the efficient sharing and usage of genomic sample material and associated specimen information in a consistent way. The new data standard presented here build upon existing standards commonly used within the community extending them with the capability to exchange data on tissue, environmental and DNA sample as well as sequences. The GGBN Data Standard will reveal and democratize the hidden contents of biodiversity biobanks, for the convenience of everyone in the wider biobanking community. Technical tools exist for data providers to easily map their databases to the standard.Database URL: http://terms.tdwg.org/wiki/GGBN_Data_Standard. © The Author(s) 2016. Published by Oxford University Press.

Making metadata usable in a multi-national research setting.

PubMed

Ellul, Claire; Foord, Joanna; Mooney, John

2013-11-01

SECOA (Solutions for Environmental Contrasts in Coastal Areas) is a multi-national research project examining the effects of human mobility on urban settlements in fragile coastal environments. This paper describes the setting up of a SECOA metadata repository for non-specialist researchers such as environmental scientists and tourism experts. Conflicting usability requirements of two groups - metadata creators and metadata users - are identified along with associated limitations of current metadata standards. A description is given of a configurable metadata system designed to grow as the project evolves. This work is of relevance for similar projects such as INSPIRE. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Image processing tool for automatic feature recognition and quantification

DOEpatents

Chen, Xing; Stoddard, Ryan J.

2017-05-02

A system for defining structures within an image is described. The system includes reading of an input file, preprocessing the input file while preserving metadata such as scale information and then detecting features of the input file. In one version the detection first uses an edge detector followed by identification of features using a Hough transform. The output of the process is identified elements within the image.

Data Recommender: An Alternative Way to Discover Open Scientific Datasets

NASA Astrophysics Data System (ADS)

Klump, J. F.; Devaraju, A.; Williams, G.; Hogan, D.; Davy, R.; Page, J.; Singh, D.; Peterson, N.

2017-12-01

Over the past few years, institutions and government agencies have adopted policies to openly release their data, which has resulted in huge amounts of open data becoming available on the web. When trying to discover the data, users face two challenges: an overload of choice and the limitations of the existing data search tools. On the one hand, there are too many datasets to choose from, and therefore, users need to spend considerable effort to find the datasets most relevant to their research. On the other hand, data portals commonly offer keyword and faceted search, which depend fully on the user queries to search and rank relevant datasets. Consequently, keyword and faceted search may return loosely related or irrelevant results, although the results may contain the same query. They may also return highly specific results that depend more on how well metadata was authored. They do not account well for variance in metadata due to variance in author styles and preferences. The top-ranked results may also come from the same data collection, and users are unlikely to discover new and interesting datasets. These search modes mainly suits users who can express their information needs in terms of the structure and terminology of the data portals, but may pose a challenge otherwise. The above challenges reflect that we need a solution that delivers the most relevant (i.e., similar and serendipitous) datasets to users, beyond the existing search functionalities on the portals. A recommender system is an information filtering system that presents users with relevant and interesting contents based on users' context and preferences. Delivering data recommendations to users can make data discovery easier, and as a result may enhance user engagement with the portal. We developed a hybrid data recommendation approach for the CSIRO Data Access Portal. The approach leverages existing recommendation techniques (e.g., content-based filtering and item co-occurrence) to produce similar and serendipitous data recommendations. It measures the relevance between datasets based on their properties, and search and download patterns. We evaluated the recommendation approach in a user study, and the obtained user judgments revealed the ability of the approach to accurately quantify the relevance of the datasets.

HomeBank: An Online Repository of Daylong Child-Centered Audio Recordings

PubMed Central

VanDam, Mark; Warlaumont, Anne S.; Bergelson, Elika; Cristia, Alejandrina; Soderstrom, Melanie; De Palma, Paul; MacWhinney, Brian

2017-01-01

HomeBank is introduced here. It is a public, permanent, extensible, online database of daylong audio recorded in naturalistic environments. HomeBank serves two primary purposes. First, it is a repository for raw audio and associated files: one database requires special permissions, and another redacted database allows unrestricted public access. Associated files include metadata such as participant demographics and clinical diagnostics, automated annotations, and human-generated transcriptions and annotations. Many recordings use the child-perspective LENA recorders (LENA Research Foundation, Boulder, Colorado, United States), but various recordings and metadata can be accommodated. The HomeBank database can have both vetted and unvetted recordings, with different levels of accessibility. Additionally, HomeBank is an open repository for processing and analysis tools for HomeBank or similar data sets. HomeBank is flexible for users and contributors, making primary data available to researchers, especially those in child development, linguistics, and audio engineering. HomeBank facilitates researchers’ access to large-scale data and tools, linking the acoustic, auditory, and linguistic characteristics of children’s environments with a variety of variables including socioeconomic status, family characteristics, language trajectories, and disorders. Automated processing applied to daylong home audio recordings is now becoming widely used in early intervention initiatives, helping parents to provide richer speech input to at-risk children. PMID:27111272

Data Curation for the Exploitation of Large Earth Observation Products Databases - The MEA system

NASA Astrophysics Data System (ADS)

Mantovani, Simone; Natali, Stefano; Barboni, Damiano; Cavicchi, Mario; Della Vecchia, Andrea

2014-05-01

National Space Agencies under the umbrella of the European Space Agency are performing a strong activity to handle and provide solutions to Big Data and related knowledge (metadata, software tools and services) management and exploitation. The continuously increasing amount of long-term and of historic data in EO facilities in the form of online datasets and archives, the incoming satellite observation platforms that will generate an impressive amount of new data and the new EU approach on the data distribution policy make necessary to address technologies for the long-term management of these data sets, including their consolidation, preservation, distribution, continuation and curation across multiple missions. The management of long EO data time series of continuing or historic missions - with more than 20 years of data available already today - requires technical solutions and technologies which differ considerably from the ones exploited by existing systems. Several tools, both open source and commercial, are already providing technologies to handle data and metadata preparation, access and visualization via OGC standard interfaces. This study aims at describing the Multi-sensor Evolution Analysis (MEA) system and the Data Curation concept as approached and implemented within the ASIM and EarthServer projects, funded by the European Space Agency and the European Commission, respectively.

Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools

PubMed Central

Sud, Manish; Fahy, Eoin; Cotter, Dawn; Azam, Kenan; Vadivelu, Ilango; Burant, Charles; Edison, Arthur; Fiehn, Oliver; Higashi, Richard; Nair, K. Sreekumaran; Sumner, Susan; Subramaniam, Shankar

2016-01-01

The Metabolomics Workbench, available at www.metabolomicsworkbench.org, is a public repository for metabolomics metadata and experimental data spanning various species and experimental platforms, metabolite standards, metabolite structures, protocols, tutorials, and training material and other educational resources. It provides a computational platform to integrate, analyze, track, deposit and disseminate large volumes of heterogeneous data from a wide variety of metabolomics studies including mass spectrometry (MS) and nuclear magnetic resonance spectrometry (NMR) data spanning over 20 different species covering all the major taxonomic categories including humans and other mammals, plants, insects, invertebrates and microorganisms. Additionally, a number of protocols are provided for a range of metabolite classes, sample types, and both MS and NMR-based studies, along with a metabolite structure database. The metabolites characterized in the studies available on the Metabolomics Workbench are linked to chemical structures in the metabolite structure database to facilitate comparative analysis across studies. The Metabolomics Workbench, part of the data coordinating effort of the National Institute of Health (NIH) Common Fund's Metabolomics Program, provides data from the Common Fund's Metabolomics Resource Cores, metabolite standards, and analysis tools to the wider metabolomics community and seeks data depositions from metabolomics researchers across the world. PMID:26467476

Inter-University Upper Atmosphere Global Observation Network (IUGONET) Metadata Database and Its Interoperability

NASA Astrophysics Data System (ADS)

Yatagai, A. I.; Iyemori, T.; Ritschel, B.; Koyama, Y.; Hori, T.; Abe, S.; Tanaka, Y.; Shinbori, A.; Umemura, N.; Sato, Y.; Yagi, M.; Ueno, S.; Hashiguchi, N. O.; Kaneda, N.; Belehaki, A.; Hapgood, M. A.

2013-12-01

The IUGONET is a Japanese program to build a metadata database for ground-based observations of the upper atmosphere [1]. The project began in 2009 with five Japanese institutions which archive data observed by radars, magnetometers, photometers, radio telescopes and helioscopes, and so on, at various altitudes from the Earth's surface to the Sun. Systems have been developed to allow searching of the above described metadata. We have been updating the system and adding new and updated metadata. The IUGONET development team adopted the SPASE metadata model [2] to describe the upper atmosphere data. This model is used as the common metadata format by the virtual observatories for solar-terrestrial physics. It includes metadata referring to each data file (called a 'Granule'), which enable a search for data files as well as data sets. Further details are described in [2] and [3]. Currently, three additional Japanese institutions are being incorporated in IUGONET. Furthermore, metadata of observations of the troposphere, taken at the observatories of the middle and upper atmosphere radar at Shigaraki and the Meteor radar in Indonesia, have been incorporated. These additions will contribute to efficient interdisciplinary scientific research. In the beginning of 2013, the registration of the 'Observatory' and 'Instrument' metadata was completed, which makes it easy to overview of the metadata database. The number of registered metadata as of the end of July, totalled 8.8 million, including 793 observatories and 878 instruments. It is important to promote interoperability and/or metadata exchange between the database development groups. A memorandum of agreement has been signed with the European Near-Earth Space Data Infrastructure for e-Science (ESPAS) project, which has similar objectives to IUGONET with regard to a framework for formal collaboration. Furthermore, observations by satellites and the International Space Station are being incorporated with a view for making/linking metadata databases. The development of effective data systems will contribute to the progress of scientific research on solar terrestrial physics, climate and the geophysical environment. Any kind of cooperation, metadata input and feedback, especially for linkage of the databases, is welcomed. References 1. Hayashi, H. et al., Inter-university Upper Atmosphere Global Observation Network (IUGONET), Data Sci. J., 12, WDS179-184, 2013. 2. King, T. et al., SPASE 2.0: A standard data model for space physics. Earth Sci. Inform. 3, 67-73, 2010, doi:10.1007/s12145-010-0053-4. 3. Hori, T., et al., Development of IUGONET metadata format and metadata management system. J. Space Sci. Info. Jpn., 105-111, 2012. (in Japanese)