Managing biomedical image metadata for search and retrieval of similar images.

PubMed

Korenblum, Daniel; Rubin, Daniel; Napel, Sandy; Rodriguez, Cesar; Beaulieu, Chris

2011-08-01

Radiology images are generally disconnected from the metadata describing their contents, such as imaging observations ("semantic" metadata), which are usually described in text reports that are not directly linked to the images. We developed a system, the Biomedical Image Metadata Manager (BIMM) to (1) address the problem of managing biomedical image metadata and (2) facilitate the retrieval of similar images using semantic feature metadata. Our approach allows radiologists, researchers, and students to take advantage of the vast and growing repositories of medical image data by explicitly linking images to their associated metadata in a relational database that is globally accessible through a Web application. BIMM receives input in the form of standard-based metadata files using Web service and parses and stores the metadata in a relational database allowing efficient data query and maintenance capabilities. Upon querying BIMM for images, 2D regions of interest (ROIs) stored as metadata are automatically rendered onto preview images included in search results. The system's "match observations" function retrieves images with similar ROIs based on specific semantic features describing imaging observation characteristics (IOCs). We demonstrate that the system, using IOCs alone, can accurately retrieve images with diagnoses matching the query images, and we evaluate its performance on a set of annotated liver lesion images. BIMM has several potential applications, e.g., computer-aided detection and diagnosis, content-based image retrieval, automating medical analysis protocols, and gathering population statistics like disease prevalences. The system provides a framework for decision support systems, potentially improving their diagnostic accuracy and selection of appropriate therapies.

Array Databases: Agile Analytics (not just) for the Earth Sciences

NASA Astrophysics Data System (ADS)

Baumann, P.; Misev, D.

2015-12-01

Gridded data, such as images, image timeseries, and climate datacubes, today are managed separately from the metadata, and with different, restricted retrieval capabilities. While databases are good at metadata modelled in tables, XML hierarchies, or RDF graphs, they traditionally do not support multi-dimensional arrays.This gap is being closed by Array Databases, pioneered by the scalable rasdaman ("raster data manager") array engine. Its declarative query language, rasql, extends SQL with array operators which are optimized and parallelized on server side. Installations can easily be mashed up securely, thereby enabling large-scale location-transparent query processing in federations. Domain experts value the integration with their commonly used tools leading to a quick learning curve.Earth, Space, and Life sciences, but also Social sciences as well as business have massive amounts of data and complex analysis challenges that are answered by rasdaman. As of today, rasdaman is mature and in operational use on hundreds of Terabytes of timeseries datacubes, with transparent query distribution across more than 1,000 nodes. Additionally, its concepts have shaped international Big Data standards in the field, including the forthcoming array extension to ISO SQL, many of which are supported by both open-source and commercial systems meantime. In the geo field, rasdaman is reference implementation for the Open Geospatial Consortium (OGC) Big Data standard, WCS, now also under adoption by ISO. Further, rasdaman is in the final stage of OSGeo incubation.In this contribution we present array queries a la rasdaman, describe the architecture and novel optimization and parallelization techniques introduced in 2015, and put this in context of the intercontinental EarthServer initiative which utilizes rasdaman for enabling agile analytics on Petascale datacubes.

EquiX-A Search and Query Language for XML.

ERIC Educational Resources Information Center

Cohen, Sara; Kanza, Yaron; Kogan, Yakov; Sagiv, Yehoshua; Nutt, Werner; Serebrenik, Alexander

2002-01-01

Describes EquiX, a search language for XML that combines querying with searching to query the data and the meta-data content of Web pages. Topics include search engines; a data model for XML documents; search query syntax; search query semantics; an algorithm for evaluating a query on a document; and indexing EquiX queries. (LRW)

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.

Database technology and the management of multimedia data in the Mirror project

NASA Astrophysics Data System (ADS)

de Vries, Arjen P.; Blanken, H. M.

1998-10-01

Multimedia digital libraries require an open distributed architecture instead of a monolithic database system. In the Mirror project, we use the Monet extensible database kernel to manage different representation of multimedia objects. To maintain independence between content, meta-data, and the creation of meta-data, we allow distribution of data and operations using CORBA. This open architecture introduces new problems for data access. From an end user's perspective, the problem is how to search the available representations to fulfill an actual information need; the conceptual gap between human perceptual processes and the meta-data is too large. From a system's perspective, several representations of the data may semantically overlap or be irrelevant. We address these problems with an iterative query process and active user participating through relevance feedback. A retrieval model based on inference networks assists the user with query formulation. The integration of this model into the database design has two advantages. First, the user can query both the logical and the content structure of multimedia objects. Second, the use of different data models in the logical and the physical database design provides data independence and allows algebraic query optimization. We illustrate query processing with a music retrieval application.

Federated ontology-based queries over cancer data

PubMed Central

2012-01-01

Background Personalised medicine provides patients with treatments that are specific to their genetic profiles. It requires efficient data sharing of disparate data types across a variety of scientific disciplines, such as molecular biology, pathology, radiology and clinical practice. Personalised medicine aims to offer the safest and most effective therapeutic strategy based on the gene variations of each subject. In particular, this is valid in oncology, where knowledge about genetic mutations has already led to new therapies. Current molecular biology techniques (microarrays, proteomics, epigenetic technology and improved DNA sequencing technology) enable better characterisation of cancer tumours. The vast amounts of data, however, coupled with the use of different terms - or semantic heterogeneity - in each discipline makes the retrieval and integration of information difficult. Results Existing software infrastructures for data-sharing in the cancer domain, such as caGrid, support access to distributed information. caGrid follows a service-oriented model-driven architecture. Each data source in caGrid is associated with metadata at increasing levels of abstraction, including syntactic, structural, reference and domain metadata. The domain metadata consists of ontology-based annotations associated with the structural information of each data source. However, caGrid's current querying functionality is given at the structural metadata level, without capitalising on the ontology-based annotations. This paper presents the design of and theoretical foundations for distributed ontology-based queries over cancer research data. Concept-based queries are reformulated to the target query language, where join conditions between multiple data sources are found by exploiting the semantic annotations. The system has been implemented, as a proof of concept, over the caGrid infrastructure. The approach is applicable to other model-driven architectures. A graphical user interface has been developed, supporting ontology-based queries over caGrid data sources. An extensive evaluation of the query reformulation technique is included. Conclusions To support personalised medicine in oncology, it is crucial to retrieve and integrate molecular, pathology, radiology and clinical data in an efficient manner. The semantic heterogeneity of the data makes this a challenging task. Ontologies provide a formal framework to support querying and integration. This paper provides an ontology-based solution for querying distributed databases over service-oriented, model-driven infrastructures. PMID:22373043

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 .

Storing, Browsing, Querying, and Sharing Data: the THREDDS Data Repository (TDR)

NASA Astrophysics Data System (ADS)

Wilson, A.; Lindholm, D.; Baltzer, T.

2005-12-01

The Unidata Internet Data Distribution (IDD) network delivers gigabytes of data per day in near real time to sites across the U.S. and beyond. The THREDDS Data Server (TDS) supports public browsing of metadata and data access via OPeNDAP enabled URLs for datasets such as these. With such large quantities of data, sites generally employ a simple data management policy, keeping the data for a relatively short term on the order of hours to perhaps a week or two. In order to save interesting data in longer term storage and make it available for sharing, a user must move the data herself. In this case the user is responsible for determining where space is available, executing the data movement, generating any desired metadata, and setting access control to enable sharing. This task sequence is generally based on execution of a sequence of low level operating system specific commands with significant user involvement. The LEAD (Linked Environments for Atmospheric Discovery) project is building a cyberinfrastructure to support research and education in mesoscale meteorology. LEAD orchestrations require large, robust, and reliable storage with speedy access to stage data and store both intermediate and final results. These requirements suggest storage solutions that involve distributed storage, replication, and interfacing to archival storage systems such as mass storage systems and tape or removable disks. LEAD requirements also include metadata generation and access in order to support querying. In support of both THREDDS and LEAD requirements, Unidata is designing and prototyping the THREDDS Data Repository (TDR), a framework for a modular data repository to support distributed data storage and retrieval using a variety of back end storage media and interchangeable software components. The TDR interface will provide high level abstractions for long term storage, controlled, fast and reliable access, and data movement capabilities via a variety of technologies such as OPeNDAP and gridftp. The modular structure will allow substitution of software components so that both simple and complex storage media can be integrated into the repository. It will also allow integration of different varieties of supporting software. For example, if replication is desired, replica management could be handled via a simple hash table or a complex solution such as Replica Locater Service (RLS). In order to ensure that metadata is available for all the data in the repository, the TDR will also generate THREDDS metadata when necessary. Users will be able to establish levels of access control to their metadata and data. Coupled with a THREDDS Data Server, both browsing via THREDDS catalogs and querying capabilities will be supported. This presentation will describe the motivating factors, current status, and future plans of the TDR. References: IDD: http://www.unidata.ucar.edu/content/software/idd/index.html THREDDS: http://www.unidata.ucar.edu/content/projects/THREDDS/tech/server/ServerStatus.html LEAD: http://lead.ou.edu/ RLS: http://www.isi.edu/~annc/papers/chervenakRLSjournal05.pdf

Flexible Querying of Lifelong Learner Metadata

ERIC Educational Resources Information Center

Poulovassilis, A.; Selmer, P.; Wood, P. T.

2012-01-01

This paper discusses the provision of flexible querying facilities over heterogeneous data arising from lifelong learners' educational and work experiences. A key aim of such querying facilities is to allow learners to identify possible choices for their future learning and professional development by seeing what others have done. We motivate and…

A Shared Infrastructure for Federated Search Across Distributed Scientific Metadata Catalogs

NASA Astrophysics Data System (ADS)

Reed, S. A.; Truslove, I.; Billingsley, B. W.; Grauch, A.; Harper, D.; Kovarik, J.; Lopez, L.; Liu, M.; Brandt, M.

2013-12-01

The vast amount of science metadata can be overwhelming and highly complex. Comprehensive analysis and sharing of metadata is difficult since institutions often publish to their own repositories. There are many disjoint standards used for publishing scientific data, making it difficult to discover and share information from different sources. Services that publish metadata catalogs often have different protocols, formats, and semantics. The research community is limited by the exclusivity of separate metadata catalogs and thus it is desirable to have federated search interfaces capable of unified search queries across multiple sources. Aggregation of metadata catalogs also enables users to critique metadata more rigorously. With these motivations in mind, the National Snow and Ice Data Center (NSIDC) and Advanced Cooperative Arctic Data and Information Service (ACADIS) implemented two search interfaces for the community. Both the NSIDC Search and ACADIS Arctic Data Explorer (ADE) use a common infrastructure which keeps maintenance costs low. The search clients are designed to make OpenSearch requests against Solr, an Open Source search platform. Solr applies indexes to specific fields of the metadata which in this instance optimizes queries containing keywords, spatial bounds and temporal ranges. NSIDC metadata is reused by both search interfaces but the ADE also brokers additional sources. Users can quickly find relevant metadata with minimal effort and ultimately lowers costs for research. This presentation will highlight the reuse of data and code between NSIDC and ACADIS, discuss challenges and milestones for each project, and will identify creation and use of Open Source libraries.

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

PropBase Query Layer: a single portal to UK subsurface physical property databases

NASA Astrophysics Data System (ADS)

Kingdon, Andrew; Nayembil, Martin L.; Richardson, Anne E.; Smith, A. Graham

2013-04-01

Until recently, the delivery of geological information for industry and public was achieved by geological mapping. Now pervasively available computers mean that 3D geological models can deliver realistic representations of the geometric location of geological units, represented as shells or volumes. The next phase of this process is to populate these with physical properties data that describe subsurface heterogeneity and its associated uncertainty. Achieving this requires capture and serving of physical, hydrological and other property information from diverse sources to populate these models. The British Geological Survey (BGS) holds large volumes of subsurface property data, derived both from their own research data collection and also other, often commercially derived data sources. This can be voxelated to incorporate this data into the models to demonstrate property variation within the subsurface geometry. All property data held by BGS has for many years been stored in relational databases to ensure their long-term continuity. However these have, by necessity, complex structures; each database contains positional reference data and model information, and also metadata such as sample identification information and attributes that define the source and processing. Whilst this is critical to assessing these analyses, it also hugely complicates the understanding of variability of the property under assessment and requires multiple queries to study related datasets making extracting physical properties from these databases difficult. Therefore the PropBase Query Layer has been created to allow simplified aggregation and extraction of all related data and its presentation of complex data in simple, mostly denormalized, tables which combine information from multiple databases into a single system. The structure from each relational database is denormalized in a generalised structure, so that each dataset can be viewed together in a common format using a simple interface. Data are re-engineered to facilitate easy loading. The query layer structure comprises tables, procedures, functions, triggers, views and materialised views. The structure contains a main table PRB_DATA which contains all of the data with the following attribution: • a unique identifier • the data source • the unique identifier from the parent database for traceability • the 3D location • the property type • the property value • the units • necessary qualifiers • precision information and an audit trail Data sources, property type and units are constrained by dictionaries, a key component of the structure which defines what properties and inheritance hierarchies are to be coded and also guides the process as to what and how these are extracted from the structure. Data types served by the Query Layer include site investigation derived geotechnical data, hydrogeology datasets, regional geochemistry, geophysical logs as well as lithological and borehole metadata. The size and complexity of the data sets with multiple parent structures requires a technically robust approach to keep the layer synchronised. This is achieved through Oracle procedures written in PL/SQL containing the logic required to carry out the data manipulation (inserts, updates, deletes) to keep the layer synchronised with the underlying databases either as regular scheduled jobs (weekly, monthly etc) or invoked on demand. The PropBase Query Layer's implementation has enabled rapid data discovery, visualisation and interpretation of geological data with greater ease, simplifying the parametrisation of 3D model volumes and facilitating the study of intra-unit heterogeneity.

Development of an Integrated Biospecimen Database among the Regional Biobanks in Korea.

PubMed

Park, Hyun Sang; Cho, Hune; Kim, Hwa Sun

2016-04-01

This study developed an integrated database for 15 regional biobanks that provides large quantities of high-quality bio-data to researchers to be used for the prevention of disease, for the development of personalized medicines, and in genetics studies. We collected raw data, managed independently by 15 regional biobanks, for database modeling and analyzed and defined the metadata of the items. We also built a three-step (high, middle, and low) classification system for classifying the item concepts based on the metadata. To generate clear meanings of the items, clinical items were defined using the Systematized Nomenclature of Medicine Clinical Terms, and specimen items were defined using the Logical Observation Identifiers Names and Codes. To optimize database performance, we set up a multi-column index based on the classification system and the international standard code. As a result of subdividing 7,197,252 raw data items collected, we refined the metadata into 1,796 clinical items and 1,792 specimen items. The classification system consists of 15 high, 163 middle, and 3,588 low class items. International standard codes were linked to 69.9% of the clinical items and 71.7% of the specimen items. The database consists of 18 tables based on a table from MySQL Server 5.6. As a result of the performance evaluation, the multi-column index shortened query time by as much as nine times. The database developed was based on an international standard terminology system, providing an infrastructure that can integrate the 7,197,252 raw data items managed by the 15 regional biobanks. In particular, it resolved the inevitable interoperability issues in the exchange of information among the biobanks, and provided a solution to the synonym problem, which arises when the same concept is expressed in a variety of ways.

A "Simple Query Interface" Adapter for the Discovery and Exchange of Learning Resources

ERIC Educational Resources Information Center

Massart, David

2006-01-01

Developed as part of CEN/ISSS Workshop on Learning Technology efforts to improve interoperability between learning resource repositories, the Simple Query Interface (SQI) is an Application Program Interface (API) for querying heterogeneous repositories of learning resource metadata. In the context of the ProLearn Network of Excellence, SQI is used…

On-the-fly form generation and on-line metadata configuration--a clinical data management Web infrastructure in Java.

PubMed

Beck, Peter; Truskaller, Thomas; Rakovac, Ivo; Cadonna, Bruno; Pieber, Thomas R

2006-01-01

In this paper we describe the approach to build a web-based clinical data management infrastructure on top of an entity-attribute-value (EAV) database which provides for flexible definition and extension of clinical data sets as well as efficient data handling and high performance query execution. A "mixed" EAV implementation provides a flexible and configurable data repository and at the same time utilizes the performance advantages of conventional database tables for rarely changing data structures. A dynamically configurable data dictionary contains further information for data validation. The online user interface can also be assembled dynamically. A data transfer object which encapsulates data together with all required metadata is populated by the backend and directly used to dynamically render frontend forms and handle incoming data. The "mixed" EAV model enables flexible definition and modification of clinical data sets while reducing performance drawbacks of pure EAV implementations to a minimum. The system currently is in use in an electronic patient record with focus on flexibility and a quality management application (www.healthgate.at) with high performance requirements.

Using a linked data approach to aid development of a metadata portal to support Marine Strategy Framework Directive (MSFD) implementation

NASA Astrophysics Data System (ADS)

Wood, Chris

2016-04-01

Under the Marine Strategy Framework Directive (MSFD), EU Member States are mandated to achieve or maintain 'Good Environmental Status' (GES) in their marine areas by 2020, through a series of Programme of Measures (PoMs). The Celtic Seas Partnership (CSP), an EU LIFE+ project, aims to support policy makers, special-interest groups, users of the marine environment, and other interested stakeholders on MSFD implementation in the Celtic Seas geographical area. As part of this support, a metadata portal has been built to provide a signposting service to datasets that are relevant to MSFD within the Celtic Seas. To ensure that the metadata has the widest possible reach, a linked data approach was employed to construct the database. Although the metadata are stored in a traditional RDBS, the metadata are exposed as linked data via the D2RQ platform, allowing virtual RDF graphs to be generated. SPARQL queries can be executed against the end-point allowing any user to manipulate the metadata. D2RQ's mapping language, based on turtle, was used to map a wide range of relevant ontologies to the metadata (e.g. The Provenance Ontology (prov-o), Ocean Data Ontology (odo), Dublin Core Elements and Terms (dc & dcterms), Friend of a Friend (foaf), and Geospatial ontologies (geo)) allowing users to browse the metadata, either via SPARQL queries or by using D2RQ's HTML interface. The metadata were further enhanced by mapping relevant parameters to the NERC Vocabulary Server, itself built on a SPARQL endpoint. Additionally, a custom web front-end was built to enable users to browse the metadata and express queries through an intuitive graphical user interface that requires no prior knowledge of SPARQL. As well as providing means to browse the data via MSFD-related parameters (Descriptor, Criteria, and Indicator), the metadata records include the dataset's country of origin, the list of organisations involved in the management of the data, and links to any relevant INSPIRE-compliant services relating to the dataset. The web front-end therefore enables users to effectively filter, sort, or search the metadata. As the MSFD timeline requires Member States to review their progress on achieving or maintaining GES every six years, the timely development of this metadata portal will not only aid interested stakeholders in understanding how member states are meeting their targets, but also shows how linked data can be used effectively to support policy makers and associated legislative bodies.

EUDAT B2FIND : A Cross-Discipline Metadata Service and Discovery Portal

NASA Astrophysics Data System (ADS)

Widmann, Heinrich; Thiemann, Hannes

2016-04-01

The European Data Infrastructure (EUDAT) project aims at a pan-European environment that supports a variety of multiple research communities and individuals to manage the rising tide of scientific data by advanced data management technologies. This led to the establishment of the community-driven Collaborative Data Infrastructure that implements common data services and storage resources to tackle the basic requirements and the specific challenges of international and interdisciplinary research data management. The metadata service B2FIND plays a central role in this context by providing a simple and user-friendly discovery portal to find research data collections stored in EUDAT data centers or in other repositories. For this we store the diverse metadata collected from heterogeneous sources in a comprehensive joint metadata catalogue and make them searchable in an open data portal. The implemented metadata ingestion workflow consists of three steps. First the metadata records - provided either by various research communities or via other EUDAT services - are harvested. Afterwards the raw metadata records are converted and mapped to unified key-value dictionaries as specified by the B2FIND schema. The semantic mapping of the non-uniform, community specific metadata to homogenous structured datasets is hereby the most subtle and challenging task. To assure and improve the quality of the metadata this mapping process is accompanied by • iterative and intense exchange with the community representatives, • usage of controlled vocabularies and community specific ontologies and • formal and semantic validation. Finally the mapped and checked records are uploaded as datasets to the catalogue, which is based on the open source data portal software CKAN. CKAN provides a rich RESTful JSON API and uses SOLR for dataset indexing that enables users to query and search in the catalogue. The homogenization of the community specific data models and vocabularies enables not only the unique presentation of these datasets as tables of field-value pairs but also the faceted, spatial and temporal search in the B2FIND metadata portal. Furthermore the service provides transparent access to the scientific data objects through the given references and identifiers in the metadata. B2FIND offers support for new communities interested in publishing their data within EUDAT. We present here the functionality and the features of the B2FIND service and give an outlook of further developments as interfaces to external libraries and use of Linked Data.

The health care and life sciences community profile for dataset descriptions

PubMed Central

Alexiev, Vladimir; Ansell, Peter; Bader, Gary; Baran, Joachim; Bolleman, Jerven T.; Callahan, Alison; Cruz-Toledo, José; Gaudet, Pascale; Gombocz, Erich A.; Gonzalez-Beltran, Alejandra N.; Groth, Paul; Haendel, Melissa; Ito, Maori; Jupp, Simon; Juty, Nick; Katayama, Toshiaki; Kobayashi, Norio; Krishnaswami, Kalpana; Laibe, Camille; Le Novère, Nicolas; Lin, Simon; Malone, James; Miller, Michael; Mungall, Christopher J.; Rietveld, Laurens; Wimalaratne, Sarala M.; Yamaguchi, Atsuko

2016-01-01

Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting guideline covers elements of description, identification, attribution, versioning, provenance, and content summarization. This guideline reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets. PMID:27602295

New concepts for building vocabulary for cell image ontologies.

PubMed

Plant, Anne L; Elliott, John T; Bhat, Talapady N

2011-12-21

There are significant challenges associated with the building of ontologies for cell biology experiments including the large numbers of terms and their synonyms. These challenges make it difficult to simultaneously query data from multiple experiments or ontologies. If vocabulary terms were consistently used and reused across and within ontologies, queries would be possible through shared terms. One approach to achieving this is to strictly control the terms used in ontologies in the form of a pre-defined schema, but this approach limits the individual researcher's ability to create new terms when needed to describe new experiments. Here, we propose the use of a limited number of highly reusable common root terms, and rules for an experimentalist to locally expand terms by adding more specific terms under more general root terms to form specific new vocabulary hierarchies that can be used to build ontologies. We illustrate the application of the method to build vocabularies and a prototype database for cell images that uses a visual data-tree of terms to facilitate sophisticated queries based on a experimental parameters. We demonstrate how the terminology might be extended by adding new vocabulary terms into the hierarchy of terms in an evolving process. In this approach, image data and metadata are handled separately, so we also describe a robust file-naming scheme to unambiguously identify image and other files associated with each metadata value. The prototype database http://sbd.nist.gov/ consists of more than 2000 images of cells and benchmark materials, and 163 metadata terms that describe experimental details, including many details about cell culture and handling. Image files of interest can be retrieved, and their data can be compared, by choosing one or more relevant metadata values as search terms. Metadata values for any dataset can be compared with corresponding values of another dataset through logical operations. Organizing metadata for cell imaging experiments under a framework of rules that include highly reused root terms will facilitate the addition of new terms into a vocabulary hierarchy and encourage the reuse of terms. These vocabulary hierarchies can be converted into XML schema or RDF graphs for displaying and querying, but this is not necessary for using it to annotate cell images. Vocabulary data trees from multiple experiments or laboratories can be aligned at the root terms to facilitate query development. This approach of developing vocabularies is compatible with the major advances in database technology and could be used for building the Semantic Web.

New concepts for building vocabulary for cell image ontologies

PubMed Central

2011-01-01

Background There are significant challenges associated with the building of ontologies for cell biology experiments including the large numbers of terms and their synonyms. These challenges make it difficult to simultaneously query data from multiple experiments or ontologies. If vocabulary terms were consistently used and reused across and within ontologies, queries would be possible through shared terms. One approach to achieving this is to strictly control the terms used in ontologies in the form of a pre-defined schema, but this approach limits the individual researcher's ability to create new terms when needed to describe new experiments. Results Here, we propose the use of a limited number of highly reusable common root terms, and rules for an experimentalist to locally expand terms by adding more specific terms under more general root terms to form specific new vocabulary hierarchies that can be used to build ontologies. We illustrate the application of the method to build vocabularies and a prototype database for cell images that uses a visual data-tree of terms to facilitate sophisticated queries based on a experimental parameters. We demonstrate how the terminology might be extended by adding new vocabulary terms into the hierarchy of terms in an evolving process. In this approach, image data and metadata are handled separately, so we also describe a robust file-naming scheme to unambiguously identify image and other files associated with each metadata value. The prototype database http://sbd.nist.gov/ consists of more than 2000 images of cells and benchmark materials, and 163 metadata terms that describe experimental details, including many details about cell culture and handling. Image files of interest can be retrieved, and their data can be compared, by choosing one or more relevant metadata values as search terms. Metadata values for any dataset can be compared with corresponding values of another dataset through logical operations. Conclusions Organizing metadata for cell imaging experiments under a framework of rules that include highly reused root terms will facilitate the addition of new terms into a vocabulary hierarchy and encourage the reuse of terms. These vocabulary hierarchies can be converted into XML schema or RDF graphs for displaying and querying, but this is not necessary for using it to annotate cell images. Vocabulary data trees from multiple experiments or laboratories can be aligned at the root terms to facilitate query development. This approach of developing vocabularies is compatible with the major advances in database technology and could be used for building the Semantic Web. PMID:22188658

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

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...

A Framework for WWW Query Processing

NASA Technical Reports Server (NTRS)

Wu, Binghui Helen; Wharton, Stephen (Technical Monitor)

2000-01-01

Query processing is the most common operation in a DBMS. Sophisticated query processing has been mainly targeted at a single enterprise environment providing centralized control over data and metadata. Submitting queries by anonymous users on the web is different in such a way that load balancing or DBMS' accessing control becomes the key issue. This paper provides a solution by introducing a framework for WWW query processing. The success of this framework lies in the utilization of query optimization techniques and the ontological approach. This methodology has proved to be cost effective at the NASA Goddard Space Flight Center Distributed Active Archive Center (GDAAC).

Targeted exploration and analysis of large cross-platform human transcriptomic compendia

PubMed Central

Zhu, Qian; Wong, Aaron K; Krishnan, Arjun; Aure, Miriam R; Tadych, Alicja; Zhang, Ran; Corney, David C; Greene, Casey S; Bongo, Lars A; Kristensen, Vessela N; Charikar, Moses; Li, Kai; Troyanskaya, Olga G.

2016-01-01

We present SEEK (http://seek.princeton.edu), a query-based search engine across very large transcriptomic data collections, including thousands of human data sets from almost 50 microarray and next-generation sequencing platforms. SEEK uses a novel query-level cross-validation-based algorithm to automatically prioritize data sets relevant to the query and a robust search approach to identify query-coregulated genes, pathways, and processes. SEEK provides cross-platform handling, multi-gene query search, iterative metadata-based search refinement, and extensive visualization-based analysis options. PMID:25581801

A Geospatial Semantic Enrichment and Query Service for Geotagged Photographs

PubMed Central

Ennis, Andrew; Nugent, Chris; Morrow, Philip; Chen, Liming; Ioannidis, George; Stan, Alexandru; Rachev, Preslav

2015-01-01

With the increasing abundance of technologies and smart devices, equipped with a multitude of sensors for sensing the environment around them, information creation and consumption has now become effortless. This, in particular, is the case for photographs with vast amounts being created and shared every day. For example, at the time of this writing, Instagram users upload 70 million photographs a day. Nevertheless, it still remains a challenge to discover the “right” information for the appropriate purpose. This paper describes an approach to create semantic geospatial metadata for photographs, which can facilitate photograph search and discovery. To achieve this we have developed and implemented a semantic geospatial data model by which a photograph can be enrich with geospatial metadata extracted from several geospatial data sources based on the raw low-level geo-metadata from a smartphone photograph. We present the details of our method and implementation for searching and querying the semantic geospatial metadata repository to enable a user or third party system to find the information they are looking for. PMID:26205265

A searching and reporting system for relational databases using a graph-based metadata representation.

PubMed

Hewitt, Robin; Gobbi, Alberto; Lee, Man-Ling

2005-01-01

Relational databases are the current standard for storing and retrieving data in the pharmaceutical and biotech industries. However, retrieving data from a relational database requires specialized knowledge of the database schema and of the SQL query language. At Anadys, we have developed an easy-to-use system for searching and reporting data in a relational database to support our drug discovery project teams. This system is fast and flexible and allows users to access all data without having to write SQL queries. This paper presents the hierarchical, graph-based metadata representation and SQL-construction methods that, together, are the basis of this system's capabilities.

DIRAC File Replica and Metadata Catalog

NASA Astrophysics Data System (ADS)

Tsaregorodtsev, A.; Poss, S.

2012-12-01

File replica and metadata catalogs are essential parts of any distributed data management system, which are largely determining its functionality and performance. A new File Catalog (DFC) was developed in the framework of the DIRAC Project that combines both replica and metadata catalog functionality. The DFC design is based on the practical experience with the data management system of the LHCb Collaboration. It is optimized for the most common patterns of the catalog usage in order to achieve maximum performance from the user perspective. The DFC supports bulk operations for replica queries and allows quick analysis of the storage usage globally and for each Storage Element separately. It supports flexible ACL rules with plug-ins for various policies that can be adopted by a particular community. The DFC catalog allows to store various types of metadata associated with files and directories and to perform efficient queries for the data based on complex metadata combinations. Definition of file ancestor-descendent relation chains is also possible. The DFC catalog is implemented in the general DIRAC distributed computing framework following the standard grid security architecture. In this paper we describe the design of the DFC and its implementation details. The performance measurements are compared with other grid file catalog implementations. The experience of the DFC Catalog usage in the CLIC detector project are discussed.

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.

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

Solving the problem of Trans-Genomic Query with alignment tables.

PubMed

Parker, Douglass Stott; Hsiao, Ruey-Lung; Xing, Yi; Resch, Alissa M; Lee, Christopher J

2008-01-01

The trans-genomic query (TGQ) problem--enabling the free query of biological information, even across genomes--is a central challenge facing bioinformatics. Solutions to this problem can alter the nature of the field, moving it beyond the jungle of data integration and expanding the number and scope of questions that can be answered. An alignment table is a binary relationship on locations (sequence segments). An important special case of alignment tables are hit tables ? tables of pairs of highly similar segments produced by alignment tools like BLAST. However, alignment tables also include general binary relationships, and can represent any useful connection between sequence locations. They can be curated, and provide a high-quality queryable backbone of connections between biological information. Alignment tables thus can be a natural foundation for TGQ, as they permit a central part of the TGQ problem to be reduced to purely technical problems involving tables of locations.Key challenges in implementing alignment tables include efficient representation and indexing of sequence locations. We define a location datatype that can be incorporated naturally into common off-the-shelf database systems. We also describe an implementation of alignment tables in BLASTGRES, an extension of the open-source POSTGRESQL database system that provides indexing and operators on locations required for querying alignment tables. This paper also reviews several successful large-scale applications of alignment tables for Trans-Genomic Query. Tables with millions of alignments have been used in queries about alternative splicing, an area of genomic analysis concerning the way in which a single gene can yield multiple transcripts. Comparative genomics is a large potential application area for TGQ and alignment tables.

Mashup of Geo and Space Science Data Provided via Relational Databases in the Semantic Web

NASA Astrophysics Data System (ADS)

Ritschel, B.; Seelus, C.; Neher, G.; Iyemori, T.; Koyama, Y.; Yatagai, A. I.; Murayama, Y.; King, T. A.; Hughes, J. S.; Fung, S. F.; Galkin, I. A.; Hapgood, M. A.; Belehaki, A.

2014-12-01

The use of RDBMS for the storage and management of geo and space science data and/or metadata is very common. Although the information stored in tables is based on a data model and therefore well organized and structured, a direct mashup with RDF based data stored in triple stores is not possible. One solution of the problem consists in the transformation of the whole content into RDF structures and storage in triple stores. Another interesting way is the use of a specific system/service, such as e.g. D2RQ, for the access to relational database content as virtual, read only RDF graphs. The Semantic Web based -proof of concept- GFZ ISDC uses the triple store Virtuoso for the storage of general context information/metadata to geo and space science satellite and ground station data. There is information about projects, platforms, instruments, persons, product types, etc. available but no detailed metadata about the data granuals itself. Such important information, as e.g. start or end time or the detailed spatial coverage of a single measurement is stored in RDBMS tables of the ISDC catalog system only. In order to provide a seamless access to all available information about the granuals/data products a mashup of the different data resources (triple store and RDBMS) is necessary. This paper describes the use of D2RQ for a Semantic Web/SPARQL based mashup of relational databases used for ISDC data server but also for the access to IUGONET and/or ESPAS and further geo and space science data resources. RDBMS Relational Database Management System RDF Resource Description Framework SPARQL SPARQL Protocol And RDF Query Language D2RQ Accessing Relational Databases as Virtual RDF Graphs GFZ ISDC German Research Centre for Geosciences Information System and Data Center IUGONET Inter-university Upper Atmosphere Global Observation Network (Japanese project) ESPAS Near earth space data infrastructure for e-science (European Union funded project)

The VO-Dance web application at the IA2 data center

NASA Astrophysics Data System (ADS)

Molinaro, Marco; Knapic, Cristina; Smareglia, Riccardo

2012-09-01

Italian center for Astronomical Archives (IA2, http://ia2.oats.inaf.it) is a national infrastructure project of the Italian National Institute for Astrophysics (Istituto Nazionale di AstroFisica, INAF) that provides services for the astronomical community. Besides data hosting for the Large Binocular Telescope (LBT) Corporation, the Galileo National Telescope (Telescopio Nazionale Galileo, TNG) Consortium and other telescopes and instruments, IA2 offers proprietary and public data access through user portals (both developed and mirrored) and deploys resources complying the Virtual Observatory (VO) standards. Archiving systems and web interfaces are developed to be extremely flexible about adding new instruments from other telescopes. VO resources publishing, along with data access portals, implements the International Virtual Observatory Alliance (IVOA) protocols providing astronomers with new ways of analyzing data. Given the large variety of data flavours and IVOA standards, the need for tools to easily accomplish data ingestion and data publishing arises. This paper describes the VO-Dance tool, that IA2 started developing to address VO resources publishing in a dynamical way from already existent database tables or views. The tool consists in a Java web application, potentially DBMS and platform independent, that stores internally the services' metadata and information, exposes restful endpoints to accept VO queries for these services and dynamically translates calls to these endpoints to SQL queries coherent with the published table or view. In response to the call VO-Dance translates back the database answer in a VO compliant way.

Adapt

NASA Astrophysics Data System (ADS)

Bargatze, L. F.

2015-12-01

Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted files, or the addition of new or the deletion of old data products. Next, ADAPT routines analyzed the query results and issued updates to the metadata stored in the UCLA CDAWEB and SPDF metadata registries. In this way, the SPASE metadata registries generated by ADAPT can be relied on to provide up to date and complete access to Heliophysics CDF data resources on a daily basis.

Petaminer: Using ROOT for efficient data storage in MySQL database

NASA Astrophysics Data System (ADS)

Cranshaw, J.; Malon, D.; Vaniachine, A.; Fine, V.; Lauret, J.; Hamill, P.

2010-04-01

High Energy and Nuclear Physics (HENP) experiments store Petabytes of event data and Terabytes of calibration data in ROOT files. The Petaminer project is developing a custom MySQL storage engine to enable the MySQL query processor to directly access experimental data stored in ROOT files. Our project is addressing the problem of efficient navigation to PetaBytes of HENP experimental data described with event-level TAG metadata, which is required by data intensive physics communities such as the LHC and RHIC experiments. Physicists need to be able to compose a metadata query and rapidly retrieve the set of matching events, where improved efficiency will facilitate the discovery process by permitting rapid iterations of data evaluation and retrieval. Our custom MySQL storage engine enables the MySQL query processor to directly access TAG data stored in ROOT TTrees. As ROOT TTrees are column-oriented, reading them directly provides improved performance over traditional row-oriented TAG databases. Leveraging the flexible and powerful SQL query language to access data stored in ROOT TTrees, the Petaminer approach enables rich MySQL index-building capabilities for further performance optimization.

XAFS Data Interchange: A single spectrum XAFS data file format.

PubMed

Ravel, B; Newville, M

We propose a standard data format for the interchange of XAFS data. The XAFS Data Interchange (XDI) standard is meant to encapsulate a single spectrum of XAFS along with relevant metadata. XDI is a text-based format with a simple syntax which clearly delineates metadata from the data table in a way that is easily interpreted both by a computer and by a human. The metadata header is inspired by the format of an electronic mail header, representing metadata names and values as an associative array. The data table is represented as columns of numbers. This format can be imported as is into most existing XAFS data analysis, spreadsheet, or data visualization programs. Along with a specification and a dictionary of metadata types, we provide an application-programming interface written in C and bindings for programming dynamic languages.

XAFS Data Interchange: A single spectrum XAFS data file format

NASA Astrophysics Data System (ADS)

Ravel, B.; Newville, M.

2016-05-01

We propose a standard data format for the interchange of XAFS data. The XAFS Data Interchange (XDI) standard is meant to encapsulate a single spectrum of XAFS along with relevant metadata. XDI is a text-based format with a simple syntax which clearly delineates metadata from the data table in a way that is easily interpreted both by a computer and by a human. The metadata header is inspired by the format of an electronic mail header, representing metadata names and values as an associative array. The data table is represented as columns of numbers. This format can be imported as is into most existing XAFS data analysis, spreadsheet, or data visualization programs. Along with a specification and a dictionary of metadata types, we provide an application-programming interface written in C and bindings for programming dynamic languages.

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.

Designing for Peta-Scale in the LSST Database

NASA Astrophysics Data System (ADS)

Kantor, J.; Axelrod, T.; Becla, J.; Cook, K.; Nikolaev, S.; Gray, J.; Plante, R.; Nieto-Santisteban, M.; Szalay, A.; Thakar, A.

2007-10-01

The Large Synoptic Survey Telescope (LSST), a proposed ground-based 8.4 m telescope with a 10 deg^2 field of view, will generate 15 TB of raw images every observing night. When calibration and processed data are added, the image archive, catalogs, and meta-data will grow 15 PB yr^{-1} on average. The LSST Data Management System (DMS) must capture, process, store, index, replicate, and provide open access to this data. Alerts must be triggered within 30 s of data acquisition. To do this in real-time at these data volumes will require advances in data management, database, and file system techniques. This paper describes the design of the LSST DMS and emphasizes features for peta-scale data. The LSST DMS will employ a combination of distributed database and file systems, with schema, partitioning, and indexing oriented for parallel operations. Image files are stored in a distributed file system with references to, and meta-data from, each file stored in the databases. The schema design supports pipeline processing, rapid ingest, and efficient query. Vertical partitioning reduces disk input/output requirements, horizontal partitioning allows parallel data access using arrays of servers and disks. Indexing is extensive, utilizing both conventional RAM-resident indexes and column-narrow, row-deep tag tables/covering indices that are extracted from tables that contain many more attributes. The DMS Data Access Framework is encapsulated in a middleware framework to provide a uniform service interface to all framework capabilities. This framework will provide the automated work-flow, replication, and data analysis capabilities necessary to make data processing and data quality analysis feasible at this scale.

VPipe: Virtual Pipelining for Scheduling of DAG Stream Query Plans

NASA Astrophysics Data System (ADS)

Wang, Song; Gupta, Chetan; Mehta, Abhay

There are data streams all around us that can be harnessed for tremendous business and personal advantage. For an enterprise-level stream processing system such as CHAOS [1] (Continuous, Heterogeneous Analytic Over Streams), handling of complex query plans with resource constraints is challenging. While several scheduling strategies exist for stream processing, efficient scheduling of complex DAG query plans is still largely unsolved. In this paper, we propose a novel execution scheme for scheduling complex directed acyclic graph (DAG) query plans with meta-data enriched stream tuples. Our solution, called Virtual Pipelined Chain (or VPipe Chain for short), effectively extends the "Chain" pipelining scheduling approach to complex DAG query plans.

The Star Schema Benchmark and Augmented Fact Table Indexing

NASA Astrophysics Data System (ADS)

O'Neil, Patrick; O'Neil, Elizabeth; Chen, Xuedong; Revilak, Stephen

We provide a benchmark measuring star schema queries retrieving data from a fact table with Where clause column restrictions on dimension tables. Clustering is crucial to performance with modern disk technology, since retrievals with filter factors down to 0.0005 are now performed most efficiently by sequential table search rather than by indexed access. DB2’s Multi-Dimensional Clustering (MDC) provides methods to "dice" the fact table along a number of orthogonal "dimensions", but only when these dimensions are columns in the fact table. The diced cells cluster fact rows on several of these "dimensions" at once so queries restricting several such columns can access crucially localized data, with much faster query response. Unfortunately, columns of dimension tables of a star schema are not usually represented in the fact table. In this paper, we show a simple way to adjoin physical copies of dimension columns to the fact table, dicing data to effectively cluster query retrieval, and explain how such dicing can be achieved on database products other than DB2. We provide benchmark measurements to show successful use of this methodology on three commercial database products.

Tools and strategies for instrument monitoring, data mining and data access

NASA Astrophysics Data System (ADS)

van Hees, R. M., ,, Dr

2009-04-01

The ever growing size of data sets produced by various satellite instruments creates a challenge in data management. Three main tasks were identified: instrument performance monitoring, data mining by users and data deployment. In this presentation, I will discuss the three tasks and our solution. As a practical example to illustrate the problem and make the discussion less abstract, I will use Sciamachy on-board the ESA satellite Envisat. Since the launch of Envisat, in March 2002, Sciamachy has performed nearly a billion science measurements and performed daily calibrations measurements. The total size of the data set (not including reprocessed data) is over 30 TB, distributed over 150,000 files. [Instrument Monitoring] Most instruments produce house-keeping data, which may include time, geo-location, temperature of different parts of the instrument and instrument settings and configuration. In addition, many instruments perform calibration measurements. Instrument performance monitoring requires automated analyzes of critical parameters for events, and the option to off-line inspect the behavior of various parameters in time. We choose to extract the necessary information from the SCIAMACHY data products, and store everything in one file, where we separated house-keeping data from calibration measurements. Due to the large volume and the need to have quick random-access, the Hierarchical Data Format (HDF5) was our obvious choice. The HDF5 format is self describing and designed to organize different types of data in one file. For example, one data set may contain the meta data of the calibration measurements: time, geo-location, instrument settings, quality parameters (temperature of the instrument), while a second large data set contains the actual measurements. The HDF5 high-level packet table API is ideal for tables that only grow (by appending rows), while the HDF5 table API is better suited for tables where rows need to be updated, inserted or replaced. In particular, the packet table API allows very compact storage of compound data sets and very fast read/write access. Details about this implementation and pitfalls will be given in the presentation. [Data Mining] The ability to select relevant data is a requirement that all data centers have to offer. The NL-SCIA-DC allows the users to select data using several criteria including: time, geo-location, type of observation and data quality. The result of the query are [i] location and name of relevant data products (files), or [ii] listing of meta data of the relevant measurements, or [iii] listing of the measurements (level 2 or higher). For this application, we need the power of a relational database, the SQL language, and the availability of spatial functions. PostgreSQL, extended with postGIS support turned out to be a good choice. Common queries on tables with millions of rows can be executed within seconds. [Data Deployment] The dissemination of scientific data is often cumbersome by the usage of many different formats to store the products. Therefore, time-consuming and inefficient conversions are needed to use data products from different origin. Within the Atmospheric Data Access for the Geospatial User Community (ADAGUC) project we provide selected space borne atmospheric and land data sets in the same data format and consistent internal structure, so that users can easily use and combine data. The common format for storage is HDF5, but the netCDF-4 API is used to create the data sets. The standard for metadata and dataset attributes follow the netCDF Climate and Forecast conventions, in addition metadata complies to the ISO 19115:2003 INSPIRE profile are added. The advantage of netCDF-4 is that the API is essentially equal to netCDF-3 (with a few extensions), while the data format is HDF5 (recognized by many scientific tools). The added metadata ensures product traceability. Details will be given in the presentation and several posters.

In-field Access to Geoscientific Metadata through GPS-enabled Mobile Phones

NASA Astrophysics Data System (ADS)

Hobona, Gobe; Jackson, Mike; Jordan, Colm; Butchart, Ben

2010-05-01

Fieldwork is an integral part of much geosciences research. But whilst geoscientists have physical or online access to data collections whilst in the laboratory or at base stations, equivalent in-field access is not standard or straightforward. The increasing availability of mobile internet and GPS-supported mobile phones, however, now provides the basis for addressing this issue. The SPACER project was commissioned by the Rapid Innovation initiative of the UK Joint Information Systems Committee (JISC) to explore the potential for GPS-enabled mobile phones to access geoscientific metadata collections. Metadata collections within the geosciences and the wider geospatial domain can be disseminated through web services based on the Catalogue Service for Web(CSW) standard of the Open Geospatial Consortium (OGC) - a global grouping of over 380 private, public and academic organisations aiming to improve interoperability between geospatial technologies. CSW offers an XML-over-HTTP interface for querying and retrieval of geospatial metadata. By default, the metadata returned by CSW is based on the ISO19115 standard and encoded in XML conformant to ISO19139. The SPACER project has created a prototype application that enables mobile phones to send queries to CSW containing user-defined keywords and coordinates acquired from GPS devices built-into the phones. The prototype has been developed using the free and open source Google Android platform. The mobile application offers views for listing titles, presenting multiple metadata elements and a Google Map with an overlay of bounding coordinates of datasets. The presentation will describe the architecture and approach applied in the development of the prototype.

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).

Enhanced DIII-D Data Management Through a Relational Database

NASA Astrophysics Data System (ADS)

Burruss, J. R.; Peng, Q.; Schachter, J.; Schissel, D. P.; Terpstra, T. B.

2000-10-01

A relational database is being used to serve data about DIII-D experiments. The database is optimized for queries across multiple shots, allowing for rapid data mining by SQL-literate researchers. The relational database relates different experiments and datasets, thus providing a big picture of DIII-D operations. Users are encouraged to add their own tables to the database. Summary physics quantities about DIII-D discharges are collected and stored in the database automatically. Meta-data about code runs, MDSplus usage, and visualization tool usage are collected, stored in the database, and later analyzed to improve computing. Documentation on the database may be accessed through programming languages such as C, Java, and IDL, or through ODBC compliant applications such as Excel and Access. A database-driven web page also provides a convenient means for viewing database quantities through the World Wide Web. Demonstrations will be given at the poster.

Visualizing and Validating Metadata Traceability within the CDISC Standards.

PubMed

Hume, Sam; Sarnikar, Surendra; Becnel, Lauren; Bennett, Dorine

2017-01-01

The Food & Drug Administration has begun requiring that electronic submissions of regulated clinical studies utilize the Clinical Data Information Standards Consortium data standards. Within regulated clinical research, traceability is a requirement and indicates that the analysis results can be traced back to the original source data. Current solutions for clinical research data traceability are limited in terms of querying, validation and visualization capabilities. This paper describes (1) the development of metadata models to support computable traceability and traceability visualizations that are compatible with industry data standards for the regulated clinical research domain, (2) adaptation of graph traversal algorithms to make them capable of identifying traceability gaps and validating traceability across the clinical research data lifecycle, and (3) development of a traceability query capability for retrieval and visualization of traceability information.

Visualizing and Validating Metadata Traceability within the CDISC Standards

PubMed Central

Hume, Sam; Sarnikar, Surendra; Becnel, Lauren; Bennett, Dorine

2017-01-01

The Food & Drug Administration has begun requiring that electronic submissions of regulated clinical studies utilize the Clinical Data Information Standards Consortium data standards. Within regulated clinical research, traceability is a requirement and indicates that the analysis results can be traced back to the original source data. Current solutions for clinical research data traceability are limited in terms of querying, validation and visualization capabilities. This paper describes (1) the development of metadata models to support computable traceability and traceability visualizations that are compatible with industry data standards for the regulated clinical research domain, (2) adaptation of graph traversal algorithms to make them capable of identifying traceability gaps and validating traceability across the clinical research data lifecycle, and (3) development of a traceability query capability for retrieval and visualization of traceability information. PMID:28815125

Implementing a genomic data management system using iRODS in the Wellcome Trust Sanger Institute

PubMed Central

2011-01-01

Background Increasingly large amounts of DNA sequencing data are being generated within the Wellcome Trust Sanger Institute (WTSI). The traditional file system struggles to handle these increasing amounts of sequence data. A good data management system therefore needs to be implemented and integrated into the current WTSI infrastructure. Such a system enables good management of the IT infrastructure of the sequencing pipeline and allows biologists to track their data. Results We have chosen a data grid system, iRODS (Rule-Oriented Data management systems), to act as the data management system for the WTSI. iRODS provides a rule-based system management approach which makes data replication much easier and provides extra data protection. Unlike the metadata provided by traditional file systems, the metadata system of iRODS is comprehensive and allows users to customize their own application level metadata. Users and IT experts in the WTSI can then query the metadata to find and track data. The aim of this paper is to describe how we designed and used (from both system and user viewpoints) iRODS as a data management system. Details are given about the problems faced and the solutions found when iRODS was implemented. A simple use case describing how users within the WTSI use iRODS is also introduced. Conclusions iRODS has been implemented and works as the production system for the sequencing pipeline of the WTSI. Both biologists and IT experts can now track and manage data, which could not previously be achieved. This novel approach allows biologists to define their own metadata and query the genomic data using those metadata. PMID:21906284

The SAMI Galaxy Survey: A prototype data archive for Big Science exploration

NASA Astrophysics Data System (ADS)

Konstantopoulos, I. S.; Green, A. W.; Foster, C.; Scott, N.; Allen, J. T.; Fogarty, L. M. R.; Lorente, N. P. F.; Sweet, S. M.; Hopkins, A. M.; Bland-Hawthorn, J.; Bryant, J. J.; Croom, S. M.; Goodwin, M.; Lawrence, J. S.; Owers, M. S.; Richards, S. N.

2015-11-01

We describe the data archive and database for the SAMI Galaxy Survey, an ongoing observational program that will cover ≈3400 galaxies with integral-field (spatially-resolved) spectroscopy. Amounting to some three million spectra, this is the largest sample of its kind to date. The data archive and built-in query engine use the versatile Hierarchical Data Format (HDF5), which precludes the need for external metadata tables and hence the setup and maintenance overhead those carry. The code produces simple outputs that can easily be translated to plots and tables, and the combination of these tools makes for a light system that can handle heavy data. This article acts as a contextual companion to the SAMI Survey Database source code repository, samiDB, which is freely available online and written entirely in Python. We also discuss the decisions related to the selection of tools and the creation of data visualisation modules. It is our aim that the work presented in this article-descriptions, rationale, and source code-will be of use to scientists looking to set up a maintenance-light data archive for a Big Science data load.

Informatics in radiology: use of CouchDB for document-based storage of DICOM objects.

PubMed

Rascovsky, Simón J; Delgado, Jorge A; Sanz, Alexander; Calvo, Víctor D; Castrillón, Gabriel

2012-01-01

Picture archiving and communication systems traditionally have depended on schema-based Structured Query Language (SQL) databases for imaging data management. To optimize database size and performance, many such systems store a reduced set of Digital Imaging and Communications in Medicine (DICOM) metadata, discarding informational content that might be needed in the future. As an alternative to traditional database systems, document-based key-value stores recently have gained popularity. These systems store documents containing key-value pairs that facilitate data searches without predefined schemas. Document-based key-value stores are especially suited to archive DICOM objects because DICOM metadata are highly heterogeneous collections of tag-value pairs conveying specific information about imaging modalities, acquisition protocols, and vendor-supported postprocessing options. The authors used an open-source document-based database management system (Apache CouchDB) to create and test two such databases; CouchDB was selected for its overall ease of use, capability for managing attachments, and reliance on HTTP and Representational State Transfer standards for accessing and retrieving data. A large database was created first in which the DICOM metadata from 5880 anonymized magnetic resonance imaging studies (1,949,753 images) were loaded by using a Ruby script. To provide the usual DICOM query functionality, several predefined "views" (standard queries) were created by using JavaScript. For performance comparison, the same queries were executed in both the CouchDB database and a SQL-based DICOM archive. The capabilities of CouchDB for attachment management and database replication were separately assessed in tests of a similar, smaller database. Results showed that CouchDB allowed efficient storage and interrogation of all DICOM objects; with the use of information retrieval algorithms such as map-reduce, all the DICOM metadata stored in the large database were searchable with only a minimal increase in retrieval time over that with the traditional database management system. Results also indicated possible uses for document-based databases in data mining applications such as dose monitoring, quality assurance, and protocol optimization. RSNA, 2012

EML, VEGA, ODM, LTER, GLEON - considerations and technologies for building a buoy information system at an LTER site

NASA Astrophysics Data System (ADS)

Gries, C.; Winslow, L.; Shin, P.; Hanson, P. C.; Barseghian, D.

2010-12-01

At the North Temperate Lakes Long Term Ecological Research (NTL LTER) site six buoys and one met station are maintained, each equipped with up to 20 sensors producing up to 45 separate data streams at a 1 or 10 minute frequency. Traditionally, this data volume has been managed in many matrix type tables, each described in the Ecological Metadata Language (EML) and accessed online by a query system based on the provided metadata. To develop a more flexible information system, several technologies are currently being experimented with. We will review, compare and evaluate these technologies and discuss constraints and advantages of network memberships and implementation of standards. A Data Turbine server is employed to stream data from data logger files into a database with the Real-time Data Viewer being used for monitoring sensor health. The Kepler work flow processor is being explored to introduce quality control routines into this data stream taking advantage of the Data Turbine actor. Kepler could replace traditional database triggers while adding visualization and advanced data access functionality for downstream modeling or other analytical applications. The data are currently streamed into the traditional matrix type tables and into an Observation Data Model (ODM) following the CUAHSI ODM 1.1 specifications. In parallel these sensor data are managed within the Global Lake Ecological Observatory Network (GLEON) where the software package Ziggy streams the data into a database of the VEGA data model. Contributing data to a network implies compliance with established standards for data delivery and data documentation. ODM or VEGA type data models are not easily described in EML, the metadata exchange standard for LTER sites, but are providing many advantages from an archival standpoint. Both GLEON and CUAHSI have developed advanced data access capabilities based on their respective data models and data exchange standards while LTER is currently in a phase of intense technology developments which will eventually provide standardized data access that includes ecological data set types currently not covered by either ODM or VEGA.

Data publication and sharing using the SciDrive service

NASA Astrophysics Data System (ADS)

Mishin, Dmitry; Medvedev, D.; Szalay, A. S.; Plante, R. L.

2014-01-01

Despite the last years progress in scientific data storage, still remains the problem of public data storage and sharing system for relatively small scientific datasets. These are collections forming the “long tail” of power log datasets distribution. The aggregated size of the long tail data is comparable to the size of all data collections from large archives, and the value of data is significant. The SciDrive project's main goal is providing the scientific community with a place to reliably and freely store such data and provide access to it to broad scientific community. The primary target audience of the project is astoromy community, and it will be extended to other fields. We're aiming to create a simple way of publishing a dataset, which can be then shared with other people. Data owner controls the permissions to modify and access the data and can assign a group of users or open the access to everyone. The data contained in the dataset will be automaticaly recognized by a background process. Known data formats will be extracted according to the user's settings. Currently tabular data can be automatically extracted to the user's MyDB table where user can make SQL queries to the dataset and merge it with other public CasJobs resources. Other data formats can be processed using a set of plugins that upload the data or metadata to user-defined side services. The current implementation targets some of the data formats commonly used by the astronomy communities, including FITS, ASCII and Excel tables, TIFF images, and YT simulations data archives. Along with generic metadata, format-specific metadata is also processed. For example, basic information about celestial objects is extracted from FITS files and TIFF images, if present. A 100TB implementation has just been put into production at Johns Hopkins University. The system features public data storage REST service supporting VOSpace 2.0 and Dropbox protocols, HTML5 web portal, command-line client and Java standalone client to synchronize a local folder with the remote storage. We use VAO SSO (Single Sign On) service from NCSA for users authentication that provides free registration for everyone.

Data, Metadata - Who Cares?

NASA Astrophysics Data System (ADS)

Baumann, Peter

2013-04-01

There is a traditional saying that metadata are understandable, semantic-rich, and searchable. Data, on the other hand, are big, with no accessible semantics, and just downloadable. Not only has this led to an imbalance of search support form a user perspective, but also underneath to a deep technology divide often using relational databases for metadata and bespoke archive solutions for data. Our vision is that this barrier will be overcome, and data and metadata become searchable likewise, leveraging the potential of semantic technologies in combination with scalability technologies. Ultimately, in this vision ad-hoc processing and filtering will not distinguish any longer, forming a uniformly accessible data universe. In the European EarthServer initiative, we work towards this vision by federating database-style raster query languages with metadata search and geo broker technology. We present our approach taken, how it can leverage OGC standards, the benefits envisaged, and first results.

GeoNetwork powered GI-cat: a geoportal hybrid solution

NASA Astrophysics Data System (ADS)

Baldini, Alessio; Boldrini, Enrico; Santoro, Mattia; Mazzetti, Paolo

2010-05-01

To the aim of setting up a Spatial Data Infrastructures (SDI) the creation of a system for the metadata management and discovery plays a fundamental role. An effective solution is the use of a geoportal (e.g. FAO/ESA geoportal), that has the important benefit of being accessible from a web browser. With this work we present a solution based integrating two of the available frameworks: GeoNetwork and GI-cat. GeoNetwork is an opensource software designed to improve accessibility of a wide variety of data together with the associated ancillary information (metadata), at different scale and from multidisciplinary sources; data are organized and documented in a standard and consistent way. GeoNetwork implements both the Portal and Catalog components of a Spatial Data Infrastructure (SDI) defined in the OGC Reference Architecture. It provides tools for managing and publishing metadata on spatial data and related services. GeoNetwork allows harvesting of various types of web data sources e.g. OGC Web Services (e.g. CSW, WCS, WMS). GI-cat is a distributed catalog based on a service-oriented framework of modular components and can be customized and tailored to support different deployment scenarios. It can federate a multiplicity of catalogs services, as well as inventory and access services in order to discover and access heterogeneous ESS resources. The federated resources are exposed by GI-cat through several standard catalog interfaces (e.g. OGC CSW AP ISO, OpenSearch, etc.) and by the GI-cat extended interface. Specific components implement mediation services for interfacing heterogeneous service providers, each of which exposes a specific standard specification; such components are called Accessors. These mediating components solve providers data modelmultiplicity by mapping them onto the GI-cat internal data model which implements the ISO 19115 Core profile. Accessors also implement the query protocol mapping; first they translate the query requests expressed according to the interface protocols exposed by GI-cat into the multiple query dialects spoken by the resource service providers. Currently, a number of well-accepted catalog and inventory services are supported, including several OGC Web Services, THREDDS Data Server, SeaDataNet Common Data Index, GBIF and OpenSearch engines. A GeoNetwork powered GI-cat has been developed in order to exploit the best of the two frameworks. The new system uses a modified version of GeoNetwork web interface in order to add the capability of querying also the specified GI-cat catalog and not only the GeoNetwork internal database. The resulting system consists in a geoportal in which GI-cat plays the role of the search engine. This new system allows to distribute the query on the different types of data sources linked to a GI-cat. The metadata results of the query are then visualized by the Geonetwork web interface. This configuration was experimented in the framework of GIIDA, a project of the Italian National Research Council (CNR) focused on data accessibility and interoperability. A second advantage of this solution is achieved setting up a GeoNetwork catalog amongst the accessors of the GI-cat instance. Such a configuration will allow in turn GI-cat to run the query against the internal GeoNetwork database. This allows to have both the harvesting and the metadata editor functionalities provided by GeoNetwork and the distributed search functionality of GI-cat available in a consistent way through the same web interface.

Query-Adaptive Reciprocal Hash Tables for Nearest Neighbor Search.

PubMed

Liu, Xianglong; Deng, Cheng; Lang, Bo; Tao, Dacheng; Li, Xuelong

2016-02-01

Recent years have witnessed the success of binary hashing techniques in approximate nearest neighbor search. In practice, multiple hash tables are usually built using hashing to cover more desired results in the hit buckets of each table. However, rare work studies the unified approach to constructing multiple informative hash tables using any type of hashing algorithms. Meanwhile, for multiple table search, it also lacks of a generic query-adaptive and fine-grained ranking scheme that can alleviate the binary quantization loss suffered in the standard hashing techniques. To solve the above problems, in this paper, we first regard the table construction as a selection problem over a set of candidate hash functions. With the graph representation of the function set, we propose an efficient solution that sequentially applies normalized dominant set to finding the most informative and independent hash functions for each table. To further reduce the redundancy between tables, we explore the reciprocal hash tables in a boosting manner, where the hash function graph is updated with high weights emphasized on the misclassified neighbor pairs of previous hash tables. To refine the ranking of the retrieved buckets within a certain Hamming radius from the query, we propose a query-adaptive bitwise weighting scheme to enable fine-grained bucket ranking in each hash table, exploiting the discriminative power of its hash functions and their complement for nearest neighbor search. Moreover, we integrate such scheme into the multiple table search using a fast, yet reciprocal table lookup algorithm within the adaptive weighted Hamming radius. In this paper, both the construction method and the query-adaptive search method are general and compatible with different types of hashing algorithms using different feature spaces and/or parameter settings. Our extensive experiments on several large-scale benchmarks demonstrate that the proposed techniques can significantly outperform both the naive construction methods and the state-of-the-art hashing algorithms.

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.

Evaluating non-relational storage technology for HEP metadata and meta-data catalog

NASA Astrophysics Data System (ADS)

Grigorieva, M. A.; Golosova, M. V.; Gubin, M. Y.; Klimentov, A. A.; Osipova, V. V.; Ryabinkin, E. A.

2016-10-01

Large-scale scientific experiments produce vast volumes of data. These data are stored, processed and analyzed in a distributed computing environment. The life cycle of experiment is managed by specialized software like Distributed Data Management and Workload Management Systems. In order to be interpreted and mined, experimental data must be accompanied by auxiliary metadata, which are recorded at each data processing step. Metadata describes scientific data and represent scientific objects or results of scientific experiments, allowing them to be shared by various applications, to be recorded in databases or published via Web. Processing and analysis of constantly growing volume of auxiliary metadata is a challenging task, not simpler than the management and processing of experimental data itself. Furthermore, metadata sources are often loosely coupled and potentially may lead to an end-user inconsistency in combined information queries. To aggregate and synthesize a range of primary metadata sources, and enhance them with flexible schema-less addition of aggregated data, we are developing the Data Knowledge Base architecture serving as the intelligence behind GUIs and APIs.

CMCC Data Distribution Centre

NASA Astrophysics Data System (ADS)

Aloisio, Giovanni; Fiore, Sandro; Negro, A.

2010-05-01

The CMCC Data Distribution Centre (DDC) is the primary entry point (web gateway) to the CMCC. It is a Data Grid Portal providing a ubiquitous and pervasive way to ease data publishing, climate metadata search, datasets discovery, metadata annotation, data access, data aggregation, sub-setting, etc. The grid portal security model includes the use of HTTPS protocol for secure communication with the client (based on X509v3 certificates that must be loaded into the browser) and secure cookies to establish and maintain user sessions. The CMCC DDC is now in a pre-production phase and it is currently used only by internal users (CMCC researchers and climate scientists). The most important component already available in the CMCC DDC is the Search Engine which allows users to perform, through web interfaces, distributed search and discovery activities by introducing one or more of the following search criteria: horizontal extent (which can be specified by interacting with a geographic map), vertical extent, temporal extent, keywords, topics, creation date, etc. By means of this page the user submits the first step of the query process on the metadata DB, then, she can choose one or more datasets retrieving and displaying the complete XML metadata description (from the browser). This way, the second step of the query process is carried out by accessing to a specific XML document of the metadata DB. Finally, through the web interface, the user can access to and download (partially or totally) the data stored on the storage device accessing to OPeNDAP servers and to other available grid storage interfaces. Requests concerning datasets stored in deep storage will be served asynchronously.

CoMetaR: A Collaborative Metadata Repository for Biomedical Research Networks.

PubMed

Stöhr, Mark R; Helm, Gudrun; Majeed, Raphael W; Günther, Andreas

2017-01-01

The German Center for Lung Research (DZL) is a research network with the aim of researching respiratory diseases. To perform consortium-wide queries through one single interface, it requires a uniform conceptual structure. No single terminology covers all our concepts. To achieve a broadly accepted and complete ontology, we developed a platform for collaborative metadata management "CoMetaR". Anyone can browse and discuss the ontology while editing can be performed by authenticated users.

Ontology-Based Search of Genomic Metadata.

PubMed

Fernandez, Javier D; Lenzerini, Maurizio; Masseroli, Marco; Venco, Francesco; Ceri, Stefano

2016-01-01

The Encyclopedia of DNA Elements (ENCODE) is a huge and still expanding public repository of more than 4,000 experiments and 25,000 data files, assembled by a large international consortium since 2007; unknown biological knowledge can be extracted from these huge and largely unexplored data, leading to data-driven genomic, transcriptomic, and epigenomic discoveries. Yet, search of relevant datasets for knowledge discovery is limitedly supported: metadata describing ENCODE datasets are quite simple and incomplete, and not described by a coherent underlying ontology. Here, we show how to overcome this limitation, by adopting an ENCODE metadata searching approach which uses high-quality ontological knowledge and state-of-the-art indexing technologies. Specifically, we developed S.O.S. GeM (http://www.bioinformatics.deib.polimi.it/SOSGeM/), a system supporting effective semantic search and retrieval of ENCODE datasets. First, we constructed a Semantic Knowledge Base by starting with concepts extracted from ENCODE metadata, matched to and expanded on biomedical ontologies integrated in the well-established Unified Medical Language System. We prove that this inference method is sound and complete. Then, we leveraged the Semantic Knowledge Base to semantically search ENCODE data from arbitrary biologists' queries. This allows correctly finding more datasets than those extracted by a purely syntactic search, as supported by the other available systems. We empirically show the relevance of found datasets to the biologists' queries.

Distributed Multi-interface Catalogue for Geospatial Data

NASA Astrophysics Data System (ADS)

Nativi, S.; Bigagli, L.; Mazzetti, P.; Mattia, U.; Boldrini, E.

2007-12-01

Several geosciences communities (e.g. atmospheric science, oceanography, hydrology) have developed tailored data and metadata models and service protocol specifications for enabling online data discovery, inventory, evaluation, access and download. These specifications are conceived either profiling geospatial information standards or extending the well-accepted geosciences data models and protocols in order to capture more semantics. These artifacts have generated a set of related catalog -and inventory services- characterizing different communities, initiatives and projects. In fact, these geospatial data catalogs are discovery and access systems that use metadata as the target for query on geospatial information. The indexed and searchable metadata provide a disciplined vocabulary against which intelligent geospatial search can be performed within or among communities. There exists a clear need to conceive and achieve solutions to implement interoperability among geosciences communities, in the context of the more general geospatial information interoperability framework. Such solutions should provide search and access capabilities across catalogs, inventory lists and their registered resources. Thus, the development of catalog clearinghouse solutions is a near-term challenge in support of fully functional and useful infrastructures for spatial data (e.g. INSPIRE, GMES, NSDI, GEOSS). This implies the implementation of components for query distribution and virtual resource aggregation. These solutions must implement distributed discovery functionalities in an heterogeneous environment, requiring metadata profiles harmonization as well as protocol adaptation and mediation. We present a catalog clearinghouse solution for the interoperability of several well-known cataloguing systems (e.g. OGC CSW, THREDDS catalog and data services). The solution implements consistent resource discovery and evaluation over a dynamic federation of several well-known cataloguing and inventory systems. Prominent features include: 1)Support to distributed queries over a hierarchical data model, supporting incremental queries (i.e. query over collections, to be subsequently refined) and opaque/translucent chaining; 2)Support to several client protocols, through a compound front-end interface module. This allows to accommodate a (growing) number of cataloguing standards, or profiles thereof, including the OGC CSW interface, ebRIM Application Profile (for Core ISO Metadata and other data models), and the ISO Application Profile. The presented catalog clearinghouse supports both the opaque and translucent pattern for service chaining. In fact, the clearinghouse catalog may be configured either to completely hide the underlying federated services or to provide clients with services information. In both cases, the clearinghouse solution presents a higher level interface (i.e. OGC CSW) which harmonizes multiple lower level services (e.g. OGC CSW, WMS and WCS, THREDDS, etc.), and handles all control and interaction with them. In the translucent case, client has the option to directly access the lower level services (e.g. to improve performances). In the GEOSS context, the solution has been experimented both as a stand-alone user application and as a service framework. The first scenario allows a user to download a multi-platform client software and query a federation of cataloguing systems, that he can customize at will. The second scenario support server-side deployment and can be flexibly adapted to several use-cases, such as intranet proxy, catalog broker, etc.

GEMINI: a computationally-efficient search engine for large gene expression datasets.

PubMed

DeFreitas, Timothy; Saddiki, Hachem; Flaherty, Patrick

2016-02-24

Low-cost DNA sequencing allows organizations to accumulate massive amounts of genomic data and use that data to answer a diverse range of research questions. Presently, users must search for relevant genomic data using a keyword, accession number of meta-data tag. However, in this search paradigm the form of the query - a text-based string - is mismatched with the form of the target - a genomic profile. To improve access to massive genomic data resources, we have developed a fast search engine, GEMINI, that uses a genomic profile as a query to search for similar genomic profiles. GEMINI implements a nearest-neighbor search algorithm using a vantage-point tree to store a database of n profiles and in certain circumstances achieves an [Formula: see text] expected query time in the limit. We tested GEMINI on breast and ovarian cancer gene expression data from The Cancer Genome Atlas project and show that it achieves a query time that scales as the logarithm of the number of records in practice on genomic data. In a database with 10(5) samples, GEMINI identifies the nearest neighbor in 0.05 sec compared to a brute force search time of 0.6 sec. GEMINI is a fast search engine that uses a query genomic profile to search for similar profiles in a very large genomic database. It enables users to identify similar profiles independent of sample label, data origin or other meta-data information.

Visualization of historical data for the ATLAS detector controls - DDV

NASA Astrophysics Data System (ADS)

Maciejewski, J.; Schlenker, S.

2017-10-01

The ATLAS experiment is one of four detectors located on the Large Hardon Collider (LHC) based at CERN. Its detector control system (DCS) stores the slow control data acquired within the back-end of distributed WinCC OA applications, which enables the data to be retrieved for future analysis, debugging and detector development in an Oracle relational database. The ATLAS DCS Data Viewer (DDV) is a client-server application providing access to the historical data outside of the experiment network. The server builds optimized SQL queries, retrieves the data from the database and serves it to the clients via HTTP connections. The server also implements protection methods to prevent malicious use of the database. The client is an AJAX-type web application based on the Vaadin (framework build around the Google Web Toolkit (GWT)) which gives users the possibility to access the data with ease. The DCS metadata can be selected using a column-tree navigation or a search engine supporting regular expressions. The data is visualized by a selection of output modules such as a java script value-over time plots or a lazy loading table widget. Additional plugins give the users the possibility to retrieve the data in ROOT format or as an ASCII file. Control system alarms can also be visualized in a dedicated table if necessary. Python mock-up scripts can be generated by the client, allowing the user to query the pythonic DDV server directly, such that the users can embed the scripts into more complex analysis programs. Users are also able to store searches and output configurations as XML on the server to share with others via URL or to embed in HTML.

ASIST 2003: Part III: Posters.

ERIC Educational Resources Information Center

Proceedings of the ASIST Annual Meeting, 2003

2003-01-01

Twenty-three posters address topics including access to information; metadata; personal information management; scholarly information communication; online resources; content analysis; interfaces; Web queries; information evaluation; informatics; information needs; search effectiveness; digital libraries; diversity; automated indexing; e-commerce;…

Metadata management and semantics in microarray repositories.

PubMed

Kocabaş, F; Can, T; Baykal, N

2011-12-01

The number of microarray and other high-throughput experiments on primary repositories keeps increasing as do the size and complexity of the results in response to biomedical investigations. Initiatives have been started on standardization of content, object model, exchange format and ontology. However, there are backlogs and inability to exchange data between microarray repositories, which indicate that there is a great need for a standard format and data management. We have introduced a metadata framework that includes a metadata card and semantic nets that make experimental results visible, understandable and usable. These are encoded in syntax encoding schemes and represented in RDF (Resource Description Frame-word), can be integrated with other metadata cards and semantic nets, and can be exchanged, shared and queried. We demonstrated the performance and potential benefits through a case study on a selected microarray repository. We concluded that the backlogs can be reduced and that exchange of information and asking of knowledge discovery questions can become possible with the use of this metadata framework.

Using RDF and Git to Realize a Collaborative Metadata Repository.

PubMed

Stöhr, Mark R; Majeed, Raphael W; Günther, Andreas

2018-01-01

The German Center for Lung Research (DZL) is a research network with the aim of researching respiratory diseases. The participating study sites' register data differs in terms of software and coding system as well as data field coverage. To perform meaningful consortium-wide queries through one single interface, a uniform conceptual structure is required covering the DZL common data elements. No single existing terminology includes all our concepts. Potential candidates such as LOINC and SNOMED only cover specific subject areas or are not granular enough for our needs. To achieve a broadly accepted and complete ontology, we developed a platform for collaborative metadata management. The DZL data management group formulated detailed requirements regarding the metadata repository and the user interfaces for metadata editing. Our solution builds upon existing standard technologies allowing us to meet those requirements. Its key parts are RDF and the distributed version control system Git. We developed a software system to publish updated metadata automatically and immediately after performing validation tests for completeness and consistency.

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.

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.

A Dimensional Bus model for integrating clinical and research data.

PubMed

Wade, Ted D; Hum, Richard C; Murphy, James R

2011-12-01

Many clinical research data integration platforms rely on the Entity-Attribute-Value model because of its flexibility, even though it presents problems in query formulation and execution time. The authors sought more balance in these traits. Borrowing concepts from Entity-Attribute-Value and from enterprise data warehousing, the authors designed an alternative called the Dimensional Bus model and used it to integrate electronic medical record, sponsored study, and biorepository data. Each type of observational collection has its own table, and the structure of these tables varies to suit the source data. The observational tables are linked to the Bus, which holds provenance information and links to various classificatory dimensions that amplify the meaning of the data or facilitate its query and exposure management. The authors implemented a Bus-based clinical research data repository with a query system that flexibly manages data access and confidentiality, facilitates catalog search, and readily formulates and compiles complex queries. The design provides a workable way to manage and query mixed schemas in a data warehouse.

Clustering header categories extracted from web tables

NASA Astrophysics Data System (ADS)

Nagy, George; Embley, David W.; Krishnamoorthy, Mukkai; Seth, Sharad

2015-01-01

Revealing related content among heterogeneous web tables is part of our long term objective of formulating queries over multiple sources of information. Two hundred HTML tables from institutional web sites are segmented and each table cell is classified according to the fundamental indexing property of row and column headers. The categories that correspond to the multi-dimensional data cube view of a table are extracted by factoring the (often multi-row/column) headers. To reveal commonalities between tables from diverse sources, the Jaccard distances between pairs of category headers (and also table titles) are computed. We show how about one third of our heterogeneous collection can be clustered into a dozen groups that exhibit table-title and header similarities that can be exploited for queries.

Integrating a local database into the StarView distributed user interface

NASA Technical Reports Server (NTRS)

Silberberg, D. P.

1992-01-01

A distributed user interface to the Space Telescope Data Archive and Distribution Service (DADS) known as StarView is being developed. The DADS architecture consists of the data archive as well as a relational database catalog describing the archive. StarView is a client/server system in which the user interface is the front-end client to the DADS catalog and archive servers. Users query the DADS catalog from the StarView interface. Query commands are transmitted via a network and evaluated by the database. The results are returned via the network and are displayed on StarView forms. Based on the results, users decide which data sets to retrieve from the DADS archive. Archive requests are packaged by StarView and sent to DADS, which returns the requested data sets to the users. The advantages of distributed client/server user interfaces over traditional one-machine systems are well known. Since users run software on machines separate from the database, the overall client response time is much faster. Also, since the server is free to process only database requests, the database response time is much faster. Disadvantages inherent in this architecture are slow overall database access time due to the network delays, lack of a 'get previous row' command, and that refinements of a previously issued query must be submitted to the database server, even though the domain of values have already been returned by the previous query. This architecture also does not allow users to cross correlate DADS catalog data with other catalogs. Clearly, a distributed user interface would be more powerful if it overcame these disadvantages. A local database is being integrated into StarView to overcome these disadvantages. When a query is made through a StarView form, which is often composed of fields from multiple tables, it is translated to an SQL query and issued to the DADS catalog. At the same time, a local database table is created to contain the resulting rows of the query. The returned rows are displayed on the form as well as inserted into the local database table. Identical results are produced by reissuing the query to either the DADS catalog or to the local table. Relational databases do not provide a 'get previous row' function because of the inherent complexity of retrieving previous rows of multiple-table joins. However, since this function is easily implemented on a single table, StarView uses the local table to retrieve the previous row. Also, StarView issues subsequent query refinements to the local table instead of the DADS catalog, eliminating the network transmission overhead. Finally, other catalogs can be imported into the local database for cross correlation with local tables. Overall, it is believe that this is a more powerful architecture for distributed, database user interfaces.

An asynchronous traversal engine for graph-based rich metadata management

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

Dai, Dong; Carns, Philip; Ross, Robert B.

Rich metadata in high-performance computing (HPC) systems contains extended information about users, jobs, data files, and their relationships. Property graphs are a promising data model to represent heterogeneous rich metadata flexibly. Specifically, a property graph can use vertices to represent different entities and edges to record the relationships between vertices with unique annotations. The high-volume HPC use case, with millions of entities and relationships, naturally requires an out-of-core distributed property graph database, which must support live updates (to ingest production information in real time), low-latency point queries (for frequent metadata operations such as permission checking), and large-scale traversals (for provenancemore » data mining). Among these needs, large-scale property graph traversals are particularly challenging for distributed graph storage systems. Most existing graph systems implement a "level synchronous" breadth-first search algorithm that relies on global synchronization in each traversal step. This performs well in many problem domains; but a rich metadata management system is characterized by imbalanced graphs, long traversal lengths, and concurrent workloads, each of which has the potential to introduce or exacerbate stragglers (i.e., abnormally slow steps or servers in a graph traversal) that lead to low overall throughput for synchronous traversal algorithms. Previous research indicated that the straggler problem can be mitigated by using asynchronous traversal algorithms, and many graph-processing frameworks have successfully demonstrated this approach. Such systems require the graph to be loaded into a separate batch-processing framework instead of being iteratively accessed, however. In this work, we investigate a general asynchronous graph traversal engine that can operate atop a rich metadata graph in its native format. We outline a traversal-aware query language and key optimizations (traversal-affiliate caching and execution merging) necessary for efficient performance. We further explore the effect of different graph partitioning strategies on the traversal performance for both synchronous and asynchronous traversal engines. Our experiments show that the asynchronous graph traversal engine is more efficient than its synchronous counterpart in the case of HPC rich metadata processing, where more servers are involved and larger traversals are needed. Furthermore, the asynchronous traversal engine is more adaptive to different graph partitioning strategies.« less

An asynchronous traversal engine for graph-based rich metadata management

DOE PAGES

Dai, Dong; Carns, Philip; Ross, Robert B.; ...

2016-06-23

Rich metadata in high-performance computing (HPC) systems contains extended information about users, jobs, data files, and their relationships. Property graphs are a promising data model to represent heterogeneous rich metadata flexibly. Specifically, a property graph can use vertices to represent different entities and edges to record the relationships between vertices with unique annotations. The high-volume HPC use case, with millions of entities and relationships, naturally requires an out-of-core distributed property graph database, which must support live updates (to ingest production information in real time), low-latency point queries (for frequent metadata operations such as permission checking), and large-scale traversals (for provenancemore » data mining). Among these needs, large-scale property graph traversals are particularly challenging for distributed graph storage systems. Most existing graph systems implement a "level synchronous" breadth-first search algorithm that relies on global synchronization in each traversal step. This performs well in many problem domains; but a rich metadata management system is characterized by imbalanced graphs, long traversal lengths, and concurrent workloads, each of which has the potential to introduce or exacerbate stragglers (i.e., abnormally slow steps or servers in a graph traversal) that lead to low overall throughput for synchronous traversal algorithms. Previous research indicated that the straggler problem can be mitigated by using asynchronous traversal algorithms, and many graph-processing frameworks have successfully demonstrated this approach. Such systems require the graph to be loaded into a separate batch-processing framework instead of being iteratively accessed, however. In this work, we investigate a general asynchronous graph traversal engine that can operate atop a rich metadata graph in its native format. We outline a traversal-aware query language and key optimizations (traversal-affiliate caching and execution merging) necessary for efficient performance. We further explore the effect of different graph partitioning strategies on the traversal performance for both synchronous and asynchronous traversal engines. Our experiments show that the asynchronous graph traversal engine is more efficient than its synchronous counterpart in the case of HPC rich metadata processing, where more servers are involved and larger traversals are needed. Furthermore, the asynchronous traversal engine is more adaptive to different graph partitioning strategies.« less

Keeping Dublin Core Simple: Cross-Domain Discovery or Resource Description?; First Steps in an Information Commerce Economy: Digital Rights Management in the Emerging E-Book Environment; Interoperability: Digital Rights Management and the Emerging EBook Environment; Searching the Deep Web: Direct Query Engine Applications at the Department of Energy.

ERIC Educational Resources Information Center

Lagoze, Carl; Neylon, Eamonn; Mooney, Stephen; Warnick, Walter L.; Scott, R. L.; Spence, Karen J.; Johnson, Lorrie A.; Allen, Valerie S.; Lederman, Abe

2001-01-01

Includes four articles that discuss Dublin Core metadata, digital rights management and electronic books, including interoperability; and directed query engines, a type of search engine designed to access resources on the deep Web that is being used at the Department of Energy. (LRW)

Building a Smart Portal for Astronomy

NASA Astrophysics Data System (ADS)

Derriere, S.; Boch, T.

2011-07-01

The development of a portal for accessing astronomical resources is not an easy task. The ever-increasing complexity of the data products can result in very complex user interfaces, requiring a lot of effort and learning from the user in order to perform searches. This is often a design choice, where the user must explicitly set many constraints, while the portal search logic remains simple. We investigated a different approach, where the query interface is kept as simple as possible (ideally, a simple text field, like for Google search), and the search logic is made much more complex to interpret the query in a relevant manner. We will present the implications of this approach in terms of interpretation and categorization of the query parameters (related to astronomical vocabularies), translation (mapping) of these concepts into the portal components metadata, identification of query schemes and use cases matching the input parameters, and delivery of query results to the user.

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.

Querying Safety Cases

NASA Technical Reports Server (NTRS)

Denney, Ewen W.; Naylor, Dwight; Pai, Ganesh

2014-01-01

Querying a safety case to show how the various stakeholders' concerns about system safety are addressed has been put forth as one of the benefits of argument-based assurance (in a recent study by the Health Foundation, UK, which reviewed the use of safety cases in safety-critical industries). However, neither the literature nor current practice offer much guidance on querying mechanisms appropriate for, or available within, a safety case paradigm. This paper presents a preliminary approach that uses a formal basis for querying safety cases, specifically Goal Structuring Notation (GSN) argument structures. Our approach semantically enriches GSN arguments with domain-specific metadata that the query language leverages, along with its inherent structure, to produce views. We have implemented the approach in our toolset AdvoCATE, and illustrate it by application to a fragment of the safety argument for an Unmanned Aircraft System (UAS) being developed at NASA Ames. We also discuss the potential practical utility of our query mechanism within the context of the existing framework for UAS safety assurance.

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.

A Dimensional Bus model for integrating clinical and research data

PubMed Central

Hum, Richard C; Murphy, James R

2011-01-01

Objectives Many clinical research data integration platforms rely on the Entity–Attribute–Value model because of its flexibility, even though it presents problems in query formulation and execution time. The authors sought more balance in these traits. Materials and Methods Borrowing concepts from Entity–Attribute–Value and from enterprise data warehousing, the authors designed an alternative called the Dimensional Bus model and used it to integrate electronic medical record, sponsored study, and biorepository data. Each type of observational collection has its own table, and the structure of these tables varies to suit the source data. The observational tables are linked to the Bus, which holds provenance information and links to various classificatory dimensions that amplify the meaning of the data or facilitate its query and exposure management. Results The authors implemented a Bus-based clinical research data repository with a query system that flexibly manages data access and confidentiality, facilitates catalog search, and readily formulates and compiles complex queries. Conclusion The design provides a workable way to manage and query mixed schemas in a data warehouse. PMID:21856687

Operational Support for Instrument Stability through ODI-PPA Metadata Visualization and Analysis

NASA Astrophysics Data System (ADS)

Young, M. D.; Hayashi, S.; Gopu, A.; Kotulla, R.; Harbeck, D.; Liu, W.

2015-09-01

Over long time scales, quality assurance metrics taken from calibration and calibrated data products can aid observatory operations in quantifying the performance and stability of the instrument, and identify potential areas of concern or guide troubleshooting and engineering efforts. Such methods traditionally require manual SQL entries, assuming the requisite metadata has even been ingested into a database. With the ODI-PPA system, QA metadata has been harvested and indexed for all data products produced over the life of the instrument. In this paper we will describe how, utilizing the industry standard Highcharts Javascript charting package with a customized AngularJS-driven user interface, we have made the process of visualizing the long-term behavior of these QA metadata simple and easily replicated. Operators can easily craft a custom query using the powerful and flexible ODI-PPA search interface and visualize the associated metadata in a variety of ways. These customized visualizations can be bookmarked, shared, or embedded externally, and will be dynamically updated as new data products enter the system, enabling operators to monitor the long-term health of their instrument with ease.

Data Model and Relational Database Design for Highway Runoff Water-Quality Metadata

USGS Publications Warehouse

Granato, Gregory E.; Tessler, Steven

2001-01-01

A National highway and urban runoff waterquality metadatabase was developed by the U.S. Geological Survey in cooperation with the Federal Highway Administration as part of the National Highway Runoff Water-Quality Data and Methodology Synthesis (NDAMS). The database was designed to catalog available literature and to document results of the synthesis in a format that would facilitate current and future research on highway and urban runoff. This report documents the design and implementation of the NDAMS relational database, which was designed to provide a catalog of available information and the results of an assessment of the available data. All the citations and the metadata collected during the review process are presented in a stratified metadatabase that contains citations for relevant publications, abstracts (or previa), and reportreview metadata for a sample of selected reports that document results of runoff quality investigations. The database is referred to as a metadatabase because it contains information about available data sets rather than a record of the original data. The database contains the metadata needed to evaluate and characterize how valid, current, complete, comparable, and technically defensible published and available information may be when evaluated for application to the different dataquality objectives as defined by decision makers. This database is a relational database, in that all information is ultimately linked to a given citation in the catalog of available reports. The main database file contains 86 tables consisting of 29 data tables, 11 association tables, and 46 domain tables. The data tables all link to a particular citation, and each data table is focused on one aspect of the information collected in the literature search and the evaluation of available information. This database is implemented in the Microsoft (MS) Access database software because it is widely used within and outside of government and is familiar to many existing and potential customers. The stratified metadatabase design for the NDAMS program is presented in the MS Access file DBDESIGN.mdb and documented with a data dictionary in the NDAMS_DD.mdb file recorded on the CD-ROM. The data dictionary file includes complete documentation of the table names, table descriptions, and information about each of the 419 fields in the database.

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.

Microsoft Repository Version 2 and the Open Information Model.

ERIC Educational Resources Information Center

Bernstein, Philip A.; Bergstraesser, Thomas; Carlson, Jason; Pal, Shankar; Sanders, Paul; Shutt, David

1999-01-01

Describes the programming interface and implementation of the repository engine and the Open Information Model for Microsoft Repository, an object-oriented meta-data management facility that ships in Microsoft Visual Studio and Microsoft SQL Server. Discusses Microsoft's component object model, object manipulation, queries, and information…

a Novel Approach of Indexing and Retrieving Spatial Polygons for Efficient Spatial Region Queries

NASA Astrophysics Data System (ADS)

Zhao, J. H.; Wang, X. Z.; Wang, F. Y.; Shen, Z. H.; Zhou, Y. C.; Wang, Y. L.

2017-10-01

Spatial region queries are more and more widely used in web-based applications. Mechanisms to provide efficient query processing over geospatial data are essential. However, due to the massive geospatial data volume, heavy geometric computation, and high access concurrency, it is difficult to get response in real time. Spatial indexes are usually used in this situation. In this paper, based on k-d tree, we introduce a distributed KD-Tree (DKD-Tree) suitbable for polygon data, and a two-step query algorithm. The spatial index construction is recursive and iterative, and the query is an in memory process. Both the index and query methods can be processed in parallel, and are implemented based on HDFS, Spark and Redis. Experiments on a large volume of Remote Sensing images metadata have been carried out, and the advantages of our method are investigated by comparing with spatial region queries executed on PostgreSQL and PostGIS. Results show that our approach not only greatly improves the efficiency of spatial region query, but also has good scalability, Moreover, the two-step spatial range query algorithm can also save cluster resources to support a large number of concurrent queries. Therefore, this method is very useful when building large geographic information systems.

Shark: Fast Data Analysis Using Coarse-grained Distributed Memory

DTIC Science & Technology

2013-05-01

Schemes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 7.1.1 Java Objects...often MySQL or Derby) with a namespace for tables, table metadata, and par- tition information. Table data is stored in an HDFS directory, while a...saving time and space for large data sets. This is achieved with support for custom SerDe (serialization/deserialization) java interface implementations

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.

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.

From Ambiguities to Insights: Query-based Comparisons of High-Dimensional Data

NASA Astrophysics Data System (ADS)

Kowalski, Jeanne; Talbot, Conover; Tsai, Hua L.; Prasad, Nijaguna; Umbricht, Christopher; Zeiger, Martha A.

2007-11-01

Genomic technologies will revolutionize drag discovery and development; that much is universally agreed upon. The high dimension of data from such technologies has challenged available data analytic methods; that much is apparent. To date, large-scale data repositories have not been utilized in ways that permit their wealth of information to be efficiently processed for knowledge, presumably due in large part to inadequate analytical tools to address numerous comparisons of high-dimensional data. In candidate gene discovery, expression comparisons are often made between two features (e.g., cancerous versus normal), such that the enumeration of outcomes is manageable. With multiple features, the setting becomes more complex, in terms of comparing expression levels of tens of thousands transcripts across hundreds of features. In this case, the number of outcomes, while enumerable, become rapidly large and unmanageable, and scientific inquiries become more abstract, such as "which one of these (compounds, stimuli, etc.) is not like the others?" We develop analytical tools that promote more extensive, efficient, and rigorous utilization of the public data resources generated by the massive support of genomic studies. Our work innovates by enabling access to such metadata with logically formulated scientific inquires that define, compare and integrate query-comparison pair relations for analysis. We demonstrate our computational tool's potential to address an outstanding biomedical informatics issue of identifying reliable molecular markers in thyroid cancer. Our proposed query-based comparison (QBC) facilitates access to and efficient utilization of metadata through logically formed inquires expressed as query-based comparisons by organizing and comparing results from biotechnologies to address applications in biomedicine.

Heuristic query optimization for query multiple table and multiple clausa on mobile finance application

NASA Astrophysics Data System (ADS)

Indrayana, I. N. E.; P, N. M. Wirasyanti D.; Sudiartha, I. KG

2018-01-01

Mobile application allow many users to access data from the application without being limited to space, space and time. Over time the data population of this application will increase. Data access time will cause problems if the data record has reached tens of thousands to millions of records.The objective of this research is to maintain the performance of data execution for large data records. One effort to maintain data access time performance is to apply query optimization method. The optimization used in this research is query heuristic optimization method. The built application is a mobile-based financial application using MySQL database with stored procedure therein. This application is used by more than one business entity in one database, thus enabling rapid data growth. In this stored procedure there is an optimized query using heuristic method. Query optimization is performed on a “Select” query that involves more than one table with multiple clausa. Evaluation is done by calculating the average access time using optimized and unoptimized queries. Access time calculation is also performed on the increase of population data in the database. The evaluation results shown the time of data execution with query heuristic optimization relatively faster than data execution time without using query optimization.

DAS: A Data Management System for Instrument Tests and Operations

NASA Astrophysics Data System (ADS)

Frailis, M.; Sartor, S.; Zacchei, A.; Lodi, M.; Cirami, R.; Pasian, F.; Trifoglio, M.; Bulgarelli, A.; Gianotti, F.; Franceschi, E.; Nicastro, L.; Conforti, V.; Zoli, A.; Smart, R.; Morbidelli, R.; Dadina, M.

2014-05-01

The Data Access System (DAS) is a and data management software system, providing a reusable solution for the storage of data acquired both from telescopes and auxiliary data sources during the instrument development phases and operations. It is part of the Customizable Instrument WorkStation system (CIWS-FW), a framework for the storage, processing and quick-look at the data acquired from scientific instruments. The DAS provides a data access layer mainly targeted to software applications: quick-look displays, pre-processing pipelines and scientific workflows. It is logically organized in three main components: an intuitive and compact Data Definition Language (DAS DDL) in XML format, aimed for user-defined data types; an Application Programming Interface (DAS API), automatically adding classes and methods supporting the DDL data types, and providing an object-oriented query language; a data management component, which maps the metadata of the DDL data types in a relational Data Base Management System (DBMS), and stores the data in a shared (network) file system. With the DAS DDL, developers define the data model for a particular project, specifying for each data type the metadata attributes, the data format and layout (if applicable), and named references to related or aggregated data types. Together with the DDL user-defined data types, the DAS API acts as the only interface to store, query and retrieve the metadata and data in the DAS system, providing both an abstract interface and a data model specific one in C, C++ and Python. The mapping of metadata in the back-end database is automatic and supports several relational DBMSs, including MySQL, Oracle and PostgreSQL.

A semantically rich and standardised approach enhancing discovery of sensor data and metadata

NASA Astrophysics Data System (ADS)

Kokkinaki, Alexandra; Buck, Justin; Darroch, Louise

2016-04-01

The marine environment plays an essential role in the earth's climate. To enhance the ability to monitor the health of this important system, innovative sensors are being produced and combined with state of the art sensor technology. As the number of sensors deployed is continually increasing,, it is a challenge for data users to find the data that meet their specific needs. Furthermore, users need to integrate diverse ocean datasets originating from the same or even different systems. Standards provide a solution to the above mentioned challenges. The Open Geospatial Consortium (OGC) has created Sensor Web Enablement (SWE) standards that enable different sensor networks to establish syntactic interoperability. When combined with widely accepted controlled vocabularies, they become semantically rich and semantic interoperability is achievable. In addition, Linked Data is the recommended best practice for exposing, sharing and connecting information on the Semantic Web using Uniform Resource Identifiers (URIs), Resource Description Framework (RDF) and RDF Query Language (SPARQL). As part of the EU-funded SenseOCEAN project, the British Oceanographic Data Centre (BODC) is working on the standardisation of sensor metadata enabling 'plug and play' sensor integration. Our approach combines standards, controlled vocabularies and persistent URIs to publish sensor descriptions, their data and associated metadata as 5 star Linked Data and OGC SWE (SensorML, Observations & Measurements) standard. Thus sensors become readily discoverable, accessible and useable via the web. Content and context based searching is also enabled since sensors descriptions are understood by machines. Additionally, sensor data can be combined with other sensor or Linked Data datasets to form knowledge. This presentation will describe the work done in BODC to achieve syntactic and semantic interoperability in the sensor domain. It will illustrate the reuse and extension of the Semantic Sensor Network (SSN) ontology to Linked Sensor Ontology (LSO) and the steps taken to combine OGC SWE with the Linked Data approach through alignment and embodiment of other ontologies. It will then explain how data and models were annotated with controlled vocabularies to establish unambiguous semantics and interconnect them with data from different sources. Finally, it will introduce the RDF triple store where the sensor descriptions and metadata are stored and can be queried through the standard query language SPARQL. Providing different flavours of machine readable interpretations of sensors, sensor data and metadata enhances discoverability but most importantly allows seamless aggregation of information from different networks that will finally produce knowledge.

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.

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.

HodDB: Design and Analysis of a Query Processor for Brick.

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

Fierro, Gabriel; Culler, David

Brick is a recently proposed metadata schema and ontology for describing building components and the relationships between them. It represents buildings as directed labeled graphs using the RDF data model. Using the SPARQL query language, building-agnostic applications query a Brick graph to discover the set of resources and relationships they require to operate. Latency-sensitive applications, such as user interfaces, demand response and modelpredictive control, require fast queries — conventionally less than 100ms. We benchmark a set of popular open-source and commercial SPARQL databases against three real Brick models using seven application queries and find that none of them meet thismore » performance target. This lack of performance can be attributed to design decisions that optimize for queries over large graphs consisting of billions of triples, but give poor spatial locality and join performance on the small dense graphs typical of Brick. We present the design and evaluation of HodDB, a RDF/SPARQL database for Brick built over a node-based index structure. HodDB performs Brick queries 3-700x faster than leading SPARQL databases and consistently meets the 100ms threshold, enabling the portability of important latency-sensitive building applications.« less

Metadata and network API aspects of a framework for storing and retrieving civil infrastructure monitoring data

NASA Astrophysics Data System (ADS)

Wong, John-Michael; Stojadinovic, Bozidar

2005-05-01

A framework has been defined for storing and retrieving civil infrastructure monitoring data over a network. The framework consists of two primary components: metadata and network communications. The metadata component provides the descriptions and data definitions necessary for cataloging and searching monitoring data. The communications component provides Java classes for remotely accessing the data. Packages of Enterprise JavaBeans and data handling utility classes are written to use the underlying metadata information to build real-time monitoring applications. The utility of the framework was evaluated using wireless accelerometers on a shaking table earthquake simulation test of a reinforced concrete bridge column. The NEESgrid data and metadata repository services were used as a backend storage implementation. A web interface was created to demonstrate the utility of the data model and provides an example health monitoring application.

BP Spill Sampling and Monitoring Data

EPA Pesticide Factsheets

This dataset analyzes waste from the the British Petroleum Deepwater Horizon Rig Explosion Emergency Response, providing opportunity to query data sets by metadata criteria and find resulting raw datasets in CSV format.The data query tool allows users to download EPA's air, water and sediment sampling and monitoring data that has been collected in response to the BP oil spill. All sampling and monitoring data that has been collected to date is available for download as raw structured data.The query tools enables CSV file creation to be refined based on the following search criteria: date range (between April 28, 2010 and 9/29/2010); location by zip, city, or county; media (solid waste, weathered oil, air, surface water, liquid waste, tar, sediment, water); substance categories (based on media selection) and substances (based on substance category selection).

Using Common Table Expressions to Build a Scalable Boolean Query Generator for Clinical Data Warehouses

PubMed Central

Harris, Daniel R.; Henderson, Darren W.; Kavuluru, Ramakanth; Stromberg, Arnold J.; Johnson, Todd R.

2015-01-01

We present a custom, Boolean query generator utilizing common-table expressions (CTEs) that is capable of scaling with big datasets. The generator maps user-defined Boolean queries, such as those interactively created in clinical-research and general-purpose healthcare tools, into SQL. We demonstrate the effectiveness of this generator by integrating our work into the Informatics for Integrating Biology and the Bedside (i2b2) query tool and show that it is capable of scaling. Our custom generator replaces and outperforms the default query generator found within the Clinical Research Chart (CRC) cell of i2b2. In our experiments, sixteen different types of i2b2 queries were identified by varying four constraints: date, frequency, exclusion criteria, and whether selected concepts occurred in the same encounter. We generated non-trivial, random Boolean queries based on these 16 types; the corresponding SQL queries produced by both generators were compared by execution times. The CTE-based solution significantly outperformed the default query generator and provided a much more consistent response time across all query types (M=2.03, SD=6.64 vs. M=75.82, SD=238.88 seconds). Without costly hardware upgrades, we provide a scalable solution based on CTEs with very promising empirical results centered on performance gains. The evaluation methodology used for this provides a means of profiling clinical data warehouse performance. PMID:25192572

Integrated Array/Metadata Analytics

NASA Astrophysics Data System (ADS)

Misev, Dimitar; Baumann, Peter

2015-04-01

Data comes in various forms and types, and integration usually presents a problem that is often simply ignored and solved with ad-hoc solutions. Multidimensional arrays are an ubiquitous data type, that we find at the core of virtually all science and engineering domains, as sensor, model, image, statistics data. Naturally, arrays are richly described by and intertwined with additional metadata (alphanumeric relational data, XML, JSON, etc). Database systems, however, a fundamental building block of what we call "Big Data", lack adequate support for modelling and expressing these array data/metadata relationships. Array analytics is hence quite primitive or non-existent at all in modern relational DBMS. Recognizing this, we extended SQL with a new SQL/MDA part seamlessly integrating multidimensional array analytics into the standard database query language. We demonstrate the benefits of SQL/MDA with real-world examples executed in ASQLDB, an open-source mediator system based on HSQLDB and rasdaman, that already implements SQL/MDA.

SnoVault and encodeD: A novel object-based storage system and applications to ENCODE metadata.

PubMed

Hitz, Benjamin C; Rowe, Laurence D; Podduturi, Nikhil R; Glick, David I; Baymuradov, Ulugbek K; Malladi, Venkat S; Chan, Esther T; Davidson, Jean M; Gabdank, Idan; Narayana, Aditi K; Onate, Kathrina C; Hilton, Jason; Ho, Marcus C; Lee, Brian T; Miyasato, Stuart R; Dreszer, Timothy R; Sloan, Cricket A; Strattan, J Seth; Tanaka, Forrest Y; Hong, Eurie L; Cherry, J Michael

2017-01-01

The Encyclopedia of DNA elements (ENCODE) project is an ongoing collaborative effort to create a comprehensive catalog of functional elements initiated shortly after the completion of the Human Genome Project. The current database exceeds 6500 experiments across more than 450 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the H. sapiens and M. musculus genomes. All ENCODE experimental data, metadata, and associated computational analyses are submitted to the ENCODE Data Coordination Center (DCC) for validation, tracking, storage, unified processing, and distribution to community resources and the scientific community. As the volume of data increases, the identification and organization of experimental details becomes increasingly intricate and demands careful curation. The ENCODE DCC has created a general purpose software system, known as SnoVault, that supports metadata and file submission, a database used for metadata storage, web pages for displaying the metadata and a robust API for querying the metadata. The software is fully open-source, code and installation instructions can be found at: http://github.com/ENCODE-DCC/snovault/ (for the generic database) and http://github.com/ENCODE-DCC/encoded/ to store genomic data in the manner of ENCODE. The core database engine, SnoVault (which is completely independent of ENCODE, genomic data, or bioinformatic data) has been released as a separate Python package.

SnoVault and encodeD: A novel object-based storage system and applications to ENCODE metadata

PubMed Central

Podduturi, Nikhil R.; Glick, David I.; Baymuradov, Ulugbek K.; Malladi, Venkat S.; Chan, Esther T.; Davidson, Jean M.; Gabdank, Idan; Narayana, Aditi K.; Onate, Kathrina C.; Hilton, Jason; Ho, Marcus C.; Lee, Brian T.; Miyasato, Stuart R.; Dreszer, Timothy R.; Sloan, Cricket A.; Strattan, J. Seth; Tanaka, Forrest Y.; Hong, Eurie L.; Cherry, J. Michael

2017-01-01

The Encyclopedia of DNA elements (ENCODE) project is an ongoing collaborative effort to create a comprehensive catalog of functional elements initiated shortly after the completion of the Human Genome Project. The current database exceeds 6500 experiments across more than 450 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the H. sapiens and M. musculus genomes. All ENCODE experimental data, metadata, and associated computational analyses are submitted to the ENCODE Data Coordination Center (DCC) for validation, tracking, storage, unified processing, and distribution to community resources and the scientific community. As the volume of data increases, the identification and organization of experimental details becomes increasingly intricate and demands careful curation. The ENCODE DCC has created a general purpose software system, known as SnoVault, that supports metadata and file submission, a database used for metadata storage, web pages for displaying the metadata and a robust API for querying the metadata. The software is fully open-source, code and installation instructions can be found at: http://github.com/ENCODE-DCC/snovault/ (for the generic database) and http://github.com/ENCODE-DCC/encoded/ to store genomic data in the manner of ENCODE. The core database engine, SnoVault (which is completely independent of ENCODE, genomic data, or bioinformatic data) has been released as a separate Python package. PMID:28403240

Analytics-Driven Lossless Data Compression for Rapid In-situ Indexing, Storing, and Querying

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

Jenkins, John; Arkatkar, Isha; Lakshminarasimhan, Sriram

2013-01-01

The analysis of scientific simulations is highly data-intensive and is becoming an increasingly important challenge. Peta-scale data sets require the use of light-weight query-driven analysis methods, as opposed to heavy-weight schemes that optimize for speed at the expense of size. This paper is an attempt in the direction of query processing over losslessly compressed scientific data. We propose a co-designed double-precision compression and indexing methodology for range queries by performing unique-value-based binning on the most significant bytes of double precision data (sign, exponent, and most significant mantissa bits), and inverting the resulting metadata to produce an inverted index over amore » reduced data representation. Without the inverted index, our method matches or improves compression ratios over both general-purpose and floating-point compression utilities. The inverted index is light-weight, and the overall storage requirement for both reduced column and index is less than 135%, whereas existing DBMS technologies can require 200-400%. As a proof-of-concept, we evaluate univariate range queries that additionally return column values, a critical component of data analytics, against state-of-the-art bitmap indexing technology, showing multi-fold query performance improvements.« less

The Self-Organized Archive: SPASE, PDS and Archive Cooperatives

NASA Astrophysics Data System (ADS)

King, T. A.; Hughes, J. S.; Roberts, D. A.; Walker, R. J.; Joy, S. P.

2005-05-01

Information systems with high quality metadata enable uses and services which often go beyond the original purpose. There are two types of metadata: annotations which are items that comment on or describe the content of a resource and identification attributes which describe the external properties of the resource itself. For example, annotations may indicate which columns are present in a table of data, whereas an identification attribute would indicate source of the table, such as the observatory, instrument, organization, and data type. When the identification attributes are collected and used as the basis of a search engine, a user can constrain on an attribute, the archive can then self-organize around the constraint, presenting the user with a particular view of the archive. In an archive cooperative where each participating data system or archive may have its own metadata standards, providing a multi-system search engine requires that individual archive metadata be mapped to a broad based standard. To explore how cooperative archives can form a larger self-organized archive we will show how the Space Physics Archive Search and Extract (SPASE) data model will allow different systems to create a cooperative and will use Planetary Data System (PDS) plus existing space physics activities as a demonstration.

A SensorML-based Metadata Model and Registry for Ocean Observatories: a Contribution from European Projects NeXOS and FixO3

NASA Astrophysics Data System (ADS)

Delory, E.; Jirka, S.

2016-02-01

Discovering sensors and observation data is important when enabling the exchange of oceanographic data between observatories and scientists that need the data sets for their work. To better support this discovery process, one task of the European project FixO3 (Fixed-point Open Ocean Observatories) is dealing with the question which elements are needed for developing a better registry for sensors. This has resulted in four items which are addressed by the FixO3 project in cooperation with further European projects such as NeXOS (http://www.nexosproject.eu/). 1.) Metadata description format: To store and retrieve information about sensors and platforms it is necessary to have a common approach how to provide and encode the metadata. For this purpose, the OGC Sensor Model Language (SensorML) 2.0 standard was selected. Especially the opportunity to distinguish between sensor types and instances offers new chances for a more efficient provision and maintenance of sensor metadata. 2.) Conversion of existing metadata into a SensorML 2.0 representation: In order to ensure a sustainable re-use of already provided metadata content (e.g. from ESONET-FixO3 yellow pages), it is important to provide a mechanism which is capable of transforming these already available metadata sets into the new SensorML 2.0 structure. 3.) Metadata editor: To create descriptions of sensors and platforms, it is not possible to expect users to manually edit XML-based description files. Thus, a visual interface is necessary to help during the metadata creation. We will outline a prototype of this editor, building upon the development of the ESONET sensor registry interface. 4.) Sensor Metadata Store: A server is needed that for storing and querying the created sensor descriptions. For this purpose different options exist which will be discussed. In summary, we will present a set of different elements enabling sensor discovery ranging from metadata formats, metadata conversion and editing to metadata storage. Furthermore, the current development status will be demonstrated.

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

A digital repository with an extensible data model for biobanking and genomic analysis management.

PubMed

Izzo, Massimiliano; Mortola, Francesco; Arnulfo, Gabriele; Fato, Marco M; Varesio, Luigi

2014-01-01

Molecular biology laboratories require extensive metadata to improve data collection and analysis. The heterogeneity of the collected metadata grows as research is evolving in to international multi-disciplinary collaborations and increasing data sharing among institutions. Single standardization is not feasible and it becomes crucial to develop digital repositories with flexible and extensible data models, as in the case of modern integrated biobanks management. We developed a novel data model in JSON format to describe heterogeneous data in a generic biomedical science scenario. The model is built on two hierarchical entities: processes and events, roughly corresponding to research studies and analysis steps within a single study. A number of sequential events can be grouped in a process building up a hierarchical structure to track patient and sample history. Each event can produce new data. Data is described by a set of user-defined metadata, and may have one or more associated files. We integrated the model in a web based digital repository with a data grid storage to manage large data sets located in geographically distinct areas. We built a graphical interface that allows authorized users to define new data types dynamically, according to their requirements. Operators compose queries on metadata fields using a flexible search interface and run them on the database and on the grid. We applied the digital repository to the integrated management of samples, patients and medical history in the BIT-Gaslini biobank. The platform currently manages 1800 samples of over 900 patients. Microarray data from 150 analyses are stored on the grid storage and replicated on two physical resources for preservation. The system is equipped with data integration capabilities with other biobanks for worldwide information sharing. Our data model enables users to continuously define flexible, ad hoc, and loosely structured metadata, for information sharing in specific research projects and purposes. This approach can improve sensitively interdisciplinary research collaboration and allows to track patients' clinical records, sample management information, and genomic data. The web interface allows the operators to easily manage, query, and annotate the files, without dealing with the technicalities of the data grid.

A digital repository with an extensible data model for biobanking and genomic analysis management

PubMed Central

2014-01-01

Motivation Molecular biology laboratories require extensive metadata to improve data collection and analysis. The heterogeneity of the collected metadata grows as research is evolving in to international multi-disciplinary collaborations and increasing data sharing among institutions. Single standardization is not feasible and it becomes crucial to develop digital repositories with flexible and extensible data models, as in the case of modern integrated biobanks management. Results We developed a novel data model in JSON format to describe heterogeneous data in a generic biomedical science scenario. The model is built on two hierarchical entities: processes and events, roughly corresponding to research studies and analysis steps within a single study. A number of sequential events can be grouped in a process building up a hierarchical structure to track patient and sample history. Each event can produce new data. Data is described by a set of user-defined metadata, and may have one or more associated files. We integrated the model in a web based digital repository with a data grid storage to manage large data sets located in geographically distinct areas. We built a graphical interface that allows authorized users to define new data types dynamically, according to their requirements. Operators compose queries on metadata fields using a flexible search interface and run them on the database and on the grid. We applied the digital repository to the integrated management of samples, patients and medical history in the BIT-Gaslini biobank. The platform currently manages 1800 samples of over 900 patients. Microarray data from 150 analyses are stored on the grid storage and replicated on two physical resources for preservation. The system is equipped with data integration capabilities with other biobanks for worldwide information sharing. Conclusions Our data model enables users to continuously define flexible, ad hoc, and loosely structured metadata, for information sharing in specific research projects and purposes. This approach can improve sensitively interdisciplinary research collaboration and allows to track patients' clinical records, sample management information, and genomic data. The web interface allows the operators to easily manage, query, and annotate the files, without dealing with the technicalities of the data grid. PMID:25077808

Reinforcement learning interfaces for biomedical database systems.

PubMed

Rudowsky, I; Kulyba, O; Kunin, M; Parsons, S; Raphan, T

2006-01-01

Studies of neural function that are carried out in different laboratories and that address different questions use a wide range of descriptors for data storage, depending on the laboratory and the individuals that input the data. A common approach to describe non-textual data that are referenced through a relational database is to use metadata descriptors. We have recently designed such a prototype system, but to maintain efficiency and a manageable metadata table, free formatted fields were designed as table entries. The database interface application utilizes an intelligent agent to improve integrity of operation. The purpose of this study was to investigate how reinforcement learning algorithms can assist the user in interacting with the database interface application that has been developed to improve the performance of the system.

Toward a Data Scalable Solution for Facilitating Discovery of Science Resources

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

Weaver, Jesse R.; Castellana, Vito G.; Morari, Alessandro

Science is increasingly motivated by the need to process larger quantities of data. It is facing severe challenges in data collection, management, and processing, so much so that the computational demands of “data scaling” are competing with, and in many fields surpassing, the traditional objective of decreasing processing time. Example domains with large datasets include astronomy, biology, genomics, climate/weather, and material sciences. This paper presents a real-world use case in which we wish to answer queries pro- vided by domain scientists in order to facilitate discovery of relevant science resources. The problem is that the metadata for these science resourcesmore » is very large and is growing quickly, rapidly increasing the need for a data scaling solution. We propose a system – SGEM – designed for answering graph-based queries over large datasets on cluster architectures, and we re- port performance results for queries on the current RDESC dataset of nearly 1.4 billion triples, and on the well-known BSBM SPARQL query benchmark.« less

BP Spill Sampling and Monitoring Data April-September 2010 - Data Download Tool

EPA Pesticide Factsheets

This dataset analyzes waste from the the British Petroleum Deepwater Horizon Rig Explosion Emergency Response, providing opportunity to query data sets by metadata criteria and find resulting raw datasets in CSV format.The data query tool allows users to download air, water and sediment sampling and monitoring data that has been collected in response to the BP oil spill. All sampling and monitoring data that has been collected to date is available for download as raw structured data.The query tools enables CSV file creation to be refined based on the following search criteria: date range (between April 28, 2010 and 9/29/2010); location by zip, city, or county; media (solid waste, weathered oil, air, surface water, liquid waste, tar, sediment, water); substance categories (based on media selection) and substances (based on substance category selection).

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.

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);

TOPCAT -- Tool for OPerations on Catalogues And Tables

NASA Astrophysics Data System (ADS)

Taylor, Mark

TOPCAT is an interactive graphical viewer and editor for tabular data. It has been designed for use with astronomical tables such as object catalogues, but is not restricted to astronomical applications. It understands a number of different astronomically important formats, and more formats can be added. It is designed to cope well with large tables; a million rows by a hundred columns should not present a problem even with modest memory and CPU resources. It offers a variety of ways to view and analyse the data, including a browser for the cell data themselves, viewers for information about table and column metadata, tools for joining tables using flexible matching algorithms, and visualisation facilities including histograms, 2- and 3-dimensional scatter plots, and density maps. Using a powerful and extensible Java-based expression language new columns can be defined and row subsets selected for separate analysis. Selecting a row can be configured to trigger an action, for instance displaying an image of the catalogue object in an external viewer. Table data and metadata can be edited and the resulting modified table can be written out in a wide range of output formats. A number of options are provided for loading data from external sources, including Virtual Observatory (VO) services, thus providing a gateway to many remote archives of astronomical data. It can also interoperate with other desktop tools using the SAMP protocol. TOPCAT is written in pure Java and is available under the GNU General Public Licence. Its underlying table processing facilities are provided by STIL, the Starlink Tables Infrastructure Library.

A Research on E - learning Resources Construction Based on Semantic Web

NASA Astrophysics Data System (ADS)

Rui, Liu; Maode, Deng

Traditional e-learning platforms have the flaws that it's usually difficult to query or positioning, and realize the cross platform sharing and interoperability. In the paper, the semantic web and metadata standard is discussed, and a kind of e - learning system framework based on semantic web is put forward to try to solve the flaws of traditional elearning platforms.

A spatial data handling system for retrieval of images by unrestricted regions of user interest

NASA Technical Reports Server (NTRS)

Dorfman, Erik; Cromp, Robert F.

1992-01-01

The Intelligent Data Management (IDM) project at NASA/Goddard Space Flight Center has prototyped an Intelligent Information Fusion System (IIFS), which automatically ingests metadata from remote sensor observations into a large catalog which is directly queryable by end-users. The greatest challenge in the implementation of this catalog was supporting spatially-driven searches, where the user has a possible complex region of interest and wishes to recover those images that overlap all or simply a part of that region. A spatial data management system is described, which is capable of storing and retrieving records of image data regardless of their source. This system was designed and implemented as part of the IIFS catalog. A new data structure, called a hypercylinder, is central to the design. The hypercylinder is specifically tailored for data distributed over the surface of a sphere, such as satellite observations of the Earth or space. Operations on the hypercylinder are regulated by two expert systems. The first governs the ingest of new metadata records, and maintains the efficiency of the data structure as it grows. The second translates, plans, and executes users' spatial queries, performing incremental optimization as partial query results are returned.

A semantic proteomics dashboard (SemPoD) for data management in translational research.

PubMed

Jayapandian, Catherine P; Zhao, Meng; Ewing, Rob M; Zhang, Guo-Qiang; Sahoo, Satya S

2012-01-01

One of the primary challenges in translational research data management is breaking down the barriers between the multiple data silos and the integration of 'omics data with clinical information to complete the cycle from the bench to the bedside. The role of contextual metadata, also called provenance information, is a key factor ineffective data integration, reproducibility of results, correct attribution of original source, and answering research queries involving "What", "Where", "When", "Which", "Who", "How", and "Why" (also known as the W7 model). But, at present there is limited or no effective approach to managing and leveraging provenance information for integrating data across studies or projects. Hence, there is an urgent need for a paradigm shift in creating a "provenance-aware" informatics platform to address this challenge. We introduce an ontology-driven, intuitive Semantic Proteomics Dashboard (SemPoD) that uses provenance together with domain information (semantic provenance) to enable researchers to query, compare, and correlate different types of data across multiple projects, and allow integration with legacy data to support their ongoing research. The SemPoD platform, currently in use at the Case Center for Proteomics and Bioinformatics (CPB), consists of three components: (a) Ontology-driven Visual Query Composer, (b) Result Explorer, and (c) Query Manager. Currently, SemPoD allows provenance-aware querying of 1153 mass-spectrometry experiments from 20 different projects. SemPod uses the systems molecular biology provenance ontology (SysPro) to support a dynamic query composition interface, which automatically updates the components of the query interface based on previous user selections and efficiently prunes the result set usinga "smart filtering" approach. The SysPro ontology re-uses terms from the PROV-ontology (PROV-O) being developed by the World Wide Web Consortium (W3C) provenance working group, the minimum information required for reporting a molecular interaction experiment (MIMIx), and the minimum information about a proteomics experiment (MIAPE) guidelines. The SemPoD was evaluated both in terms of user feedback and as scalability of the system. SemPoD is an intuitive and powerful provenance ontology-driven data access and query platform that uses the MIAPE and MIMIx metadata guideline to create an integrated view over large-scale systems molecular biology datasets. SemPoD leverages the SysPro ontology to create an intuitive dashboard for biologists to compose queries, explore the results, and use a query manager for storing queries for later use. SemPoD can be deployed over many existing database applications storing 'omics data, including, as illustrated here, the LabKey data-management system. The initial user feedback evaluating the usability and functionality of SemPoD has been very positive and it is being considered for wider deployment beyond the proteomics domain, and in other 'omics' centers.

Seqcrawler: biological data indexing and browsing platform.

PubMed

Sallou, Olivier; Bretaudeau, Anthony; Roult, Aurelien

2012-07-24

Seqcrawler takes its roots in software like SRS or Lucegene. It provides an indexing platform to ease the search of data and meta-data in biological banks and it can scale to face the current flow of data. While many biological bank search tools are available on the Internet, mainly provided by large organizations to search their data, there is a lack of free and open source solutions to browse one's own set of data with a flexible query system and able to scale from a single computer to a cloud system. A personal index platform will help labs and bioinformaticians to search their meta-data but also to build a larger information system with custom subsets of data. The software is scalable from a single computer to a cloud-based infrastructure. It has been successfully tested in a private cloud with 3 index shards (pieces of index) hosting ~400 millions of sequence information (whole GenBank, UniProt, PDB and others) for a total size of 600 GB in a fault tolerant architecture (high-availability). It has also been successfully integrated with software to add extra meta-data from blast results to enhance users' result analysis. Seqcrawler provides a complete open source search and store solution for labs or platforms needing to manage large amount of data/meta-data with a flexible and customizable web interface. All components (search engine, visualization and data storage), though independent, share a common and coherent data system that can be queried with a simple HTTP interface. The solution scales easily and can also provide a high availability infrastructure.

New tools and methods for direct programmatic access to the dbSNP relational database.

PubMed

Saccone, Scott F; Quan, Jiaxi; Mehta, Gaurang; Bolze, Raphael; Thomas, Prasanth; Deelman, Ewa; Tischfield, Jay A; Rice, John P

2011-01-01

Genome-wide association studies often incorporate information from public biological databases in order to provide a biological reference for interpreting the results. The dbSNP database is an extensive source of information on single nucleotide polymorphisms (SNPs) for many different organisms, including humans. We have developed free software that will download and install a local MySQL implementation of the dbSNP relational database for a specified organism. We have also designed a system for classifying dbSNP tables in terms of common tasks we wish to accomplish using the database. For each task we have designed a small set of custom tables that facilitate task-related queries and provide entity-relationship diagrams for each task composed from the relevant dbSNP tables. In order to expose these concepts and methods to a wider audience we have developed web tools for querying the database and browsing documentation on the tables and columns to clarify the relevant relational structure. All web tools and software are freely available to the public at http://cgsmd.isi.edu/dbsnpq. Resources such as these for programmatically querying biological databases are essential for viably integrating biological information into genetic association experiments on a genome-wide scale.

[Full Sibling Identification by IBS Scoring Method and Establishment of the Query Table of Its Critical Value].

PubMed

Li, R; Li, C T; Zhao, S M; Li, H X; Li, L; Wu, R G; Zhang, C C; Sun, H Y

2017-04-01

To establish a query table of IBS critical value and identification power for the detection systems with different numbers of STR loci under different false judgment standards. Samples of 267 pairs of full siblings and 360 pairs of unrelated individuals were collected and 19 autosomal STR loci were genotyped by Golden e ye™ 20A system. The full siblings were determined using IBS scoring method according to the 'Regulation for biological full sibling testing'. The critical values and identification power for the detection systems with different numbers of STR loci under different false judgment standards were calculated by theoretical methods. According to the formal IBS scoring criteria, the identification power of full siblings and unrelated individuals was 0.764 0 and the rate of false judgment was 0. The results of theoretical calculation were consistent with that of sample observation. The query table of IBS critical value for identification of full sibling detection systems with different numbers of STR loci was successfully established. The IBS scoring method defined by the regulation has high detection efficiency and low false judgment rate, which provides a relatively conservative result. The query table of IBS critical value for identification of full sibling detection systems with different numbers of STR loci provides an important reference data for the result judgment of full sibling testing and owns a considerable practical value. Copyright© by the Editorial Department of Journal of Forensic Medicine

A metadata approach for clinical data management in translational genomics studies in breast cancer.

PubMed

Papatheodorou, Irene; Crichton, Charles; Morris, Lorna; Maccallum, Peter; Davies, Jim; Brenton, James D; Caldas, Carlos

2009-11-30

In molecular profiling studies of cancer patients, experimental and clinical data are combined in order to understand the clinical heterogeneity of the disease: clinical information for each subject needs to be linked to tumour samples, macromolecules extracted, and experimental results. This may involve the integration of clinical data sets from several different sources: these data sets may employ different data definitions and some may be incomplete. In this work we employ semantic web techniques developed within the CancerGrid project, in particular the use of metadata elements and logic-based inference to annotate heterogeneous clinical information, integrate and query it. We show how this integration can be achieved automatically, following the declaration of appropriate metadata elements for each clinical data set; we demonstrate the practicality of this approach through application to experimental results and clinical data from five hospitals in the UK and Canada, undertaken as part of the METABRIC project (Molecular Taxonomy of Breast Cancer International Consortium). We describe a metadata approach for managing similarities and differences in clinical datasets in a standardized way that uses Common Data Elements (CDEs). We apply and evaluate the approach by integrating the five different clinical datasets of METABRIC.

GeneLab Analysis Working Group Kick-Off Meeting

NASA Technical Reports Server (NTRS)

Costes, Sylvain V.

2018-01-01

Goals to achieve for GeneLab AWG - GL vision - Review of GeneLab AWG charter Timeline and milestones for 2018 Logistics - Monthly Meeting - Workshop - Internship - ASGSR Introduction of team leads and goals of each group Introduction of all members Q/A Three-tier Client Strategy to Democratize Data Physiological changes, pathway enrichment, differential expression, normalization, processing metadata, reproducibility, Data federation/integration with heterogeneous bioinformatics external databases The GLDS currently serves over 100 omics investigations to the biomedical community via open access. In order to expand the scope of metadata record searches via the GLDS, we designed a metadata warehouse that collects and updates metadata records from external systems housing similar data. To demonstrate the capabilities of federated search and retrieval of these data, we imported metadata records from three open-access data systems into the GLDS metadata warehouse: NCBI's Gene Expression Omnibus (GEO), EBI's PRoteomics IDEntifications (PRIDE) repository, and the Metagenomics Analysis server (MG-RAST). Each of these systems defines metadata for omics data sets differently. One solution to bridge such differences is to employ a common object model (COM) to which each systems' representation of metadata can be mapped. Warehoused metadata records are then transformed at ETL to this single, common representation. Queries generated via the GLDS are then executed against the warehouse, and matching records are shown in the COM representation (Fig. 1). While this approach is relatively straightforward to implement, the volume of the data in the omics domain presents challenges in dealing with latency and currency of records. Furthermore, the lack of a coordinated has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics.

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.

Visual analytics for semantic queries of TerraSAR-X image content

NASA Astrophysics Data System (ADS)

Espinoza-Molina, Daniela; Alonso, Kevin; Datcu, Mihai

2015-10-01

With the continuous image product acquisition of satellite missions, the size of the image archives is considerably increasing every day as well as the variety and complexity of their content, surpassing the end-user capacity to analyse and exploit them. Advances in the image retrieval field have contributed to the development of tools for interactive exploration and extraction of the images from huge archives using different parameters like metadata, key-words, and basic image descriptors. Even though we count on more powerful tools for automated image retrieval and data analysis, we still face the problem of understanding and analyzing the results. Thus, a systematic computational analysis of these results is required in order to provide to the end-user a summary of the archive content in comprehensible terms. In this context, visual analytics combines automated analysis with interactive visualizations analysis techniques for an effective understanding, reasoning and decision making on the basis of very large and complex datasets. Moreover, currently several researches are focused on associating the content of the images with semantic definitions for describing the data in a format to be easily understood by the end-user. In this paper, we present our approach for computing visual analytics and semantically querying the TerraSAR-X archive. Our approach is mainly composed of four steps: 1) the generation of a data model that explains the information contained in a TerraSAR-X product. The model is formed by primitive descriptors and metadata entries, 2) the storage of this model in a database system, 3) the semantic definition of the image content based on machine learning algorithms and relevance feedback, and 4) querying the image archive using semantic descriptors as query parameters and computing the statistical analysis of the query results. The experimental results shows that with the help of visual analytics and semantic definitions we are able to explain the image content using semantic terms and the relations between them answering questions such as what is the percentage of urban area in a region? or what is the distribution of water bodies in a city?

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

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

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

DOE PAGES

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith; ...

2017-11-06

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

Data services providing by the Ukrainian NODC (MHI NASU)

NASA Astrophysics Data System (ADS)

Eremeev, V.; Godin, E.; Khaliulin, A.; Ingerov, A.; Zhuk, E.

2009-04-01

At modern stage of the World Ocean study information support of investigation based on ad-vanced computer technologies becomes of particular importance. These abstracts are devoted to presentation of several data services developed in the Ukrainian NODC on the base of the Ma-rine Environmental and Information Technologies Department of MHI NASU. The Data Quality Control Service Using experience of international collaboration in the field of data collection and quality check we have developed the quality control (QC) software providing both preliminary(automatic) and expert(manual) data quality check procedures. The current version of the QC software works for the Mediterranean and Black seas and includes the climatic arrays for hydrological and few hydrochemical parameters based on such products as MEDAR/MEDATLAS II, Physical Oceanography of the Black Sea and Climatic Atlas of Oxygen and Hydrogen Sulfide in the Black sea. The data quality check procedure includes metadata control and hydrological and hydrochemical data control. Metadata control provides checking of duplicate cruises and pro-files, date and chronology, ship velocity, station location, sea depth and observation depth. Data QC procedure includes climatic (or range for parameters with small number of observations) data QC, density inversion check for hydrological data and searching for spikes. Using of cli-matic fields and profiles prepared by regional oceanography experts leads to more reliable results of data quality check procedure. The Data Access Services The Ukrainian NODC provides two products for data access - on-line software and data access module for the MHI NASU local net. This software allows select-ing data on rectangle area, on date, on months, on cruises. The result of query is metadata which are presented in the table and the visual presentation of stations on the map. It is possible to see both metadata and data. For this purpose it is necessary to select station in the table of metadata or on the map. There is also an opportunity to export data in ODV format. The product is avail-able on http://www.ocean.nodc.org.ua/DataAccess.php The local net version provides access to the oceanological database of the MHI NASU. The cur-rent version allows selecting data by spatial and temporal limits, depth, values of parameters, quality flags and works for the Mediterranean and Black seas. It provides visualization of meta-data and data, statistics of data selection, data export into several data formats. The Operational Data Management Services The collaborators of the MHI Experimental Branch developed a system of obtaining information on water pressure and temperature, as well as on atmospheric pressure. Sea level observations are also conducted. The obtained data are transferred online. The interface for operation data access was developed. It allows to select parameters (sea level, water temperature, atmospheric pressure, wind and wa-ter pressure) and time interval to see parameter graphics. The product is available on http://www.ocean.nodc.org.ua/Katsively.php . The Climatic products The current version of the Climatic Atlas includes maps on such pa-rameters as temperature, salinity, density, heat storage, dynamic heights, upper boundary of hy-drogen sulfide and lower boundary of oxygen for the Black sea basin. Maps for temperature, sa-linity, density were calculated on 19 standard depths and averaged monthly for depths 0 - 300 m and annually for lower depth values. The climatic maps of upper boundary of hydrogen sulfide and lower boundary of oxygen were averaged by decades from 20 till 90 of the XX century and by seasons. Two versions of climatic atlas viewer - on-line and desktop for presentation of the climatic maps were developed. They provide similar functions of selection and viewing maps by parameter, month and depth and saving maps in various formats. On-line version of atlas is available on http://www.ocean.nodc.org.ua/Main_Atlas.php .

A Comparison of Query-by-Example Methods for Spoken Term Detection

DTIC Science & Technology

2009-09-01

consistent “errors” between the in- dex and the query. Few query terms have more than one pro- nunciation (avg. 1.1 prons . per term), as a result, there is... pron lex. one dict entry (llr) 73.01 47.66 21.11 all dict entries (avg+llr) 73.99 48.16 20.92 all dict entries (max+llr) 74.27 48.26 20.93 Table 1

A unified framework for managing provenance information in translational research

PubMed Central

2011-01-01

Background A critical aspect of the NIH Translational Research roadmap, which seeks to accelerate the delivery of "bench-side" discoveries to patient's "bedside," is the management of the provenance metadata that keeps track of the origin and history of data resources as they traverse the path from the bench to the bedside and back. A comprehensive provenance framework is essential for researchers to verify the quality of data, reproduce scientific results published in peer-reviewed literature, validate scientific process, and associate trust value with data and results. Traditional approaches to provenance management have focused on only partial sections of the translational research life cycle and they do not incorporate "domain semantics", which is essential to support domain-specific querying and analysis by scientists. Results We identify a common set of challenges in managing provenance information across the pre-publication and post-publication phases of data in the translational research lifecycle. We define the semantic provenance framework (SPF), underpinned by the Provenir upper-level provenance ontology, to address these challenges in the four stages of provenance metadata: (a) Provenance collection - during data generation (b) Provenance representation - to support interoperability, reasoning, and incorporate domain semantics (c) Provenance storage and propagation - to allow efficient storage and seamless propagation of provenance as the data is transferred across applications (d) Provenance query - to support queries with increasing complexity over large data size and also support knowledge discovery applications We apply the SPF to two exemplar translational research projects, namely the Semantic Problem Solving Environment for Trypanosoma cruzi (T.cruzi SPSE) and the Biomedical Knowledge Repository (BKR) project, to demonstrate its effectiveness. Conclusions The SPF provides a unified framework to effectively manage provenance of translational research data during pre and post-publication phases. This framework is underpinned by an upper-level provenance ontology called Provenir that is extended to create domain-specific provenance ontologies to facilitate provenance interoperability, seamless propagation of provenance, automated querying, and analysis. PMID:22126369

A Novel Database to Rank and Display Archeomagnetic Intensity Data

NASA Astrophysics Data System (ADS)

Donadini, F.; Korhonen, K.; Riisager, P.; Pesonen, L. J.; Kahma, K.

2005-12-01

To understand the content and the causes of the changes in the Earth's magnetic field beyond the observatory records one has to rely on archeomagnetic and lake sediment paleomagnetic data. The regional archeointensity curves are often of different quality and temporally variable which hampers the global analysis of the data in terms of dipole vs non-dipole field. We have developed a novel archeointensity database application utilizing MySQL, PHP (PHP Hypertext Preprocessor), and the Generic Mapping Tools (GMT) for ranking and displaying geomagnetic intensity data from the last 12000 years. Our application has the advantage that no specific software is required to query the database and view the results. Querying the database is performed using any Web browser; a fill-out form is used to enter the site location and a minimum ranking value to select the data points to be displayed. The form also features the possibility to select plotting of the data as an archeointensity curve with error bars, and a Virtual Axial Dipole Moment (VADM) or ancient field value (Ba) curve calculated using the CALS7K model (Continuous Archaeomagnetic and Lake Sediment geomagnetic model) of (Korte and Constable, 2005). The results of a query are displayed on a Web page containing a table summarizing the query parameters, a table showing the archeointensity values satisfying the query parameters, and a plot of VADM or Ba as a function of sample age. The database consists of eight related tables. The main one, INTENSITIES, stores the 3704 archeointensity measurements collected from 159 publications as VADM (and VDM when available) and Ba values, including their standard deviations and sampling locations. It also contains the number of samples and specimens measured from each site. The REFS table stores the references to a particular study. The names, latitudes, and longitudes of the regions where the samples were collected are stored in the SITES table. The MATERIALS, METHODS, SPECIMEN_TYPES and DATING_METHODS tables store information about the sample materials, intensity determination methods, specimen types and age determination methods. The SIGMA_COUNT table is used indirectly for ranking data according to the number of samples measured and their standard deviations. Each intensity measurement is assigned a score (0--2) depending on the number of specimens measured and their standard deviations, the intensity determination method, the type of specimens measured and materials. The ranking of each data point is calculated as the sum of the four scores and varies between 0 and 8. Additionally, users can select the parameters that will be included in the ranking.

New tools and methods for direct programmatic access to the dbSNP relational database

PubMed Central

Saccone, Scott F.; Quan, Jiaxi; Mehta, Gaurang; Bolze, Raphael; Thomas, Prasanth; Deelman, Ewa; Tischfield, Jay A.; Rice, John P.

2011-01-01

Genome-wide association studies often incorporate information from public biological databases in order to provide a biological reference for interpreting the results. The dbSNP database is an extensive source of information on single nucleotide polymorphisms (SNPs) for many different organisms, including humans. We have developed free software that will download and install a local MySQL implementation of the dbSNP relational database for a specified organism. We have also designed a system for classifying dbSNP tables in terms of common tasks we wish to accomplish using the database. For each task we have designed a small set of custom tables that facilitate task-related queries and provide entity-relationship diagrams for each task composed from the relevant dbSNP tables. In order to expose these concepts and methods to a wider audience we have developed web tools for querying the database and browsing documentation on the tables and columns to clarify the relevant relational structure. All web tools and software are freely available to the public at http://cgsmd.isi.edu/dbsnpq. Resources such as these for programmatically querying biological databases are essential for viably integrating biological information into genetic association experiments on a genome-wide scale. PMID:21037260

Query-Adaptive Hash Code Ranking for Large-Scale Multi-View Visual Search.

PubMed

Liu, Xianglong; Huang, Lei; Deng, Cheng; Lang, Bo; Tao, Dacheng

2016-10-01

Hash-based nearest neighbor search has become attractive in many applications. However, the quantization in hashing usually degenerates the discriminative power when using Hamming distance ranking. Besides, for large-scale visual search, existing hashing methods cannot directly support the efficient search over the data with multiple sources, and while the literature has shown that adaptively incorporating complementary information from diverse sources or views can significantly boost the search performance. To address the problems, this paper proposes a novel and generic approach to building multiple hash tables with multiple views and generating fine-grained ranking results at bitwise and tablewise levels. For each hash table, a query-adaptive bitwise weighting is introduced to alleviate the quantization loss by simultaneously exploiting the quality of hash functions and their complement for nearest neighbor search. From the tablewise aspect, multiple hash tables are built for different data views as a joint index, over which a query-specific rank fusion is proposed to rerank all results from the bitwise ranking by diffusing in a graph. Comprehensive experiments on image search over three well-known benchmarks show that the proposed method achieves up to 17.11% and 20.28% performance gains on single and multiple table search over the state-of-the-art methods.

TogoTable: cross-database annotation system using the Resource Description Framework (RDF) data model.

PubMed

Kawano, Shin; Watanabe, Tsutomu; Mizuguchi, Sohei; Araki, Norie; Katayama, Toshiaki; Yamaguchi, Atsuko

2014-07-01

TogoTable (http://togotable.dbcls.jp/) is a web tool that adds user-specified annotations to a table that a user uploads. Annotations are drawn from several biological databases that use the Resource Description Framework (RDF) data model. TogoTable uses database identifiers (IDs) in the table as a query key for searching. RDF data, which form a network called Linked Open Data (LOD), can be searched from SPARQL endpoints using a SPARQL query language. Because TogoTable uses RDF, it can integrate annotations from not only the reference database to which the IDs originally belong, but also externally linked databases via the LOD network. For example, annotations in the Protein Data Bank can be retrieved using GeneID through links provided by the UniProt RDF. Because RDF has been standardized by the World Wide Web Consortium, any database with annotations based on the RDF data model can be easily incorporated into this tool. We believe that TogoTable is a valuable Web tool, particularly for experimental biologists who need to process huge amounts of data such as high-throughput experimental output. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

NOAA's Data Catalog and the Federal Open Data Policy

NASA Astrophysics Data System (ADS)

Wengren, M. J.; de la Beaujardiere, J.

2014-12-01

The 2013 Open Data Policy Presidential Directive requires Federal agencies to create and maintain a 'public data listing' that includes all agency data that is currently or will be made publicly-available in the future. The directive requires the use of machine-readable and open formats that make use of 'common core' and extensible metadata formats according to the best practices published in an online repository called 'Project Open Data', to use open licenses where possible, and to adhere to existing metadata and other technology standards to promote interoperability. In order to meet the requirements of the Open Data Policy, the National Oceanic and Atmospheric Administration (NOAA) has implemented an online data catalog that combines metadata from all subsidiary NOAA metadata catalogs into a single master inventory. The NOAA Data Catalog is available to the public for search and discovery, providing access to the NOAA master data inventory through multiple means, including web-based text search, OGC CS-W endpoint, as well as a native Application Programming Interface (API) for programmatic query. It generates on a daily basis the Project Open Data JavaScript Object Notation (JSON) file required for compliance with the Presidential directive. The Data Catalog is based on the open source Comprehensive Knowledge Archive Network (CKAN) software and runs on the Amazon Federal GeoCloud. This presentation will cover topics including mappings of existing metadata in standard formats (FGDC-CSDGM and ISO 19115 XML ) to the Project Open Data JSON metadata schema, representation of metadata elements within the catalog, and compatible metadata sources used to feed the catalog to include Web Accessible Folder (WAF), Catalog Services for the Web (CS-W), and Esri ArcGIS.com. It will also discuss related open source technologies that can be used together to build a spatial data infrastructure compliant with the Open Data Policy.

The XMM-Newton Science Archive and its integration into ESASky

NASA Astrophysics Data System (ADS)

Loiseau, N.; Baines, D.; Colomo, E.; Giordano, F.; Merín, B.; Racero, E.; Rodríguez, P.; Salgado, J.; Sarmiento, M.

2017-07-01

We describe the variety of functionalities of the XSA (XMM-Newton Science Archive) that allow to search and access the XMM-Newton data and catalogues. The web interface http://nxsa.esac.esa.int/ is very flexible allowing different kinds of searches by a single position or target name, or by a list of targets, with several selecting options (target type, text in the abstract, etc.), and with several display options. The resulting data can be easily broadcast to Virtual Observatory (VO) facilities for a first look analysis, or for cross-matching the results with info from other observatories. Direct access via URL or command line are also possible for scripts usage, or to link XMM-Newton data from other interfaces like Vizier, ADS, etc. The full metadata content of the XSA can be queried through the TAP (Table access Protocol) via ADQL (Astronomical Data Query Language). We present also the roadmap for future improvements of the XSA including the integration of the Upper Limit server, the on-the-fly data analysis, and the interactive visualization of EPIC sources spectra and light curves and RGS spectra, among other advanced features. Within this modern visualization philosophy XSA is also being integrated into ESASky (http://sky.esa.int). ESASky is the science-driven multi-wavelength discovery portal for all the ESA Astronomy Missions (Integral, HST, Herschel, Suzaku, Planck, etc.), and other space and ground telescope data. The system offers progressive multi-resolution all-sky projections of full mission datasets using HiPS, a new generation of HEALPix projections developed by CDS, precise footprints to connect to individual observations, and direct access to science-ready data from the underlying mission specific science archives. XMM-Newton EPIC and OM all-sky HiPS maps, catalogues and links to the observations are available through ESASky.

TOPCAT: Tool for OPerations on Catalogues And Tables

NASA Astrophysics Data System (ADS)

Taylor, Mark

2011-01-01

TOPCAT is an interactive graphical viewer and editor for tabular data. Its aim is to provide most of the facilities that astronomers need for analysis and manipulation of source catalogues and other tables, though it can be used for non-astronomical data as well. It understands a number of different astronomically important formats (including FITS and VOTable) and more formats can be added. It offers a variety of ways to view and analyse tables, including a browser for the cell data themselves, viewers for information about table and column metadata, and facilities for 1-, 2-, 3- and higher-dimensional visualisation, calculating statistics and joining tables using flexible matching algorithms. Using a powerful and extensible Java-based expression language new columns can be defined and row subsets selected for separate analysis. Table data and metadata can be edited and the resulting modified table can be written out in a wide range of output formats. It is a stand-alone application which works quite happily with no network connection. However, because it uses Virtual Observatory (VO) standards, it can cooperate smoothly with other tools in the VO world and beyond, such as VODesktop, Aladin and ds9. Between 2006 and 2009 TOPCAT was developed within the AstroGrid project, and is offered as part of a standard suite of applications on the AstroGrid web site, where you can find information on several other VO tools. The program is written in pure Java and available under the GNU General Public Licence. It has been developed in the UK within the Starlink and AstroGrid projects, and under PPARC and STFC grants. Its underlying table processing facilities are provided by STIL.

STARS 2.0: 2nd-generation open-source archiving and query software

NASA Astrophysics Data System (ADS)

Winegar, Tom

2008-07-01

The Subaru Telescope is in process of developing an open-source alternative to the 1st-generation software and databases (STARS 1) used for archiving and query. For STARS 2, we have chosen PHP and Python for scripting and MySQL as the database software. We have collected feedback from staff and observers, and used this feedback to significantly improve the design and functionality of our future archiving and query software. Archiving - We identified two weaknesses in 1st-generation STARS archiving software: a complex and inflexible table structure and uncoordinated system administration for our business model: taking pictures from the summit and archiving them in both Hawaii and Japan. We adopted a simplified and normalized table structure with passive keyword collection, and we are designing an archive-to-archive file transfer system that automatically reports real-time status and error conditions and permits error recovery. Query - We identified several weaknesses in 1st-generation STARS query software: inflexible query tools, poor sharing of calibration data, and no automatic file transfer mechanisms to observers. We are developing improved query tools and sharing of calibration data, and multi-protocol unassisted file transfer mechanisms for observers. In the process, we have redefined a 'query': from an invisible search result that can only transfer once in-house right now, with little status and error reporting and no error recovery - to a stored search result that can be monitored, transferred to different locations with multiple protocols, reporting status and error conditions and permitting recovery from errors.

A rapid prototyping/artificial intelligence approach to space station-era information management and access

NASA Technical Reports Server (NTRS)

Carnahan, Richard S., Jr.; Corey, Stephen M.; Snow, John B.

1989-01-01

Applications of rapid prototyping and Artificial Intelligence techniques to problems associated with Space Station-era information management systems are described. In particular, the work is centered on issues related to: (1) intelligent man-machine interfaces applied to scientific data user support, and (2) the requirement that intelligent information management systems (IIMS) be able to efficiently process metadata updates concerning types of data handled. The advanced IIMS represents functional capabilities driven almost entirely by the needs of potential users. Space Station-era scientific data projected to be generated is likely to be significantly greater than data currently processed and analyzed. Information about scientific data must be presented clearly, concisely, and with support features to allow users at all levels of expertise efficient and cost-effective data access. Additionally, mechanisms for allowing more efficient IIMS metadata update processes must be addressed. The work reported covers the following IIMS design aspects: IIMS data and metadata modeling, including the automatic updating of IIMS-contained metadata, IIMS user-system interface considerations, including significant problems associated with remote access, user profiles, and on-line tutorial capabilities, and development of an IIMS query and browse facility, including the capability to deal with spatial information. A working prototype has been developed and is being enhanced.

Engineering the ATLAS TAG Browser

NASA Astrophysics Data System (ADS)

Zhang, Qizhi; ATLAS Collaboration

2011-12-01

ELSSI is a web-based event metadata (TAG) browser and event-level selection service for ATLAS. In this paper, we describe some of the challenges encountered in the process of developing ELSSI, and the software engineering strategies adopted to address those challenges. Approaches to management of access to data, browsing, data rendering, query building, query validation, execution, connection management, and communication with auxiliary services are discussed. We also describe strategies for dealing with data that may vary over time, such as run-dependent trigger decision decoding. Along with examples, we illustrate how programming techniques in multiple languages (PHP, JAVASCRIPT, XML, AJAX, and PL/SQL) have been blended to achieve the required results. Finally, we evaluate features of the ELSSI service in terms of functionality, scalability, and performance.

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

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.

A Web 2.0 Application for Executing Queries and Services on Climatic Data

NASA Astrophysics Data System (ADS)

Abad-Mota, S.; Ruckhaus, E.; Garboza, A.; Tepedino, G.

2007-12-01

For many years countries have collected data in order to understand climate, to study its effect in living species, and to predict future behavior. Nowadays, terabytes of data are collected by governmental agencies and academic institutions and the current challenge is how to provide appropriate access to this vast amount of climatic data. Each country has a different situation with respect to the collection and use of these data. In particular, in Venezuela, a few institutions have systematically gathered observational and hidrology data, but the data are mostly registered in non-digital media which have been lost or have deteriorated over the years; all of this restricts data availability. In 2006 a joint project between two major venezuelan universities, Universidad Simón Bolívar (USB) and Universidad Central de Venezuela (UCV) was initiated. The goal of the project is to develop a digital repository of the country's climatic and hidrology data, and to build an application that provides querying and service execution capabilities over these data. The repository has been conceptually modeled as a database, which integrates observational data and metadata. Among the metadata we have an inventory of all the stations where data has been collected, and the description of the measurements themselves, for instance, the instruments used for the collection, the time granularity of the measurements, and their units of measure. The resulting data model combines traditional entity relationship concepts with star and snowflake schemas from datawarehouses. The model allows the inclusion of historic or current data, and each kind of data requires a different loading process. A special emphasis has been given to the representation of the quality of the data stored in the repository. Quality attributes can be attached to each individual value or to sets of values; these attributes can represent statistical or semantic quality of the data. Values can be stored at any level of aggregation, hourly, daily, monthly, so that they can be provided to the user at the desired level. This means that additional caution has to be exercised in query answering, in order to distinguish between primary and derived data. On the other hand, a Web 2.0 application is being designed to provide a front-end to the repository. This design focuses on two important aspects: the use of metadata structures, and the definition of collaborative Web 2.0 features that can be integrated to a project of this nature. Metadata descriptors include for a set of measurements, its quality, granularity and other dimension information. With these descriptors it is possible to establish relationships between different sets of measurements and provide scientists with efficient searching mechanisms that determine the related sets of measurements that contribute to a query answer. Unlike traditional applications for climatic data, our approach not only satisfies requirements of researchers specialized in this domain, but also those of anyone interested in this area; one of the objectives is to build an informal knowledge base that can be improved and consolidated with the usage of the system.

Integrating TRENCADIS components in gLite to share DICOM medical images and structured reports.

PubMed

Blanquer, Ignacio; Hernández, Vicente; Salavert, José; Segrelles, Damià

2010-01-01

The problem of sharing medical information among different centres has been tackled by many projects. Several of them target the specific problem of sharing DICOM images and structured reports (DICOM-SR), such as the TRENCADIS project. In this paper we propose sharing and organizing DICOM data and DICOM-SR metadata benefiting from the existent deployed Grid infrastructures compliant with gLite such as EGEE or the Spanish NGI. These infrastructures contribute with a large amount of storage resources for creating knowledge databases and also provide metadata storage resources (such as AMGA) to semantically organize reports in a tree-structure. First, in this paper, we present the extension of TRENCADIS architecture to use gLite components (LFC, AMGA, SE) on the shake of increasing interoperability. Using the metadata from DICOM-SR, and maintaining its tree structure, enables federating different but compatible diagnostic structures and simplifies the definition of complex queries. This article describes how to do this in AMGA and it shows an approach to efficiently code radiology reports to enable the multi-centre federation of data resources.

Query optimization for graph analytics on linked data using SPARQL

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

Hong, Seokyong; Lee, Sangkeun; Lim, Seung -Hwan

2015-07-01

Triplestores that support query languages such as SPARQL are emerging as the preferred and scalable solution to represent data and meta-data as massive heterogeneous graphs using Semantic Web standards. With increasing adoption, the desire to conduct graph-theoretic mining and exploratory analysis has also increased. Addressing that desire, this paper presents a solution that is the marriage of Graph Theory and the Semantic Web. We present software that can analyze Linked Data using graph operations such as counting triangles, finding eccentricity, testing connectedness, and computing PageRank directly on triple stores via the SPARQL interface. We describe the process of optimizing performancemore » of the SPARQL-based implementation of such popular graph algorithms by reducing the space-overhead, simplifying iterative complexity and removing redundant computations by understanding query plans. Our optimized approach shows significant performance gains on triplestores hosted on stand-alone workstations as well as hardware-optimized scalable supercomputers such as the Cray XMT.« less

Digital data in support of studies and assessments of coal and petroleum resources in the Appalachian basin: Chapter I.1 in Coal and petroleum resources in the Appalachian basin: distribution, geologic framework, and geochemical character

USGS Publications Warehouse

Trippi, Michael H.; Kinney, Scott A.; Gunther, Gregory; Ryder, Robert T.; Ruppert, Leslie F.; Ruppert, Leslie F.; Ryder, Robert T.

2014-01-01

Metadata for these datasets are available in HTML and XML formats. Metadata files contain information about the sources of data used to create the dataset, the creation process steps, the data quality, the geographic coordinate system and horizontal datum used for the dataset, the values of attributes used in the dataset table, information about the publication and the publishing organization, and other information that may be useful to the reader. All links in the metadata were valid at the time of compilation. Some of these links may no longer be valid. No attempt has been made to determine the new online location (if one exists) for the data.

TabSQL: a MySQL tool to facilitate mapping user data to public databases.

PubMed

Xia, Xiao-Qin; McClelland, Michael; Wang, Yipeng

2010-06-23

With advances in high-throughput genomics and proteomics, it is challenging for biologists to deal with large data files and to map their data to annotations in public databases. We developed TabSQL, a MySQL-based application tool, for viewing, filtering and querying data files with large numbers of rows. TabSQL provides functions for downloading and installing table files from public databases including the Gene Ontology database (GO), the Ensembl databases, and genome databases from the UCSC genome bioinformatics site. Any other database that provides tab-delimited flat files can also be imported. The downloaded gene annotation tables can be queried together with users' data in TabSQL using either a graphic interface or command line. TabSQL allows queries across the user's data and public databases without programming. It is a convenient tool for biologists to annotate and enrich their data.

TabSQL: a MySQL tool to facilitate mapping user data to public databases

PubMed Central

2010-01-01

Background With advances in high-throughput genomics and proteomics, it is challenging for biologists to deal with large data files and to map their data to annotations in public databases. Results We developed TabSQL, a MySQL-based application tool, for viewing, filtering and querying data files with large numbers of rows. TabSQL provides functions for downloading and installing table files from public databases including the Gene Ontology database (GO), the Ensembl databases, and genome databases from the UCSC genome bioinformatics site. Any other database that provides tab-delimited flat files can also be imported. The downloaded gene annotation tables can be queried together with users' data in TabSQL using either a graphic interface or command line. Conclusions TabSQL allows queries across the user's data and public databases without programming. It is a convenient tool for biologists to annotate and enrich their data. PMID:20573251

Online Meta-data Collection and Monitoring Framework for the STAR Experiment at RHIC

NASA Astrophysics Data System (ADS)

Arkhipkin, D.; Lauret, J.; Betts, W.; Van Buren, G.

2012-12-01

The STAR Experiment further exploits scalable message-oriented model principles to achieve a high level of control over online data streams. In this paper we present an AMQP-powered Message Interface and Reliable Architecture framework (MIRA), which allows STAR to orchestrate the activities of Meta-data Collection, Monitoring, Online QA and several Run-Time and Data Acquisition system components in a very efficient manner. The very nature of the reliable message bus suggests parallel usage of multiple independent storage mechanisms for our meta-data. We describe our experience with a robust data-taking setup employing MySQL- and HyperTable-based archivers for meta-data processing. In addition, MIRA has an AJAX-enabled web GUI, which allows real-time visualisation of online process flow and detector subsystem states, and doubles as a sophisticated alarm system when combined with complex event processing engines like Esper, Borealis or Cayuga. The performance data and our planned path forward are based on our experience during the 2011-2012 running of STAR.

Bin-Hash Indexing: A Parallel Method for Fast Query Processing

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

Bethel, Edward W; Gosink, Luke J.; Wu, Kesheng

2008-06-27

This paper presents a new parallel indexing data structure for answering queries. The index, called Bin-Hash, offers extremely high levels of concurrency, and is therefore well-suited for the emerging commodity of parallel processors, such as multi-cores, cell processors, and general purpose graphics processing units (GPU). The Bin-Hash approach first bins the base data, and then partitions and separately stores the values in each bin as a perfect spatial hash table. To answer a query, we first determine whether or not a record satisfies the query conditions based on the bin boundaries. For the bins with records that can not bemore » resolved, we examine the spatial hash tables. The procedures for examining the bin numbers and the spatial hash tables offer the maximum possible level of concurrency; all records are able to be evaluated by our procedure independently in parallel. Additionally, our Bin-Hash procedures access much smaller amounts of data than similar parallel methods, such as the projection index. This smaller data footprint is critical for certain parallel processors, like GPUs, where memory resources are limited. To demonstrate the effectiveness of Bin-Hash, we implement it on a GPU using the data-parallel programming language CUDA. The concurrency offered by the Bin-Hash index allows us to fully utilize the GPU's massive parallelism in our work; over 12,000 records can be simultaneously evaluated at any one time. We show that our new query processing method is an order of magnitude faster than current state-of-the-art CPU-based indexing technologies. Additionally, we compare our performance to existing GPU-based projection index strategies.« less

Implementing RDA Data Citation Recommendations: Case Study in South Africa

NASA Astrophysics Data System (ADS)

Hugo, Wim

2016-04-01

SAEON operates a shared research data infrastructure for its own data sets and for clients and end users in the Earth and Environmental Sciences domain. SAEON has a license to issue Digital Object Identifiers via DataCite on behalf of third parties, and have recently concluded development work to make a universal data deposit, description, and DOI minting facility available. This facility will be used to develop a number of end user gateways, including DataCite South Africa (in collaboration with National Research Foundation and addressing all grant-funded research in the country), DIRISA (Data-intensive Research Infrastructure for South Africa - in collaboration with Meraka Institute and Department of Science and Technology), and SASDI (South African Spatial Data Infrastructure). The RDA recently published Data Citation Recommendations [1], and this was used as a basis for specification of Digital Object Identifier implementation, raising two significant challenges: 1. Synchronisation of frequently harvested meta-data sets where version management practice did not align with the RDA recommendations, and 2. Handling sub-sets of and queries on large, continuously updated data sets. In the first case, we have developed a set of tests that determine the logical course of action when discrepancies are found during synchronization, and we have incorporated these into meta-data harvester configurations. Additionally, we have developed a state diagram and attendant workflow for meta-data that includes problem states emanating from DOI management, reporting services for data depositors, and feedback to end users in respect of synchronisation issues. In the second case, in the absence of firm guidelines from DataCite, we are seeking community consensus and feedback on an approach that caches all queries performed and subsets derived from data, and provide these with anchor-style extensions linked to the dataset's original DOI. This allows extended DOIs to resolve to a meta-data page on which the cached data set is available as an anchored download link.All cached datasets are provided with checksum values to verify the contents against such copies as may exist. The paper reviews recent service-driven portal interface developments, both services and graphical user interfaces, including wizard-style, configurable applications for meta-data management and DOI minting, discovery, download, visualization, and reporting. It showcases examples of the two permanent identifier problem areas and how these were addressed. The paper concludes with contributions to open research questions, including (1) determining optimal meta-data granularity and (2) proposing an implementation guideline for extended DOIs. [1] A. Rauber, D. van Uytvanck, A. Asmi, S. Pröll, "Data Citation Recommendations", November 2015, RDA. https://rd-alliance.org/group/data-citation-wg/outcomes/data-citation-recommendation.htm

Interoperability Between Coastal Web Atlases Using Semantic Mediation: A Case Study of the International Coastal Atlas Network (ICAN)

NASA Astrophysics Data System (ADS)

Wright, D. J.; Lassoued, Y.; Dwyer, N.; Haddad, T.; Bermudez, L. E.; Dunne, D.

2009-12-01

Coastal mapping plays an important role in informing marine spatial planning, resource management, maritime safety, hazard assessment and even national sovereignty. As such, there is now a plethora of data/metadata catalogs, pre-made maps, tabular and text information on resource availability and exploitation, and decision-making tools. A recent trend has been to encapsulate these in a special class of web-enabled geographic information systems called a coastal web atlas (CWA). While multiple benefits are derived from tailor-made atlases, there is great value added from the integration of disparate CWAs. CWAs linked to one another can query more successfully to optimize planning and decision-making. If a dataset is missing in one atlas, it may be immediately located in another. Similar datasets in two atlases may be combined to enhance study in either region. *But how best to achieve semantic interoperability to mitigate vague data queries, concepts or natural language semantics when retrieving and integrating data and information?* We report on the development of a new prototype seeking to interoperate between two initial CWAs: the Marine Irish Digital Atlas (MIDA) and the Oregon Coastal Atlas (OCA). These two mature atlases are used as a testbed for more regional connections, with the intent for the OCA to use lessons learned to develop a regional network of CWAs along the west coast, and for MIDA to do the same in building and strengthening atlas networks with the UK, Belgium, and other parts of Europe. Our prototype uses semantic interoperability via services harmonization and ontology mediation, allowing local atlases to use their own data structures, and vocabularies (ontologies). We use standard technologies such as OGC Web Map Services (WMS) for delivering maps, and OGC Catalogue Service for the Web (CSW) for delivering and querying ISO-19139 metadata. The metadata records of a given CWA use a given ontology of terms called local ontology. Human or machine users formulate their requests using a common ontology of metadata terms, called global ontology. A CSW mediator rewrites the user’s request into CSW requests over local CSWs using their own (local) ontologies, collects the results and sends them back to the user. To extend the system, we have recently added global maritime boundaries and are also considering nearshore ocean observing system data. Ongoing work includes adding WFS, error management, and exception handling, enabling Smart Searches, and writing full documentation. This prototype is a central research project of the new International Coastal Atlas Network (ICAN), a group of 30+ organizations from 14 nations (and growing) dedicated to seeking interoperability approaches to CWAs in support of coastal zone management and the translation of coastal science to coastal decision-making.

GenoMetric Query Language: a novel approach to large-scale genomic data management.

PubMed

Masseroli, Marco; Pinoli, Pietro; Venco, Francesco; Kaitoua, Abdulrahman; Jalili, Vahid; Palluzzi, Fernando; Muller, Heiko; Ceri, Stefano

2015-06-15

Improvement of sequencing technologies and data processing pipelines is rapidly providing sequencing data, with associated high-level features, of many individual genomes in multiple biological and clinical conditions. They allow for data-driven genomic, transcriptomic and epigenomic characterizations, but require state-of-the-art 'big data' computing strategies, with abstraction levels beyond available tool capabilities. We propose a high-level, declarative GenoMetric Query Language (GMQL) and a toolkit for its use. GMQL operates downstream of raw data preprocessing pipelines and supports queries over thousands of heterogeneous datasets and samples; as such it is key to genomic 'big data' analysis. GMQL leverages a simple data model that provides both abstractions of genomic region data and associated experimental, biological and clinical metadata and interoperability between many data formats. Based on Hadoop framework and Apache Pig platform, GMQL ensures high scalability, expressivity, flexibility and simplicity of use, as demonstrated by several biological query examples on ENCODE and TCGA datasets. The GMQL toolkit is freely available for non-commercial use at http://www.bioinformatics.deib.polimi.it/GMQL/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Semantic technologies improving the recall and precision of the Mercury metadata search engine

NASA Astrophysics Data System (ADS)

Pouchard, L. C.; Cook, R. B.; Green, J.; Palanisamy, G.; Noy, N.

2011-12-01

The Mercury federated metadata system [1] was developed at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC), a NASA-sponsored effort holding datasets about biogeochemical dynamics, ecological data, and environmental processes. Mercury currently indexes over 100,000 records from several data providers conforming to community standards, e.g. EML, FGDC, FGDC Biological Profile, ISO 19115 and DIF. With the breadth of sciences represented in Mercury, the potential exists to address some key interdisciplinary scientific challenges related to climate change, its environmental and ecological impacts, and mitigation of these impacts. However, this wealth of metadata also hinders pinpointing datasets relevant to a particular inquiry. We implemented a semantic solution after concluding that traditional search approaches cannot improve the accuracy of the search results in this domain because: a) unlike everyday queries, scientific queries seek to return specific datasets with numerous parameters that may or may not be exposed to search (Deep Web queries); b) the relevance of a dataset cannot be judged by its popularity, as each scientific inquiry tends to be unique; and c)each domain science has its own terminology, more or less curated, consensual, and standardized depending on the domain. The same terms may refer to different concepts across domains (homonyms), but different terms mean the same thing (synonyms). Interdisciplinary research is arduous because an expert in a domain must become fluent in the language of another, just to find relevant datasets. Thus, we decided to use scientific ontologies because they can provide a context for a free-text search, in a way that string-based keywords never will. With added context, relevant datasets are more easily discoverable. To enable search and programmatic access to ontology entities in Mercury, we are using an instance of the BioPortal ontology repository. Mercury accesses ontology entities using the BioPortal REST API by passing a search parameter to BioPortal that may return domain context, parameter attribute, or entity annotations depending on the entity's associated ontological relationships. As Mercury's facetted search is popular with users, the results are displayed as facets. Unlike a facetted search however, the ontology-based solution implements both restrictions (improving precision) and expansions (improving recall) on the results of the initial search. For instance, "carbon" acquires a scientific context and additional key terms or phrases for discovering domain-specific datasets. A limitation of our solution is that the user must perform an additional step. Another limitation is that the quality of the newly discovered metadata is contingent upon the quality of the ontologies we use. Our solution leverages Mercury's federated capabilities to collect records from heterogeneous domains, and BioPortal's storage, curation and access capabilities for ontology entities. With minimal additional development, our approach builds on two mature systems for finding relevant datasets for interdisciplinary inquiries. We thus indicate a path forward for linking environmental, ecological and biological sciences. 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.

South Florida Information Access (SOFIA) metadata for the U.S. Geological Survey Greater Everglades place-based studies

USGS Publications Warehouse

Stapleton, Jo Anne; Sonenshein, Roy

2004-01-01

Beginning in 1995 the U.S. Geological Survey (USGS) funded scientific research to support the restoration of the Greater Everglades area and to supply decision makers and resource mangers with sound data on which to base their actions. However, none of the research and resulting data is useful if it can?t be discovered, can?t be assessed for utility in an application, can?t be accessed, or is in an undetermined format. The decision was made early in the USGS Place-Based Studies (PBS) program to create a ?one-stop? entry for information and data about USGS research results. To facilitate the discovery process some mechanism was needed to allow standardized queries about data. The FGDC metadata standard has been used to document the South Florida PBS data from the beginning.

A practical implementation for a data dictionary in an environment of diverse data sets

USGS Publications Warehouse

Sprenger, Karla K.; Larsen, Dana M.

1993-01-01

The need for a data dictionary database at the U.S. Geological Survey's EROS Data Center (EDC) was reinforced with the Earth Observing System Data and Information System (EOSDIS) requirement for consistent field definitions of data sets residing at more than one archive center. The EDC requirement addresses the existence of multiple sets with identical field definitions using various naming conventions. The EDC is developing a data dictionary database to accomplish the following foals: to standardize field names for ease in software development; to facilitate querying and updating of the date; and to generate ad hoc reports. The structure of the EDC electronic data dictionary database supports different metadata systems as well as many different data sets. A series of reports is used to keep consistency among data sets and various metadata systems.

An alternative database approach for management of SNOMED CT and improved patient data queries.

PubMed

Campbell, W Scott; Pedersen, Jay; McClay, James C; Rao, Praveen; Bastola, Dhundy; Campbell, James R

2015-10-01

SNOMED CT is the international lingua franca of terminologies for human health. Based in Description Logics (DL), the terminology enables data queries that incorporate inferences between data elements, as well as, those relationships that are explicitly stated. However, the ontologic and polyhierarchical nature of the SNOMED CT concept model make it difficult to implement in its entirety within electronic health record systems that largely employ object oriented or relational database architectures. The result is a reduction of data richness, limitations of query capability and increased systems overhead. The hypothesis of this research was that a graph database (graph DB) architecture using SNOMED CT as the basis for the data model and subsequently modeling patient data upon the semantic core of SNOMED CT could exploit the full value of the terminology to enrich and support advanced data querying capability of patient data sets. The hypothesis was tested by instantiating a graph DB with the fully classified SNOMED CT concept model. The graph DB instance was tested for integrity by calculating the transitive closure table for the SNOMED CT hierarchy and comparing the results with transitive closure tables created using current, validated methods. The graph DB was then populated with 461,171 anonymized patient record fragments and over 2.1 million associated SNOMED CT clinical findings. Queries, including concept negation and disjunction, were then run against the graph database and an enterprise Oracle relational database (RDBMS) of the same patient data sets. The graph DB was then populated with laboratory data encoded using LOINC, as well as, medication data encoded with RxNorm and complex queries performed using LOINC, RxNorm and SNOMED CT to identify uniquely described patient populations. A graph database instance was successfully created for two international releases of SNOMED CT and two US SNOMED CT editions. Transitive closure tables and descriptive statistics generated using the graph database were identical to those using validated methods. Patient queries produced identical patient count results to the Oracle RDBMS with comparable times. Database queries involving defining attributes of SNOMED CT concepts were possible with the graph DB. The same queries could not be directly performed with the Oracle RDBMS representation of the patient data and required the creation and use of external terminology services. Further, queries of undefined depth were successful in identifying unknown relationships between patient cohorts. The results of this study supported the hypothesis that a patient database built upon and around the semantic model of SNOMED CT was possible. The model supported queries that leveraged all aspects of the SNOMED CT logical model to produce clinically relevant query results. Logical disjunction and negation queries were possible using the data model, as well as, queries that extended beyond the structural IS_A hierarchy of SNOMED CT to include queries that employed defining attribute-values of SNOMED CT concepts as search parameters. As medical terminologies, such as SNOMED CT, continue to expand, they will become more complex and model consistency will be more difficult to assure. Simultaneously, consumers of data will increasingly demand improvements to query functionality to accommodate additional granularity of clinical concepts without sacrificing speed. This new line of research provides an alternative approach to instantiating and querying patient data represented using advanced computable clinical terminologies. Copyright © 2015 Elsevier Inc. All rights reserved.

NaKnowBaseTM: The EPA Nanomaterials Research ...

EPA Pesticide Factsheets

The ability to predict the environmental and health implications of engineered nanomaterials is an important research priority due to the exponential rate at which nanotechnology is being incorporated into consumer, industrial and biomedical applications. To address this need and develop predictive capability, we have created the NaKnowbaseTM, which provides a platform for the curation and dissemination of EPA nanomaterials data to support functional assay development, hazard risk models and informatic analyses. To date, we have combined relevant physicochemical parameters from other organizations (e.g., OECD, NIST), with those requested for nanomaterial data submitted to EPA under the Toxic Substances Control Act (TSCA). Physiochemical characterization data were collated from >400 unique nanomaterials including metals, metal oxides, carbon-based and hybrid materials evaluated or synthesized by EPA researchers. We constructed parameter requirements and table structures for encoding research metadata, including experimental factors and measured response variables. As a proof of concept, we illustrate how SQL-based queries facilitate a range of interrogations including, for example, relationships between nanoparticle characteristics and environmental or toxicological endpoints. The views expressed in this poster are those of the authors and may not reflect U.S. EPA policy. The purpose of this submission for clearance is an abstract for submission to a scientific

Tularosa Basin Play Fairway Analysis: Strain Analysis

DOE Data Explorer

Adam Brandt

2015-11-15

A DEM of the Tularosa Basin was divided into twelve zones, each of which a ZR ratio was calculated for. This submission has a TIFF image of the zoning designations, along with a table with respective ZR ratio calculations in the metadata.

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 Services-Oriented Architecture for Water Observations Data

NASA Astrophysics Data System (ADS)

Maidment, D. R.; Zaslavsky, I.; Valentine, D.; Tarboton, D. G.; Whitenack, T.; Whiteaker, T.; Hooper, R.; Kirschtel, D.

2009-04-01

Water observations data are time series of measurements made at point locations of water level, flow, and quality and corresponding data for climatic observations at point locations such as gaged precipitation and weather variables. A services-oriented architecture has been built for such information for the United States that has three components: hydrologic information servers, hydrologic information clients, and a centralized metadata cataloging system. These are connected using web services for observations data and metadata defined by an XML-based language called WaterML. A Hydrologic Information Server can be built by storing observations data in a relational database schema in the CUAHSI Observations Data Model, in which case, web services access to the data and metadata is automatically provided by query functions for WaterML that are wrapped around the relational database within a web server. A Hydrologic Information Server can also be constructed by custom-programming an interface to an existing water agency web site so that responds to the same queries by producing data in WaterML as do the CUAHSI Observations Data Model based servers. A Hydrologic Information Client is one which can interpret and ingest WaterML metadata and data. We have two client applications for Excel and ArcGIS and have shown how WaterML web services can be ingested into programming environments such as Matlab and Visual Basic. HIS Central, maintained at the San Diego Supercomputer Center is a repository of observational metadata for WaterML web services which presently indexes 342 million data measured at 1.75 million locations. This is the largest catalog water observational data for the United States presently in existence. As more observation networks join what we term "CUAHSI Water Data Federation", and the system accommodates a growing number of sites, measured parameters, applications, and users, rapid and reliable access to large heterogeneous hydrologic data repositories becomes critical. The CUAHSI HIS solution to the scalability and heterogeneity challenges has several components. Structural differences across the data repositories are addressed by building a standard services foundation for the exchange of hydrologic data, as derived from a common information model for observational data measured at stationary points and its implementation as a relational schema (ODM) and an XML schema (WaterML). Semantic heterogeneity is managed by mapping water quantity, water quality, and other parameters collected by government agencies and academic projects to a common ontology. The WaterML-compliant web services are indexed in a community services registry called HIS Central (hiscentral.cuahsi.org). Once a web service is registered in HIS Central, its metadata (site and variable characteristics, period of record for each variable at each site, etc.) is harvested and appended to the central catalog. The catalog is further updated as the service publisher associates the variables in the published service with ontology concepts. After this, the newly published service becomes available for spatial and semantics-based queries from online and desktop client applications developed by the project. Hydrologic system server software is now deployed at more than a dozen locations in the United States and Australia. To provide rapid access to data summaries, in particular for several nation-wide data repositories including EPA STORET, USGS NWIS, and USDA SNOTEL, we convert the observation data catalogs and databases with harvested data values into special representations that support high-performance analysis and visualization. The construction of OLAP (Online Analytical Processing) cubes, often called data cubes, is an approach to organizing and querying large multi-dimensional data collections. We have applied the OLAP techniques, as implemented in Microsoft SQL Server 2005/2008, to the analysis of the catalogs from several agencies. OLAP analysis results reflect geography and history of observation data availability from USGS NWIS, EPA STORET, and USDA SNOTEL repositories, and spatial and temporal dynamics of the available measurements for several key nutrient-related parameters. Our experience developing the CUAHSI HIS cyberinfrastructure demonstrated that efficient integration of hydrologic observations from multiple government and academic sources requires a range of technical approaches focused on managing different components of data heterogeneity and system scalability. While this submission addresses technical aspects of developing a national-scale information system for hydrologic observations, the challenges of explicating shared semantics of hydrologic observations and building a community of HIS users and developers remain critical in constructing a nation-wide federation of water data services.

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.

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.

DOIDB: Reusing DataCite's search software as metadata portal for GFZ Data Services

NASA Astrophysics Data System (ADS)

Elger, K.; Ulbricht, D.; Bertelmann, R.

2016-12-01

GFZ Data Services is the central service point for the publication of research data at the Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences (GFZ). It provides data publishing services to scientists of GFZ, associated projects, and associated institutions. The publishing services aim to make research data and physical samples visible and citable, by assigning persistent identifiers (DOI, IGSN) and by complementing existing IT infrastructure. To integrate several research domains a modular software stack that is made of free software components has been created to manage data and metadata as well as register persistent identifiers [1]. Pivotal component for the registration of DOIs is the DOIDB. It has been derived from three software components provided by DataCite [2] that moderate the registration of DOIs and the deposition of metadata, allow the dissemination of metadata, and provide a user interface to navigate and discover datasets. The DOIDB acts as a proxy to the DataCite infrastructure and in addition to the DataCite metadata schema, it allows to deposit and disseminate metadata following the schemas ISO19139 and NASA GCMD DIF. The search component has been modified to meet the requirements of a geosciences metadata portal. In particular, the search component has been altered to make use of Apache SOLRs capability to index and query spatial coordinates. Furthermore, the user interface has been adjusted to provide a first impression of the data by showing a map, summary information and subjects. DOIDB and its components are available on GitHub [3].We present a software solution for registration of DOIs that allows to integrate existing data systems, keeps track of registered DOIs, and provides a metadata portal to discover datasets [4]. [1] Ulbricht, D.; Elger, K.; Bertelmann, R.; Klump, J. panMetaDocs, eSciDoc, and DOIDB—An Infrastructure for the Curation and Publication of File-Based Datasets for GFZ Data Services. ISPRS Int. J. Geo-Inf. 2016, 5, 25. http://doi.org/10.3390/ijgi5030025[2] https://github.com/datacite[3] https://github.com/ulbricht/search/tree/doidb , https://github.com/ulbricht/mds/tree/doidb , https://github.com/ulbricht/oaip/tree/doidb[4] http://doidb.wdc-terra.org

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.

A Data Warehouse to Support Condition Based Maintenance (CBM)

DTIC Science & Technology

2005-05-01

Application ( VBA ) code sequence to import the original MAST-generated CSV and then create a single output table in DBASE IV format. The DBASE IV format...database architecture (Oracle, Sybase, MS- SQL , etc). This design includes table definitions, comments, specification of table attributes, primary and foreign...built queries and applications. Needs the application developers to construct data views. No SQL programming experience. b. Power Database User - knows

OntoFire: an ontology-based geo-portal for wildfires

NASA Astrophysics Data System (ADS)

Kalabokidis, K.; Athanasis, N.; Vaitis, M.

2011-12-01

With the proliferation of the geospatial technologies on the Internet, the role of geo-portals (i.e. gateways to Spatial Data Infrastructures) in the area of wildfires management emerges. However, keyword-based techniques often frustrate users when looking for data of interest in geo-portal environments, while little attention has been paid to shift from the conventional keyword-based to navigation-based mechanisms. The presented OntoFire system is an ontology-based geo-portal about wildfires. Through the proposed navigation mechanisms, the relationships between the data can be discovered, which would otherwise not be possible when using conventional querying techniques alone. End users can use the browsing interface to find resources of interest by using the navigation mechanisms provided. Data providers can use the publishing interface to submit new metadata, modify metadata or removing metadata in/from the catalogue. The proposed approach can improve the discovery of valuable information that is necessary to set priorities for disaster mitigation and prevention strategies. OntoFire aspires to be a focal point of integration and management of a very large amount of information, contributing in this way to the dissemination of knowledge and to the preparedness of the operational stakeholders.

An integrated content and metadata based retrieval system for art.

PubMed

Lewis, Paul H; Martinez, Kirk; Abas, Fazly Salleh; Fauzi, Mohammad Faizal Ahmad; Chan, Stephen C Y; Addis, Matthew J; Boniface, Mike J; Grimwood, Paul; Stevenson, Alison; Lahanier, Christian; Stevenson, James

2004-03-01

A new approach to image retrieval is presented in the domain of museum and gallery image collections. Specialist algorithms, developed to address specific retrieval tasks, are combined with more conventional content and metadata retrieval approaches, and implemented within a distributed architecture to provide cross-collection searching and navigation in a seamless way. External systems can access the different collections using interoperability protocols and open standards, which were extended to accommodate content based as well as text based retrieval paradigms. After a brief overview of the complete system, we describe the novel design and evaluation of some of the specialist image analysis algorithms including a method for image retrieval based on sub-image queries, retrievals based on very low quality images and retrieval using canvas crack patterns. We show how effective retrieval results can be achieved by real end-users consisting of major museums and galleries, accessing the distributed but integrated digital collections.

XRootD popularity on hadoop clusters

NASA Astrophysics Data System (ADS)

Meoni, Marco; Boccali, Tommaso; Magini, Nicolò; Menichetti, Luca; Giordano, Domenico; CMS Collaboration

2017-10-01

Performance data and metadata of the computing operations at the CMS experiment are collected through a distributed monitoring infrastructure, currently relying on a traditional Oracle database system. This paper shows how to harness Big Data architectures in order to improve the throughput and the efficiency of such monitoring. A large set of operational data - user activities, job submissions, resources, file transfers, site efficiencies, software releases, network traffic, machine logs - is being injected into a readily available Hadoop cluster, via several data streamers. The collected metadata is further organized running fast arbitrary queries; this offers the ability to test several Map&Reduce-based frameworks and measure the system speed-up when compared to the original database infrastructure. By leveraging a quality Hadoop data store and enabling an analytics framework on top, it is possible to design a mining platform to predict dataset popularity and discover patterns and correlations.

Efficient hemodynamic event detection utilizing relational databases and wavelet analysis

NASA Technical Reports Server (NTRS)

Saeed, M.; Mark, R. G.

2001-01-01

Development of a temporal query framework for time-oriented medical databases has hitherto been a challenging problem. We describe a novel method for the detection of hemodynamic events in multiparameter trends utilizing wavelet coefficients in a MySQL relational database. Storage of the wavelet coefficients allowed for a compact representation of the trends, and provided robust descriptors for the dynamics of the parameter time series. A data model was developed to allow for simplified queries along several dimensions and time scales. Of particular importance, the data model and wavelet framework allowed for queries to be processed with minimal table-join operations. A web-based search engine was developed to allow for user-defined queries. Typical queries required between 0.01 and 0.02 seconds, with at least two orders of magnitude improvement in speed over conventional queries. This powerful and innovative structure will facilitate research on large-scale time-oriented medical databases.

TAPRegExt: a VOResource Schema Extension for Describing TAP Services Version 1.0

NASA Astrophysics Data System (ADS)

Demleitner, Markus; Dowler, Patrick; Plante, Ray; Rixon, Guy; Taylor, Mark; Demleitner, Markus

2012-08-01

This document describes an XML encoding standard for metadata about services implementing the table access protocol TAP [TAP], referred to as TAPRegExt. Instance documents are part of the service's registry record or can be obtained from the service itself. They deliver information to both humans and software on the languages, output formats, and upload methods supported by the service, as well as data models implemented by the exposed tables, optional language features, and certain limits enforced by the service.

United States Transuranium and Uranium Registries. Annual report, February 1, 2003 - January 31, 2004

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

Alldredge, J. R.; Brumbaugh, T. L.; Ehrhart, Susan M.

2004-01-31

This year was my fourteenth year with the U. S. Transuranium and Uranium Registries (USTUR). How time flies! Since I became the director of the program five years ago, one of my primary goals was to increase the usefulness of the large USTUR database that consists of six tables containing personal information, medical histories, radiation exposure histories, causes of death, and the results of radiochemical analysis of organ samples collected at autopsy. It is essential that a query of one or more of these tables by USTUR researchers or by collaborating researchers provides complete and reliable information. Also, some ofmore » the tables (those without personal identifiers) are destined to appear on the USTUR website for the use of the scientific community. I am pleased to report that most of the data in the database have now been verified and formatted for easy query. It is important to note that no data were discarded; copies of the original tables were retained and the original paper documents are still available for further verification of values as needed.« less

Developing a Data Discovery Tool for Interdisciplinary Science: Leveraging a Web-based Mapping Application and Geosemantic Searching

NASA Astrophysics Data System (ADS)

Albeke, S. E.; Perkins, D. G.; Ewers, S. L.; Ewers, B. E.; Holbrook, W. S.; Miller, S. N.

2015-12-01

The sharing of data and results is paramount for advancing scientific research. The Wyoming Center for Environmental Hydrology and Geophysics (WyCEHG) is a multidisciplinary group that is driving scientific breakthroughs to help manage water resources in the Western United States. WyCEHG is mandated by the National Science Foundation (NSF) to share their data. However, the infrastructure from which to share such diverse, complex and massive amounts of data did not exist within the University of Wyoming. We developed an innovative framework to meet the data organization, sharing, and discovery requirements of WyCEHG by integrating both open and closed source software, embedded metadata tags, semantic web technologies, and a web-mapping application. The infrastructure uses a Relational Database Management System as the foundation, providing a versatile platform to store, organize, and query myriad datasets, taking advantage of both structured and unstructured formats. Detailed metadata are fundamental to the utility of datasets. We tag data with Uniform Resource Identifiers (URI's) to specify concepts with formal descriptions (i.e. semantic ontologies), thus allowing users the ability to search metadata based on the intended context rather than conventional keyword searches. Additionally, WyCEHG data are geographically referenced. Using the ArcGIS API for Javascript, we developed a web mapping application leveraging database-linked spatial data services, providing a means to visualize and spatially query available data in an intuitive map environment. Using server-side scripting (PHP), the mapping application, in conjunction with semantic search modules, dynamically communicates with the database and file system, providing access to available datasets. Our approach provides a flexible, comprehensive infrastructure from which to store and serve WyCEHG's highly diverse research-based data. This framework has not only allowed WyCEHG to meet its data stewardship requirements, but can provide a template for others to follow.

Large Survey Database: A Distributed Framework for Storage and Analysis of Large Datasets

NASA Astrophysics Data System (ADS)

Juric, Mario

2011-01-01

The Large Survey Database (LSD) is a Python framework and DBMS for distributed storage, cross-matching and querying of large survey catalogs (>10^9 rows, >1 TB). The primary driver behind its development is the analysis of Pan-STARRS PS1 data. It is specifically optimized for fast queries and parallel sweeps of positionally and temporally indexed datasets. It transparently scales to more than >10^2 nodes, and can be made to function in "shared nothing" architectures. An LSD database consists of a set of vertically and horizontally partitioned tables, physically stored as compressed HDF5 files. Vertically, we partition the tables into groups of related columns ('column groups'), storing together logically related data (e.g., astrometry, photometry). Horizontally, the tables are partitioned into partially overlapping ``cells'' by position in space (lon, lat) and time (t). This organization allows for fast lookups based on spatial and temporal coordinates, as well as data and task distribution. The design was inspired by the success of Google BigTable (Chang et al., 2006). Our programming model is a pipelined extension of MapReduce (Dean and Ghemawat, 2004). An SQL-like query language is used to access data. For complex tasks, map-reduce ``kernels'' that operate on query results on a per-cell basis can be written, with the framework taking care of scheduling and execution. The combination leverages users' familiarity with SQL, while offering a fully distributed computing environment. LSD adds little overhead compared to direct Python file I/O. In tests, we sweeped through 1.1 Grows of PanSTARRS+SDSS data (220GB) less than 15 minutes on a dual CPU machine. In a cluster environment, we achieved bandwidths of 17Gbits/sec (I/O limited). Based on current experience, we believe LSD should scale to be useful for analysis and storage of LSST-scale datasets. It can be downloaded from http://mwscience.net/lsd.

Do-It-Yourself: A Special Library's Approach to Creating Dynamic Web Pages Using Commercial Off-The-Shelf Applications

NASA Technical Reports Server (NTRS)

Steeman, Gerald; Connell, Christopher

2000-01-01

Many librarians may feel that dynamic Web pages are out of their reach, financially and technically. Yet we are reminded in library and Web design literature that static home pages are a thing of the past. This paper describes how librarians at the Institute for Defense Analyses (IDA) library developed a database-driven, dynamic intranet site using commercial off-the-shelf applications. Administrative issues include surveying a library users group for interest and needs evaluation; outlining metadata elements; and, committing resources from managing time to populate the database and training in Microsoft FrontPage and Web-to-database design. Technical issues covered include Microsoft Access database fundamentals, lessons learned in the Web-to-database process (including setting up Database Source Names (DSNs), redesigning queries to accommodate the Web interface, and understanding Access 97 query language vs. Standard Query Language (SQL)). This paper also offers tips on editing Active Server Pages (ASP) scripting to create desired results. A how-to annotated resource list closes out the paper.

The Genomes OnLine Database (GOLD) v.4: status of genomic and metagenomic projects and their associated metadata

PubMed Central

Pagani, Ioanna; Liolios, Konstantinos; Jansson, Jakob; Chen, I-Min A.; Smirnova, Tatyana; Nosrat, Bahador; Markowitz, Victor M.; Kyrpides, Nikos C.

2012-01-01

The Genomes OnLine Database (GOLD, http://www.genomesonline.org/) is a comprehensive resource for centralized monitoring of genome and metagenome projects worldwide. Both complete and ongoing projects, along with their associated metadata, can be accessed in GOLD through precomputed tables and a search page. As of September 2011, GOLD, now on version 4.0, contains information for 11 472 sequencing projects, of which 2907 have been completed and their sequence data has been deposited in a public repository. Out of these complete projects, 1918 are finished and 989 are permanent drafts. Moreover, GOLD contains information for 340 metagenome studies associated with 1927 metagenome samples. GOLD continues to expand, moving toward the goal of providing the most comprehensive repository of metadata information related to the projects and their organisms/environments in accordance with the Minimum Information about any (x) Sequence specification and beyond. PMID:22135293

The Genomes On Line Database (GOLD) in 2009: status of genomic and metagenomic projects and their associated metadata.

PubMed

Liolios, Konstantinos; Chen, I-Min A; Mavromatis, Konstantinos; Tavernarakis, Nektarios; Hugenholtz, Philip; Markowitz, Victor M; Kyrpides, Nikos C

2010-01-01

The Genomes On Line Database (GOLD) is a comprehensive resource for centralized monitoring of genome and metagenome projects worldwide. Both complete and ongoing projects, along with their associated metadata, can be accessed in GOLD through precomputed tables and a search page. As of September 2009, GOLD contains information for more than 5800 sequencing projects, of which 1100 have been completed and their sequence data deposited in a public repository. GOLD continues to expand, moving toward the goal of providing the most comprehensive repository of metadata information related to the projects and their organisms/environments in accordance with the Minimum Information about a (Meta)Genome Sequence (MIGS/MIMS) specification. GOLD is available at: http://www.genomesonline.org and has a mirror site at the Institute of Molecular Biology and Biotechnology, Crete, Greece, at: http://gold.imbb.forth.gr/

The Genomes OnLine Database (GOLD) v.4: status of genomic and metagenomic projects and their associated metadata.

PubMed

Pagani, Ioanna; Liolios, Konstantinos; Jansson, Jakob; Chen, I-Min A; Smirnova, Tatyana; Nosrat, Bahador; Markowitz, Victor M; Kyrpides, Nikos C

2012-01-01

The Genomes OnLine Database (GOLD, http://www.genomesonline.org/) is a comprehensive resource for centralized monitoring of genome and metagenome projects worldwide. Both complete and ongoing projects, along with their associated metadata, can be accessed in GOLD through precomputed tables and a search page. As of September 2011, GOLD, now on version 4.0, contains information for 11,472 sequencing projects, of which 2907 have been completed and their sequence data has been deposited in a public repository. Out of these complete projects, 1918 are finished and 989 are permanent drafts. Moreover, GOLD contains information for 340 metagenome studies associated with 1927 metagenome samples. GOLD continues to expand, moving toward the goal of providing the most comprehensive repository of metadata information related to the projects and their organisms/environments in accordance with the Minimum Information about any (x) Sequence specification and beyond.

The Genomes On Line Database (GOLD) in 2009: status of genomic and metagenomic projects and their associated metadata

PubMed Central

Liolios, Konstantinos; Chen, I-Min A.; Mavromatis, Konstantinos; Tavernarakis, Nektarios; Hugenholtz, Philip; Markowitz, Victor M.; Kyrpides, Nikos C.

2010-01-01

The Genomes On Line Database (GOLD) is a comprehensive resource for centralized monitoring of genome and metagenome projects worldwide. Both complete and ongoing projects, along with their associated metadata, can be accessed in GOLD through precomputed tables and a search page. As of September 2009, GOLD contains information for more than 5800 sequencing projects, of which 1100 have been completed and their sequence data deposited in a public repository. GOLD continues to expand, moving toward the goal of providing the most comprehensive repository of metadata information related to the projects and their organisms/environments in accordance with the Minimum Information about a (Meta)Genome Sequence (MIGS/MIMS) specification. GOLD is available at: http://www.genomesonline.org and has a mirror site at the Institute of Molecular Biology and Biotechnology, Crete, Greece, at: http://gold.imbb.forth.gr/ PMID:19914934

Omicseq: a web-based search engine for exploring omics datasets

PubMed Central

Sun, Xiaobo; Pittard, William S.; Xu, Tianlei; Chen, Li; Zwick, Michael E.; Jiang, Xiaoqian; Wang, Fusheng

2017-01-01

Abstract The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve ‘findability’ of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant. Omicseq is freely available at http://www.omicseq.org. PMID:28402462

Analyzing Document Retrievability in Patent Retrieval Settings

NASA Astrophysics Data System (ADS)

Bashir, Shariq; Rauber, Andreas

Most information retrieval settings, such as web search, are typically precision-oriented, i.e. they focus on retrieving a small number of highly relevant documents. However, in specific domains, such as patent retrieval or law, recall becomes more relevant than precision: in these cases the goal is to find all relevant documents, requiring algorithms to be tuned more towards recall at the cost of precision. This raises important questions with respect to retrievability and search engine bias: depending on how the similarity between a query and documents is measured, certain documents may be more or less retrievable in certain systems, up to some documents not being retrievable at all within common threshold settings. Biases may be oriented towards popularity of documents (increasing weight of references), towards length of documents, favour the use of rare or common words; rely on structural information such as metadata or headings, etc. Existing accessibility measurement techniques are limited as they measure retrievability with respect to all possible queries. In this paper, we improve accessibility measurement by considering sets of relevant and irrelevant queries for each document. This simulates how recall oriented users create their queries when searching for relevant information. We evaluate retrievability scores using a corpus of patents from US Patent and Trademark Office.

SAS- Semantic Annotation Service for Geoscience resources on the web

NASA Astrophysics Data System (ADS)

Elag, M.; Kumar, P.; Marini, L.; Li, R.; Jiang, P.

2015-12-01

There is a growing need for increased integration across the data and model resources that are disseminated on the web to advance their reuse across different earth science applications. Meaningful reuse of resources requires semantic metadata to realize the semantic web vision for allowing pragmatic linkage and integration among resources. Semantic metadata associates standard metadata with resources to turn them into semantically-enabled resources on the web. However, the lack of a common standardized metadata framework as well as the uncoordinated use of metadata fields across different geo-information systems, has led to a situation in which standards and related Standard Names abound. To address this need, we have designed SAS to provide a bridge between the core ontologies required to annotate resources and information systems in order to enable queries and analysis over annotation from a single environment (web). SAS is one of the services that are provided by the Geosematnic framework, which is a decentralized semantic framework to support the integration between models and data and allow semantically heterogeneous to interact with minimum human intervention. Here we present the design of SAS and demonstrate its application for annotating data and models. First we describe how predicates and their attributes are extracted from standards and ingested in the knowledge-base of the Geosemantic framework. Then we illustrate the application of SAS in annotating data managed by SEAD and annotating simulation models that have web interface. SAS is a step in a broader approach to raise the quality of geoscience data and models that are published on the web and allow users to better search, access, and use of the existing resources based on standard vocabularies that are encoded and published using semantic technologies.

StarView: The object oriented design of the ST DADS user interface

NASA Technical Reports Server (NTRS)

Williams, J. D.; Pollizzi, J. A.

1992-01-01

StarView is the user interface being developed for the Hubble Space Telescope Data Archive and Distribution Service (ST DADS). ST DADS is the data archive for HST observations and a relational database catalog describing the archived data. Users will use StarView to query the catalog and select appropriate datasets for study. StarView sends requests for archived datasets to ST DADS which processes the requests and returns the database to the user. StarView is designed to be a powerful and extensible user interface. Unique features include an internal relational database to navigate query results, a form definition language that will work with both CRT and X interfaces, a data definition language that will allow StarView to work with any relational database, and the ability to generate adhoc queries without requiring the user to understand the structure of the ST DADS catalog. Ultimately, StarView will allow the user to refine queries in the local database for improved performance and merge in data from external sources for correlation with other query results. The user will be able to create a query from single or multiple forms, merging the selected attributes into a single query. Arbitrary selection of attributes for querying is supported. The user will be able to select how query results are viewed. A standard form or table-row format may be used. Navigation capabilities are provided to aid the user in viewing query results. Object oriented analysis and design techniques were used in the design of StarView to support the mechanisms and concepts required to implement these features. One such mechanism is the Model-View-Controller (MVC) paradigm. The MVC allows the user to have multiple views of the underlying database, while providing a consistent mechanism for interaction regardless of the view. This approach supports both CRT and X interfaces while providing a common mode of user interaction. Another powerful abstraction is the concept of a Query Model. This concept allows a single query to be built form a single or multiple forms before it is submitted to ST DADS. Supporting this concept is the adhoc query generator which allows the user to select and qualify an indeterminate number attributes from the database. The user does not need any knowledge of how the joins across various tables are to be resolved. The adhoc generator calculates the joins automatically and generates the correct SQL query.

The BioPrompt-box: an ontology-based clustering tool for searching in biological databases.

PubMed

Corsi, Claudio; Ferragina, Paolo; Marangoni, Roberto

2007-03-08

High-throughput molecular biology provides new data at an incredible rate, so that the increase in the size of biological databanks is enormous and very rapid. This scenario generates severe problems not only at indexing time, where suitable algorithmic techniques for data indexing and retrieval are required, but also at query time, since a user query may produce such a large set of results that their browsing and "understanding" becomes humanly impractical. This problem is well known to the Web community, where a new generation of Web search engines is being developed, like Vivisimo. These tools organize on-the-fly the results of a user query in a hierarchy of labeled folders that ease their browsing and knowledge extraction. We investigate this approach on biological data, and propose the so called The BioPrompt-boxsoftware system which deploys ontology-driven clustering strategies for making the searching process of biologists more efficient and effective. The BioPrompt-box (Bpb) defines a document as a biological sequence plus its associated meta-data taken from the underneath databank--like references to ontologies or to external databanks, and plain texts as comments of researchers and (title, abstracts or even body of) papers. Bpboffers several tools to customize the search and the clustering process over its indexed documents. The user can search a set of keywords within a specific field of the document schema, or can execute Blastto find documents relative to homologue sequences. In both cases the search task returns a set of documents (hits) which constitute the answer to the user query. Since the number of hits may be large, Bpbclusters them into groups of homogenous content, organized as a hierarchy of labeled clusters. The user can actually choose among several ontology-based hierarchical clustering strategies, each offering a different "view" of the returned hits. Bpbcomputes these views by exploiting the meta-data present within the retrieved documents such as the references to Gene Ontology, the taxonomy lineage, the organism and the keywords. Of course, the approach is flexible enough to leave room for future additions of other meta-information. The ultimate goal of the clustering process is to provide the user with several different readings of the (maybe numerous) query results and show possible hidden correlations among them, thus improving their browsing and understanding. Bpb is a powerful search engine that makes it very easy to perform complex queries over the indexed databanks (currently only UNIPROT is considered). The ontology-based clustering approach is efficient and effective, and could thus be applied successfully to larger databanks, like GenBank or EMBL.

The BioPrompt-box: an ontology-based clustering tool for searching in biological databases

PubMed Central

Corsi, Claudio; Ferragina, Paolo; Marangoni, Roberto

2007-01-01

Background High-throughput molecular biology provides new data at an incredible rate, so that the increase in the size of biological databanks is enormous and very rapid. This scenario generates severe problems not only at indexing time, where suitable algorithmic techniques for data indexing and retrieval are required, but also at query time, since a user query may produce such a large set of results that their browsing and "understanding" becomes humanly impractical. This problem is well known to the Web community, where a new generation of Web search engines is being developed, like Vivisimo. These tools organize on-the-fly the results of a user query in a hierarchy of labeled folders that ease their browsing and knowledge extraction. We investigate this approach on biological data, and propose the so called The BioPrompt-boxsoftware system which deploys ontology-driven clustering strategies for making the searching process of biologists more efficient and effective. Results The BioPrompt-box (Bpb) defines a document as a biological sequence plus its associated meta-data taken from the underneath databank – like references to ontologies or to external databanks, and plain texts as comments of researchers and (title, abstracts or even body of) papers. Bpboffers several tools to customize the search and the clustering process over its indexed documents. The user can search a set of keywords within a specific field of the document schema, or can execute Blastto find documents relative to homologue sequences. In both cases the search task returns a set of documents (hits) which constitute the answer to the user query. Since the number of hits may be large, Bpbclusters them into groups of homogenous content, organized as a hierarchy of labeled clusters. The user can actually choose among several ontology-based hierarchical clustering strategies, each offering a different "view" of the returned hits. Bpbcomputes these views by exploiting the meta-data present within the retrieved documents such as the references to Gene Ontology, the taxonomy lineage, the organism and the keywords. Of course, the approach is flexible enough to leave room for future additions of other meta-information. The ultimate goal of the clustering process is to provide the user with several different readings of the (maybe numerous) query results and show possible hidden correlations among them, thus improving their browsing and understanding. Conclusion Bpb is a powerful search engine that makes it very easy to perform complex queries over the indexed databanks (currently only UNIPROT is considered). The ontology-based clustering approach is efficient and effective, and could thus be applied successfully to larger databanks, like GenBank or EMBL. PMID:17430575

3D mapping of existing observing capabilities in the frame of GAIA-CLIM H2020 project

NASA Astrophysics Data System (ADS)

Emanuele, Tramutola; Madonna, Fabio; Marco, Rosoldi; Francesco, Amato

2017-04-01

The aim of the Gap Analysis for Integrated Atmospheric ECV CLImate Monitoring (GAIA-CLIM) project is to improve our ability to use ground-based and sub-orbital observations to characterise satellite observations for a number of atmospheric Essential Climate Variables (ECVs). The key outcomes will be a "Virtual Observatory" (VO) facility of co-locations and their uncertainties and a report on gaps in capabilities or understanding, which shall be used to inform subsequent Horizon 2020 activities. In particular, Work Package 1 (WP1) of the GAIA-CLIM project is devoted to the geographical mapping of existing non-satellite measurement capabilities for a number of ECVs in the atmospheric, oceanic and terrestrial domains. The work carried out within WP1 has allowed to provide the users with an up-to-date geographical identification, at the European and global scales, of current surface-based, balloon-based and oceanic (floats) observing capabilities on an ECV by ECV basis for several parameters which can be obtained using space-based observations from past, present and planned satellite missions. Having alighted on a set of metadata schema to follow, a consistent collection of discovery metadata has been provided into a common structure and will be made available to users through the GAIA-CLIM VO in 2018. Metadata can be interactively visualized through a 3D Graphical User Interface. The metadataset includes 54 plausible networks and 2 aircraft permanent infrastructures for EO Characterisation in the context of GAIA-CLIM currently operating on different spatial domains and measuring different ECVs using one or more measurement techniques. Each classified network has in addition been assessed for suitability against metrological criteria to identifyy those with a level of maturity which enables closure on a comparison with satellite measurements. The metadata GUI is based on Cesium, a virtual globe freeware and open source written in Javascript. It allows users to apply different filters to the data displayed on the globe, selecting data per ECV, network, measurements type and level of maturity. Filtering is operated with a query to GeoServer web application through the WFS interface on a data layer configured on our DB Postgres with PostGIS extension; filters set on the GUI are expressed using ECQL (Extended Common Query Language). The GUI allows to visualize in real-time the current non-satellite observing capabilities along with the satellite platforms measuring the same ECVs. Satellite ground track and footprint of the instruments on board can be also visualized. This work contributes to improve metadata and web map services and to facilitate users' experience in the spatio-temporal analysis of Earth Observation data.

Using Bitmap Indexing Technology for Combined Numerical and TextQueries

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

Stockinger, Kurt; Cieslewicz, John; Wu, Kesheng

2006-10-16

In this paper, we describe a strategy of using compressedbitmap indices to speed up queries on both numerical data and textdocuments. By using an efficient compression algorithm, these compressedbitmap indices are compact even for indices with millions of distinctterms. Moreover, bitmap indices can be used very efficiently to answerBoolean queries over text documents involving multiple query terms.Existing inverted indices for text searches are usually inefficient forcorpora with a very large number of terms as well as for queriesinvolving a large number of hits. We demonstrate that our compressedbitmap index technology overcomes both of those short-comings. In aperformance comparison against amore » commonly used database system, ourindices answer queries 30 times faster on average. To provide full SQLsupport, we integrated our indexing software, called FastBit, withMonetDB. The integrated system MonetDB/FastBit provides not onlyefficient searches on a single table as FastBit does, but also answersjoin queries efficiently. Furthermore, MonetDB/FastBit also provides avery efficient retrieval mechanism of result records.« less

Using JavaScript and the FDSN web service to create an interactive earthquake information system

NASA Astrophysics Data System (ADS)

Fischer, Kasper D.

2015-04-01

The FDSN web service provides a web interface to access earthquake meta-data (e. g. event or station information) and waveform date over the internet. Requests are send to a server as URLs and the output is either XML or miniSEED. This makes it hard to read by humans but easy to process with different software. Different data centers are already supporting the FDSN web service, e. g. USGS, IRIS, ORFEUS. The FDSN web service is also part of the Seiscomp3 (http://www.seiscomp3.org) software. The Seismological Observatory of the Ruhr-University switched to Seiscomp3 as the standard software for the analysis of mining induced earthquakes at the beginning of 2014. This made it necessary to create a new web-based earthquake information service for the publication of results to the general public. This has be done by processing the output of a FDSN web service query by javascript running in a standard browser. The result is an interactive map presenting the observed events and further information of events and stations on a single web page as a table and on a map. In addition the user can download event information, waveform data and station data in different formats like miniSEED, quakeML or FDSNxml. The developed code and all used libraries are open source and freely available.

Creating Actionable Data from an Optical Depth Measurement Network using RDF

NASA Astrophysics Data System (ADS)

Freemantle, J. R.; O'Neill, N. T.; Lumb, L. I.; Abboud, I.; McArthur, B.

2010-12-01

The AEROCAN sunphotometery network has, for more than a decade, generated optical indicators of aerosol concentration and size on a regional and national scale. We believe this optical information can be rendered more “actionable” to the health care community by developing a technical and interpretative information-sharing geospatial strategy with that community. By actionable data we mean information that is presented in manner that can be understood and then used in the decision making process. The decision may be that of a technical professional, a policy maker or a machine. The information leading up to a decision may come from many sources; this means it is particularly important that data are well defined across knowledge fields, in our case atmospheric science and respiratory health science. As part of the AEROCAN operational quality assurance (QA) methodology we have written automatic procedures to make some of the AEROCAN data more accessible or “actionable”. Tim Berners-Lee has advocated making datasets, “Linked Data”, available on the web with a proper structural description (metadata). We have been using RDF (Resource Description Framework) to enhance the utility of our sunphotometer data; the resulting self-describing representation is structured so that it is machine readable. This allows semantically based queries (e.g., via SPARQL) on our dataset that in the past were only viewable as passive Web tables of data.

Analyzing Enron Data: Bitmap Indexing Outperforms MySQL Queries bySeveral Orders of Magnitude

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

Stockinger, Kurt; Rotem, Doron; Shoshani, Arie

2006-01-28

FastBit is an efficient, compressed bitmap indexing technology that was developed in our group. In this report we evaluate the performance of MySQL and FastBit for analyzing the email traffic of the Enron dataset. The first finding shows that materializing the join results of several tables significantly improves the query performance. The second finding shows that FastBit outperforms MySQL by several orders of magnitude.

MOPED enables discoveries through consistently processed proteomics data

PubMed Central

Higdon, Roger; Stewart, Elizabeth; Stanberry, Larissa; Haynes, Winston; Choiniere, John; Montague, Elizabeth; Anderson, Nathaniel; Yandl, Gregory; Janko, Imre; Broomall, William; Fishilevich, Simon; Lancet, Doron; Kolker, Natali; Kolker, Eugene

2014-01-01

The Model Organism Protein Expression Database (MOPED, http://moped.proteinspire.org), is an expanding proteomics resource to enable biological and biomedical discoveries. MOPED aggregates simple, standardized and consistently processed summaries of protein expression and metadata from proteomics (mass spectrometry) experiments from human and model organisms (mouse, worm and yeast). The latest version of MOPED adds new estimates of protein abundance and concentration, as well as relative (differential) expression data. MOPED provides a new updated query interface that allows users to explore information by organism, tissue, localization, condition, experiment, or keyword. MOPED supports the Human Proteome Project’s efforts to generate chromosome and diseases specific proteomes by providing links from proteins to chromosome and disease information, as well as many complementary resources. MOPED supports a new omics metadata checklist in order to harmonize data integration, analysis and use. MOPED’s development is driven by the user community, which spans 90 countries guiding future development that will transform MOPED into a multi-omics resource. MOPED encourages users to submit data in a simple format. They can use the metadata a checklist generate a data publication for this submission. As a result, MOPED will provide even greater insights into complex biological processes and systems and enable deeper and more comprehensive biological and biomedical discoveries. PMID:24350770

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.

Image BOSS: a biomedical object storage system

NASA Astrophysics Data System (ADS)

Stacy, Mahlon C.; Augustine, Kurt E.; Robb, Richard A.

1997-05-01

Researchers using biomedical images have data management needs which are oriented perpendicular to clinical PACS. The image BOSS system is designed to permit researchers to organize and select images based on research topic, image metadata, and a thumbnail of the image. Image information is captured from existing images in a Unix based filesystem, stored in an object oriented database, and presented to the user in a familiar laboratory notebook metaphor. In addition, the ImageBOSS is designed to provide an extensible infrastructure for future content-based queries directly on the images.

Neural networks and logical reasoning systems: a translation table.

PubMed

Martins, J; Mendes, R V

2001-04-01

A correspondence is established between the basic elements of logic reasoning systems (knowledge bases, rules, inference and queries) and the structure and dynamical evolution laws of neural networks. The correspondence is pictured as a translation dictionary which might allow to go back and forth between symbolic and network formulations, a desirable step in learning-oriented systems and multicomputer networks. In the framework of Horn clause logics, it is found that atomic propositions with n arguments correspond to nodes with nth order synapses, rules to synaptic intensity constraints, forward chaining to synaptic dynamics and queries either to simple node activation or to a query tensor dynamics.

Application of XML to Journal Table Archiving

NASA Astrophysics Data System (ADS)

Shaya, E. J.; Blackwell, J. H.; Gass, J. E.; Kargatis, V. E.; Schneider, G. L.; Weiland, J. L.; Borne, K. D.; White, R. A.; Cheung, C. Y.

1998-12-01

The Astronomical Data Center (ADC) at the NASA Goddard Space Flight Center is a major archive for machine-readable astronomical data tables. Many ADC tables are derived from published journal articles. Article tables are reformatted to be machine-readable and documentation is crafted to facilitate proper reuse by researchers. The recent switch of journals to web based electronic format has resulted in the generation of large amounts of tabular data that could be captured into machine-readable archive format at fairly low cost. The large data flow of the tables from all major North American astronomical journals (a factor of 100 greater than the present rate at the ADC) necessitates the development of rigorous standards for the exchange of data between researchers, publishers, and the archives. We have selected a suitable markup language that can fully describe the large variety of astronomical information contained in ADC tables. The eXtensible Markup Language XML is a powerful internet-ready documentation format for data. It provides a precise and clear data description language that is both machine- and human-readable. It is rapidly becoming the standard format for business and information transactions on the internet and it is an ideal common metadata exchange format. By labelling, or "marking up", all elements of the information content, documents are created that computers can easily parse. An XML archive can easily and automatically be maintained, ingested into standard databases or custom software, and even totally restructured whenever necessary. Structuring astronomical data into XML format will enable efficient and focused search capabilities via off-the-shelf software. The ADC is investigating XML's expanded hyperlinking power to enhance connectivity within the ADC data/metadata and developing XSL display scripts to enhance display of astronomical data. The ADC XML Definition Type Document can be viewed at http://messier.gsfc.nasa.gov/dtdhtml/DTD-TREE.html

Omicseq: a web-based search engine for exploring omics datasets.

PubMed

Sun, Xiaobo; Pittard, William S; Xu, Tianlei; Chen, Li; Zwick, Michael E; Jiang, Xiaoqian; Wang, Fusheng; Qin, Zhaohui S

2017-07-03

The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve 'findability' of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant. Omicseq is freely available at http://www.omicseq.org. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

The Chandra Source Catalog: User Interface

NASA Astrophysics Data System (ADS)

Bonaventura, Nina; Evans, I. N.; Harbo, P. N.; Rots, A. H.; Tibbetts, M. S.; Van Stone, D. W.; Zografou, P.; Anderson, C. S.; Chen, J. C.; Davis, J. E.; Doe, S. M.; Evans, J. D.; Fabbiano, G.; Galle, E.; Gibbs, D. G.; Glotfelty, K. J.; Grier, J. D.; Hain, R.; Hall, D. M.; He, X.; Houck, J. C.; Karovska, M.; Lauer, J.; McCollough, M. L.; McDowell, J. C.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Nichols, J. S.; Nowak, M. A.; Plummer, D. A.; Primini, F. A.; Refsdal, B. L.; Siemiginowska, A. L.; Sundheim, B. A.; Winkelman, S. L.

2009-01-01

The Chandra Source Catalog (CSC) is the definitive catalog of all X-ray sources detected by Chandra. The CSC is presented to the user in two tables: the Master Chandra Source Table and the Table of Individual Source Observations. Each distinct X-ray source identified in the CSC is represented by a single master source entry and one or more individual source entries. If a source is unaffected by confusion and pile-up in multiple observations, the individual source observations are merged to produce a master source. In each table, a row represents a source, and each column a quantity that is officially part of the catalog. The CSC contains positions and multi-band fluxes for the sources, as well as derived spatial, spectral, and temporal source properties. The CSC also includes associated source region and full-field data products for each source, including images, photon event lists, light curves, and spectra. The master source properties represent the best estimates of the properties of a source, and are presented in the following categories: Position and Position Errors, Source Flags, Source Extent and Errors, Source Fluxes, Source Significance, Spectral Properties, and Source Variability. The CSC Data Access GUI provides direct access to the source properties and data products contained in the catalog. The user may query the catalog database via a web-style search or an SQL command-line query. Each query returns a table of source properties, along with the option to browse and download associated data products. The GUI is designed to run in a web browser with Java version 1.5 or higher, and may be accessed via a link on the CSC website homepage (http://cxc.harvard.edu/csc/). As an alternative to the GUI, the contents of the CSC may be accessed directly through a URL, using the command-line tool, cURL. Support: NASA contract NAS8-03060 (CXC).

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.

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.

Aggregator: a machine learning approach to identifying MEDLINE articles that derive from the same underlying clinical trial.

PubMed

Shao, Weixiang; Adams, Clive E; Cohen, Aaron M; Davis, John M; McDonagh, Marian S; Thakurta, Sujata; Yu, Philip S; Smalheiser, Neil R

2015-03-01

It is important to identify separate publications that report outcomes from the same underlying clinical trial, in order to avoid over-counting these as independent pieces of evidence. We created positive and negative training sets (comprised of pairs of articles reporting on the same condition and intervention) that were, or were not, linked to the same clinicaltrials.gov trial registry number. Features were extracted from MEDLINE and PubMed metadata; pairwise similarity scores were modeled using logistic regression. Article pairs from the same trial were identified with high accuracy (F1 score=0.843). We also created a clustering tool, Aggregator, that takes as input a PubMed user query for RCTs on a given topic, and returns article clusters predicted to arise from the same clinical trial. Although painstaking examination of full-text may be needed to be conclusive, metadata are surprisingly accurate in predicting when two articles derive from the same underlying clinical trial. Copyright © 2014 Elsevier Inc. All rights reserved.

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

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/

Grid Enabled Geospatial Catalogue Web Service

NASA Technical Reports Server (NTRS)

Chen, Ai-Jun; Di, Li-Ping; Wei, Ya-Xing; Liu, Yang; Bui, Yu-Qi; Hu, Chau-Min; Mehrotra, Piyush

2004-01-01

Geospatial Catalogue Web Service is a vital service for sharing and interoperating volumes of distributed heterogeneous geospatial resources, such as data, services, applications, and their replicas over the web. Based on the Grid technology and the Open Geospatial Consortium (0GC) s Catalogue Service - Web Information Model, this paper proposes a new information model for Geospatial Catalogue Web Service, named as GCWS which can securely provides Grid-based publishing, managing and querying geospatial data and services, and the transparent access to the replica data and related services under the Grid environment. This information model integrates the information model of the Grid Replica Location Service (RLS)/Monitoring & Discovery Service (MDS) with the information model of OGC Catalogue Service (CSW), and refers to the geospatial data metadata standards from IS0 19115, FGDC and NASA EOS Core System and service metadata standards from IS0 191 19 to extend itself for expressing geospatial resources. Using GCWS, any valid geospatial user, who belongs to an authorized Virtual Organization (VO), can securely publish and manage geospatial resources, especially query on-demand data in the virtual community and get back it through the data-related services which provide functions such as subsetting, reformatting, reprojection etc. This work facilitates the geospatial resources sharing and interoperating under the Grid environment, and implements geospatial resources Grid enabled and Grid technologies geospatial enabled. It 2!so makes researcher to focus on science, 2nd not cn issues with computing ability, data locztic, processir,g and management. GCWS also is a key component for workflow-based virtual geospatial data producing.

MeRy-B: a web knowledgebase for the storage, visualization, analysis and annotation of plant NMR metabolomic profiles

PubMed Central

2011-01-01

Background Improvements in the techniques for metabolomics analyses and growing interest in metabolomic approaches are resulting in the generation of increasing numbers of metabolomic profiles. Platforms are required for profile management, as a function of experimental design, and for metabolite identification, to facilitate the mining of the corresponding data. Various databases have been created, including organism-specific knowledgebases and analytical technique-specific spectral databases. However, there is currently no platform meeting the requirements for both profile management and metabolite identification for nuclear magnetic resonance (NMR) experiments. Description MeRy-B, the first platform for plant 1H-NMR metabolomic profiles, is designed (i) to provide a knowledgebase of curated plant profiles and metabolites obtained by NMR, together with the corresponding experimental and analytical metadata, (ii) for queries and visualization of the data, (iii) to discriminate between profiles with spectrum visualization tools and statistical analysis, (iv) to facilitate compound identification. It contains lists of plant metabolites and unknown compounds, with information about experimental conditions, the factors studied and metabolite concentrations for several plant species, compiled from more than one thousand annotated NMR profiles for various organs or tissues. Conclusion MeRy-B manages all the data generated by NMR-based plant metabolomics experiments, from description of the biological source to identification of the metabolites and determinations of their concentrations. It is the first database allowing the display and overlay of NMR metabolomic profiles selected through queries on data or metadata. MeRy-B is available from http://www.cbib.u-bordeaux2.fr/MERYB/index.php. PMID:21668943

Defining datasets and creating data dictionaries for quality improvement and research in chronic disease using routinely collected data: an ontology-driven approach.

PubMed

de Lusignan, Simon; Liaw, Siaw-Teng; Michalakidis, Georgios; Jones, Simon

2011-01-01

The burden of chronic disease is increasing, and research and quality improvement will be less effective if case finding strategies are suboptimal. To describe an ontology-driven approach to case finding in chronic disease and how this approach can be used to create a data dictionary and make the codes used in case finding transparent. A five-step process: (1) identifying a reference coding system or terminology; (2) using an ontology-driven approach to identify cases; (3) developing metadata that can be used to identify the extracted data; (4) mapping the extracted data to the reference terminology; and (5) creating the data dictionary. Hypertension is presented as an exemplar. A patient with hypertension can be represented by a range of codes including diagnostic, history and administrative. Metadata can link the coding system and data extraction queries to the correct data mapping and translation tool, which then maps it to the equivalent code in the reference terminology. The code extracted, the term, its domain and subdomain, and the name of the data extraction query can then be automatically grouped and published online as a readily searchable data dictionary. An exemplar online is: www.clininf.eu/qickd-data-dictionary.html Adopting an ontology-driven approach to case finding could improve the quality of disease registers and of research based on routine data. It would offer considerable advantages over using limited datasets to define cases. This approach should be considered by those involved in research and quality improvement projects which utilise routine data.

The NOAO Data Lab PHAT Photometry Database

NASA Astrophysics Data System (ADS)

Olsen, Knut; Williams, Ben; Fitzpatrick, Michael; PHAT Team

2018-01-01

We present a database containing both the combined photometric object catalog and the single epoch measurements from the Panchromatic Hubble Andromeda Treasury (PHAT). This database is hosted by the NOAO Data Lab (http://datalab.noao.edu), and as such exposes a number of data services to the PHAT photometry, including access through a Table Access Protocol (TAP) service, direct PostgreSQL queries, web-based and programmatic query interfaces, remote storage space for personal database tables and files, and a JupyterHub-based Notebook analysis environment, as well as image access through a Simple Image Access (SIA) service. We show how the Data Lab database and Jupyter Notebook environment allow for straightforward and efficient analyses of PHAT catalog data, including maps of object density, depth, and color, extraction of light curves of variable objects, and proper motion exploration.

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.

Small numbers, disclosure risk, security, and reliability issues in Web-based data query systems.

PubMed

Rudolph, Barbara A; Shah, Gulzar H; Love, Denise

2006-01-01

This article describes the process for developing consensus guidelines and tools for releasing public health data via the Web and highlights approaches leading agencies have taken to balance disclosure risk with public dissemination of reliable health statistics. An agency's choice of statistical methods for improving the reliability of released data for Web-based query systems is based upon a number of factors, including query system design (dynamic analysis vs preaggregated data and tables), population size, cell size, data use, and how data will be supplied to users. The article also describes those efforts that are necessary to reduce the risk of disclosure of an individual's protected health information.

Beyond 10 Years of Evolving the IGSN Architecture: What's Next?

NASA Astrophysics Data System (ADS)

Lehnert, K.; Arko, R. A.

2016-12-01

The IGSN was developed as part of a US NSF-funded project, which started in 2004 to establish a registry for sample metadata, the System for Earth Sample Registration (SESAR). The initial version of the system provided a centralized solution for users to submit information about their samples and obtain IGSNs and bar codes. A new distributed architecture for the IGSN was designed at a workshop in 2011 that aimed to advance the global implementation of the IGSN. The workshop led to the founding of an international non-profit organization, the IGSN e.V., that adopted the governance model of the DataCite consortium as a non-profit membership organization and its architecture with a central registry and a network of distributed Allocating Agents that provide registration services to the users. Recent progress came at a workshop in 2015, where stakeholders from both geoscience and life science disciplines drafted a standard IGSN metadata schema for describing samples with an essential set of properties about the sample's origin and classification, creating a "birth certificate" for the sample. Consensus was reached that the IGSN should also be used to identify sampling features and collection of samples. The IGSN e.V. global network has steadily grown, with now members in 4 continents and 5 Allocating Agents operational in the US, Australia, and Europe. A Central Catalog has been established at the IGSN Management Office that harvests "birth certificate" metadata records from Allocating Agents via the Open Archives Initiative Protocol for Metadata Harvest (OAI-PMH), and publishes them as a Linked Open Data graph using the Resource Description Framework (RDF) and RDF Query Language (SPARQL) for reuse by Semantic Web clients. Next developments will include a web-based validation service that allows journal editors to check the validity of IGSNs and compliance with metadata requirements, and use of community-recommended vocabularies for specific disciplines.

A Software Prototype For Accessing Large Climate Simulation Data Through Digital Globe Interface

NASA Astrophysics Data System (ADS)

Chaudhuri, A.; Sorokine, A.

2010-12-01

The IPCC suite of global Earth system models produced terabytes of data for the CMIP3/AR4 archive and is expected to reach the petabyte scale by CMIP5/AR5. Dynamic downscaling of global models based on regional climate models can potentially lead to even larger data volumes. The model simulations for global or regional climate models like CCSM3 or WRF are typically run on supercomputers like the ORNL/DOE Jaguar and the results are stored on high performance storage systems. Access to these results from a user workstation is impeded by a number of factors such as enormous data size, limited bandwidth of standard office networks, data formats which are not fully supported by applications. So, a user-friendly interface for accessing and visualizing these results over standard Internet connection is required to facilitate collaborative work among geographically dispersed groups of scientists. To address this problem, we have developed a virtual globe based application which enables the scientists to query, visualize and analyze the results without the need of large data transfers to desktops and department-level servers. We have used open-source NASA WorldWind as a virtual globe platform and extended it with modules capable of visualizing model outputs stored in NetCDF format, while the data resides on the high-performance system. Based on the query placed by the scientist, our system initiates data processing routines on the high performance storage system to subset the data and reduce its size and then transfer it back to scientist's workstation through secure shell tunnel. The whole operation is kept totally transparent to the scientist and for the most part is controlled from a point-and-click GUI. The virtual globe also serves as a common platform for geospatial data, allowing smooth integration of the model simulation results with geographic data from other sources such as various web services or user-specific data in local files, if required. Also the system has the capability of building and updating a metadata catalog on the high performance storage that presents a simplified summary of the stored variables, hiding the low-level details such as physical location, size or format of the files from the user. Since data are often contributed to the system from multiple sources, the metadata catalog provides the user with a bird's eye view of the recent status of the database. As a next step, we plan on parallelizing the metadata updating and query-driven data selection routines to reduce the query response time. At current stage, the system can be immediately useful in making climate model simulation results available to a greater number of researchers who need simple and intuitive visualization of the simulation data or want to perform some analysis on it. The system's utility can reach beyond this particular application since it is generic enough to be ported to other high performance systems and to enable easy access to other types of geographic data.

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.

An Open Catalog for Supernova Data

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

Guillochon, James; Parrent, Jerod; Kelley, Luke Zoltan

We present the Open Supernova Catalog , an online collection of observations and metadata for presently 36,000+ supernovae and related candidates. The catalog is freely available on the web (https://sne.space), with its main interface having been designed to be a user-friendly, rapidly searchable table accessible on desktop and mobile devices. In addition to the primary catalog table containing supernova metadata, an individual page is generated for each supernova, which displays its available metadata, light curves, and spectra spanning X-ray to radio frequencies. The data presented in the catalog is automatically rebuilt on a daily basis and is constructed by parsingmore » several dozen sources, including the data presented in the supernova literature and from secondary sources such as other web-based catalogs. Individual supernova data is stored in the hierarchical, human- and machine-readable JSON format, with the entirety of each supernova’s data being contained within a single JSON file bearing its name. The setup we present here, which is based on open-source software maintained via git repositories hosted on github, enables anyone to download the entirety of the supernova data set to their home computer in minutes, and to make contributions of their own data back to the catalog via git. As the supernova data set continues to grow, especially in the upcoming era of all-sky synoptic telescopes, which will increase the total number of events by orders of magnitude, we hope that the catalog we have designed will be a valuable tool for the community to analyze both historical and contemporary supernovae.« less

An Open Catalog for Supernova Data

NASA Astrophysics Data System (ADS)

Guillochon, James; Parrent, Jerod; Kelley, Luke Zoltan; Margutti, Raffaella

2017-01-01

We present the Open Supernova Catalog, an online collection of observations and metadata for presently 36,000+ supernovae and related candidates. The catalog is freely available on the web (https://sne.space), with its main interface having been designed to be a user-friendly, rapidly searchable table accessible on desktop and mobile devices. In addition to the primary catalog table containing supernova metadata, an individual page is generated for each supernova, which displays its available metadata, light curves, and spectra spanning X-ray to radio frequencies. The data presented in the catalog is automatically rebuilt on a daily basis and is constructed by parsing several dozen sources, including the data presented in the supernova literature and from secondary sources such as other web-based catalogs. Individual supernova data is stored in the hierarchical, human- and machine-readable JSON format, with the entirety of each supernova’s data being contained within a single JSON file bearing its name. The setup we present here, which is based on open-source software maintained via git repositories hosted on github, enables anyone to download the entirety of the supernova data set to their home computer in minutes, and to make contributions of their own data back to the catalog via git. As the supernova data set continues to grow, especially in the upcoming era of all-sky synoptic telescopes, which will increase the total number of events by orders of magnitude, we hope that the catalog we have designed will be a valuable tool for the community to analyze both historical and contemporary supernovae.

The Origin of the Name "Onion's Fusible Alloy"

ERIC Educational Resources Information Center

Jensen, William B.

2010-01-01

In response to a reader query, this article traces the history of fusible alloys, including Newton's metal, D'Arcet's metal, Rose's metal, Onion's fusible alloy, and Wood's metal. (Contains 1 table and 1 figure.)

The ATLAS Eventlndex: data flow and inclusion of other metadata

NASA Astrophysics Data System (ADS)

Barberis, D.; Cárdenas Zárate, S. E.; Favareto, A.; Fernandez Casani, A.; Gallas, E. J.; Garcia Montoro, C.; Gonzalez de la Hoz, S.; Hrivnac, J.; Malon, D.; Prokoshin, F.; Salt, J.; Sanchez, J.; Toebbicke, R.; Yuan, R.; ATLAS Collaboration

2016-10-01

The ATLAS EventIndex is the catalogue of the event-related metadata for the information collected from the ATLAS detector. The basic unit of this information is the event record, containing the event identification parameters, pointers to the files containing this event as well as trigger decision information. The main use case for the EventIndex is event picking, as well as data consistency checks for large production campaigns. The EventIndex employs the Hadoop platform for data storage and handling, as well as a messaging system for the collection of information. The information for the EventIndex is collected both at Tier-0, when the data are first produced, and from the Grid, when various types of derived data are produced. The EventIndex uses various types of auxiliary information from other ATLAS sources for data collection and processing: trigger tables from the condition metadata database (COMA), dataset information from the data catalogue AMI and the Rucio data management system and information on production jobs from the ATLAS production system. The ATLAS production system is also used for the collection of event information from the Grid jobs. EventIndex developments started in 2012 and in the middle of 2015 the system was commissioned and started collecting event metadata, as a part of ATLAS Distributed Computing operations.

A journey to Semantic Web query federation in the life sciences.

PubMed

Cheung, Kei-Hoi; Frost, H Robert; Marshall, M Scott; Prud'hommeaux, Eric; Samwald, Matthias; Zhao, Jun; Paschke, Adrian

2009-10-01

As interest in adopting the Semantic Web in the biomedical domain continues to grow, Semantic Web technology has been evolving and maturing. A variety of technological approaches including triplestore technologies, SPARQL endpoints, Linked Data, and Vocabulary of Interlinked Datasets have emerged in recent years. In addition to the data warehouse construction, these technological approaches can be used to support dynamic query federation. As a community effort, the BioRDF task force, within the Semantic Web for Health Care and Life Sciences Interest Group, is exploring how these emerging approaches can be utilized to execute distributed queries across different neuroscience data sources. We have created two health care and life science knowledge bases. We have explored a variety of Semantic Web approaches to describe, map, and dynamically query multiple datasets. We have demonstrated several federation approaches that integrate diverse types of information about neurons and receptors that play an important role in basic, clinical, and translational neuroscience research. Particularly, we have created a prototype receptor explorer which uses OWL mappings to provide an integrated list of receptors and executes individual queries against different SPARQL endpoints. We have also employed the AIDA Toolkit, which is directed at groups of knowledge workers who cooperatively search, annotate, interpret, and enrich large collections of heterogeneous documents from diverse locations. We have explored a tool called "FeDeRate", which enables a global SPARQL query to be decomposed into subqueries against the remote databases offering either SPARQL or SQL query interfaces. Finally, we have explored how to use the vocabulary of interlinked Datasets (voiD) to create metadata for describing datasets exposed as Linked Data URIs or SPARQL endpoints. We have demonstrated the use of a set of novel and state-of-the-art Semantic Web technologies in support of a neuroscience query federation scenario. We have identified both the strengths and weaknesses of these technologies. While Semantic Web offers a global data model including the use of Uniform Resource Identifiers (URI's), the proliferation of semantically-equivalent URI's hinders large scale data integration. Our work helps direct research and tool development, which will be of benefit to this community.

A journey to Semantic Web query federation in the life sciences

PubMed Central

Cheung, Kei-Hoi; Frost, H Robert; Marshall, M Scott; Prud'hommeaux, Eric; Samwald, Matthias; Zhao, Jun; Paschke, Adrian

2009-01-01

Background As interest in adopting the Semantic Web in the biomedical domain continues to grow, Semantic Web technology has been evolving and maturing. A variety of technological approaches including triplestore technologies, SPARQL endpoints, Linked Data, and Vocabulary of Interlinked Datasets have emerged in recent years. In addition to the data warehouse construction, these technological approaches can be used to support dynamic query federation. As a community effort, the BioRDF task force, within the Semantic Web for Health Care and Life Sciences Interest Group, is exploring how these emerging approaches can be utilized to execute distributed queries across different neuroscience data sources. Methods and results We have created two health care and life science knowledge bases. We have explored a variety of Semantic Web approaches to describe, map, and dynamically query multiple datasets. We have demonstrated several federation approaches that integrate diverse types of information about neurons and receptors that play an important role in basic, clinical, and translational neuroscience research. Particularly, we have created a prototype receptor explorer which uses OWL mappings to provide an integrated list of receptors and executes individual queries against different SPARQL endpoints. We have also employed the AIDA Toolkit, which is directed at groups of knowledge workers who cooperatively search, annotate, interpret, and enrich large collections of heterogeneous documents from diverse locations. We have explored a tool called "FeDeRate", which enables a global SPARQL query to be decomposed into subqueries against the remote databases offering either SPARQL or SQL query interfaces. Finally, we have explored how to use the vocabulary of interlinked Datasets (voiD) to create metadata for describing datasets exposed as Linked Data URIs or SPARQL endpoints. Conclusion We have demonstrated the use of a set of novel and state-of-the-art Semantic Web technologies in support of a neuroscience query federation scenario. We have identified both the strengths and weaknesses of these technologies. While Semantic Web offers a global data model including the use of Uniform Resource Identifiers (URI's), the proliferation of semantically-equivalent URI's hinders large scale data integration. Our work helps direct research and tool development, which will be of benefit to this community. PMID:19796394

[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.

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

Heuristics for Relevancy Ranking of Earth Dataset Search Results

NASA Astrophysics Data System (ADS)

Lynnes, C.; Quinn, P.; Norton, J.

2016-12-01

As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.

Heuristics for Relevancy Ranking of Earth Dataset Search Results

NASA Technical Reports Server (NTRS)

Lynnes, Christopher; Quinn, Patrick; Norton, James

2016-01-01

As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.

Relevancy Ranking of Satellite Dataset Search Results

NASA Technical Reports Server (NTRS)

Lynnes, Christopher; Quinn, Patrick; Norton, James

2017-01-01

As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.

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

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

Blaiszik, B.; Chard, K.; Pruyne, J.

2016-07-06

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 cloudhosted 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)andmore » automatically-extractedmetadata in a registrywhile 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. TheMDF 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 thirdparty 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.« less

Chandra Source Catalog: User Interfaces

NASA Astrophysics Data System (ADS)

Bonaventura, Nina; Evans, I. N.; Harbo, P. N.; Rots, A. H.; Tibbetts, M. S.; Van Stone, D. W.; Zografou, P.; Anderson, C. S.; Chen, J. C.; Davis, J. E.; Doe, S. M.; Evans, J. D.; Fabbiano, G.; Galle, E.; Gibbs, D. G.; Glotfelty, K. J.; Grier, J. D.; Hain, R.; Hall, D. M.; He, X.; Houck, J. C.; Karovska, M.; Lauer, J.; McCollough, M. L.; McDowell, J. C.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Nichols, J. S.; Nowak, M. A.; Plummer, D. A.; Primini, F. A.; Refsdal, B. L.; Siemiginowska, A. L.; Sundheim, B. A.; Winkelman, S. L.

2010-03-01

The CSCview data mining interface is available for browsing the Chandra Source Catalog (CSC) and downloading tables of quality-assured source properties and data products. Once the desired source properties and search criteria are entered into the CSCview query form, the resulting source matches are returned in a table along with the values of the requested source properties for each source. (The catalog can be searched on any source property, not just position.) At this point, the table of search results may be saved to a text file, and the available data products for each source may be downloaded. CSCview save files are output in RDB-like and VOTable format. The available CSC data products include event files, spectra, lightcurves, and images, all of which are processed with the CIAO software. CSC data may also be accessed non-interactively with Unix command-line tools such as cURL and Wget, using ADQL 2.0 query syntax. In fact, CSCview features a separate ADQL query form for those who wish to specify this type of query within the GUI. Several interfaces are available for learning if a source is included in the catalog (in addition to CSCview): 1) the CSC interface to Sky in Google Earth shows the footprint of each Chandra observation on the sky, along with the CSC footprint for comparison (CSC source properties are also accessible when a source within a Chandra field-of-view is clicked); 2) the CSC Limiting Sensitivity online tool indicates if a source at an input celestial location was too faint for detection; 3) an IVOA Simple Cone Search interface locates all CSC sources within a specified radius of an R.A. and Dec.; and 4) the CSC-SDSS cross-match service returns the list of sources common to the CSC and SDSS, either all such sources or a subset based on search criteria.

Environmental Dataset Gateway (EDG) Search Widget

EPA Pesticide Factsheets

Use the Environmental Dataset Gateway (EDG) to find and access EPA's environmental resources. Many options are available for easily reusing EDG content in other other applications. This allows individuals to provide direct access to EPA's metadata outside the EDG interface. The EDG Search Widget makes it possible to search the EDG from another web page or application. The search widget can be included on your website by simply inserting one or two lines of code. Users can type a search term or lucene search query in the search field and retrieve a pop-up list of records that match that search.

Metadata for selecting or submitting generic seismic vulnerability functions via GEM's vulnerability database

USGS Publications Warehouse

Jaiswal, Kishor

2013-01-01

This memo lays out a procedure for the GEM software to offer an available vulnerability function for any acceptable set of attributes that the user specifies for a particular building category. The memo also provides general guidelines on how to submit the vulnerability or fragility functions to the GEM vulnerability repository, stipulating which attributes modelers must provide so that their vulnerability or fragility functions can be queried appropriately by the vulnerability database. An important objective is to provide users guidance on limitations and applicability by providing the associated modeling assumptions and applicability of each vulnerability or fragility function.

HTML5 PivotViewer: high-throughput visualization and querying of image data on the web.

PubMed

Taylor, Stephen; Noble, Roger

2014-09-15

Visualization and analysis of large numbers of biological images has generated a bottle neck in research. We present HTML5 PivotViewer, a novel, open source, platform-independent viewer making use of the latest web technologies that allows seamless access to images and associated metadata for each image. This provides a powerful method to allow end users to mine their data. Documentation, examples and links to the software are available from http://www.cbrg.ox.ac.uk/data/pivotviewer/. The software is licensed under GPLv2. © The Author 2014. Published by Oxford University Press.

Activity recognition using Video Event Segmentation with Text (VEST)

NASA Astrophysics Data System (ADS)

Holloway, Hillary; Jones, Eric K.; Kaluzniacki, Andrew; Blasch, Erik; Tierno, Jorge

2014-06-01

Multi-Intelligence (multi-INT) data includes video, text, and signals that require analysis by operators. Analysis methods include information fusion approaches such as filtering, correlation, and association. In this paper, we discuss the Video Event Segmentation with Text (VEST) method, which provides event boundaries of an activity to compile related message and video clips for future interest. VEST infers meaningful activities by clustering multiple streams of time-sequenced multi-INT intelligence data and derived fusion products. We discuss exemplar results that segment raw full-motion video (FMV) data by using extracted commentary message timestamps, FMV metadata, and user-defined queries.

Software Engineering Laboratory (SEL) database organization and user's guide, revision 2

NASA Technical Reports Server (NTRS)

Morusiewicz, Linda; Bristow, John

1992-01-01

The organization of the Software Engineering Laboratory (SEL) database is presented. Included are definitions and detailed descriptions of the database tables and views, the SEL data, and system support data. The mapping from the SEL and system support data to the base table is described. In addition, techniques for accessing the database through the Database Access Manager for the SEL (DAMSEL) system and via the ORACLE structured query language (SQL) are discussed.

Software Engineering Laboratory (SEL) database organization and user's guide

NASA Technical Reports Server (NTRS)

So, Maria; Heller, Gerard; Steinberg, Sandra; Spiegel, Douglas

1989-01-01

The organization of the Software Engineering Laboratory (SEL) database is presented. Included are definitions and detailed descriptions of the database tables and views, the SEL data, and system support data. The mapping from the SEL and system support data to the base tables is described. In addition, techniques for accessing the database, through the Database Access Manager for the SEL (DAMSEL) system and via the ORACLE structured query language (SQL), are discussed.

WebBee: A Platform for Secure Coordination and Communication in Crisis Scenarios

DTIC Science & Technology

2008-04-16

implemented through database triggers. The Webbee Database Server contains an Information Server, which is a Postgres database with PostGIS [5] extension...sends it to the target user. The heavy lifting for this mechanism is done through an extension of Postgres triggers (Figures 6.1 and 6.2), resulting...in fewer queries and better performance. Trigger support in Postgres is table-based and comparatively primitive: with n table triggers, an update

Composing Data Parallel Code for a SPARQL Graph Engine

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

Castellana, Vito G.; Tumeo, Antonino; Villa, Oreste

Big data analytics process large amount of data to extract knowledge from them. Semantic databases are big data applications that adopt the Resource Description Framework (RDF) to structure metadata through a graph-based representation. The graph based representation provides several benefits, such as the possibility to perform in memory processing with large amounts of parallelism. SPARQL is a language used to perform queries on RDF-structured data through graph matching. In this paper we present a tool that automatically translates SPARQL queries to parallel graph crawling and graph matching operations. The tool also supports complex SPARQL constructs, which requires more than basicmore » graph matching for their implementation. The tool generates parallel code annotated with OpenMP pragmas for x86 Shared-memory Multiprocessors (SMPs). With respect to commercial database systems such as Virtuoso, our approach reduces memory occupation due to join operations and provides higher performance. We show the scaling of the automatically generated graph-matching code on a 48-core SMP.« less

"Science SQL" as a Building Block for Flexible, Standards-based Data Infrastructures

NASA Astrophysics Data System (ADS)

Baumann, Peter

2016-04-01

We have learnt to live with the pain of separating data and metadata into non-interoperable silos. For metadata, we enjoy the flexibility of databases, be they relational, graph, or some other NoSQL. Contrasting this, users still "drown in files" as an unstructured, low-level archiving paradigm. It is time to bridge this chasm which once was technologically induced, but today can be overcome. One building block towards a common re-integrated information space is to support massive multi-dimensional spatio-temporal arrays. These "datacubes" appear as sensor, image, simulation, and statistics data in all science and engineering domains, and beyond. For example, 2-D satellilte imagery, 2-D x/y/t image timeseries and x/y/z geophysical voxel data, and 4-D x/y/z/t climate data contribute to today's data deluge in the Earth sciences. Virtual observatories in the Space sciences routinely generate Petabytes of such data. Life sciences deal with microarray data, confocal microscopy, human brain data, which all fall into the same category. The ISO SQL/MDA (Multi-Dimensional Arrays) candidate standard is extending SQL with modelling and query support for n-D arrays ("datacubes") in a flexible, domain-neutral way. This heralds a new generation of services with new quality parameters, such as flexibility, ease of access, embedding into well-known user tools, and scalability mechanisms that remain completely transparent to users. Technology like the EU rasdaman ("raster data manager") Array Database system can support all of the above examples simultaneously, with one technology. This is practically proven: As of today, rasdaman is in operational use on hundreds of Terabytes of satellite image timeseries datacubes, with transparent query distribution across more than 1,000 nodes. Therefore, Array Databases offering SQL/MDA constitute a natural common building block for next-generation data infrastructures. Being initiator and editor of the standard we present principles, implementation facets, and application examples as a basis for further discussion. Further, we highlight recent implementation progress in parallelization, data distribution, and query optimization showing their effects on real-life use cases.

A study of the influence of task familiarity on user behaviors and performance with a MeSH term suggestion interface for PubMed bibliographic search.

PubMed

Tang, Muh-Chyun; Liu, Ying-Hsang; Wu, Wan-Ching

2013-09-01

Previous research has shown that information seekers in biomedical domain need more support in formulating their queries. A user study was conducted to evaluate the effectiveness of a metadata based query suggestion interface for PubMed bibliographic search. The study also investigated the impact of search task familiarity on search behaviors and the effectiveness of the interface. A real user, user search request and real system approach was used for the study. Unlike tradition IR evaluation, where assigned tasks were used, the participants were asked to search requests of their own. Forty-four researchers in Health Sciences participated in the evaluation - each conducted two research requests of their own, alternately with the proposed interface and the PubMed baseline. Several performance criteria were measured to assess the potential benefits of the experimental interface, including users' assessment of their original and eventual queries, the perceived usefulness of the interfaces, satisfaction with the search results, and the average relevance score of the saved records. The results show that, when searching for an unfamiliar topic, users were more likely to change their queries, indicating the effect of familiarity on search behaviors. The results also show that the interface scored higher on several of the performance criteria, such as the "goodness" of the queries, perceived usefulness, and user satisfaction. Furthermore, in line with our hypothesis, the proposed interface was relatively more effective when less familiar search requests were attempted. Results indicate that there is a selective compatibility between search familiarity and search interface. One implication of the research for system evaluation is the importance of taking into consideration task familiarity when assessing the effectiveness of interactive IR systems. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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.

A data model and database for high-resolution pathology analytical image informatics.

PubMed

Wang, Fusheng; Kong, Jun; Cooper, Lee; Pan, Tony; Kurc, Tahsin; Chen, Wenjin; Sharma, Ashish; Niedermayr, Cristobal; Oh, Tae W; Brat, Daniel; Farris, Alton B; Foran, David J; Saltz, Joel

2011-01-01

The systematic analysis of imaged pathology specimens often results in a vast amount of morphological information at both the cellular and sub-cellular scales. While microscopy scanners and computerized analysis are capable of capturing and analyzing data rapidly, microscopy image data remain underutilized in research and clinical settings. One major obstacle which tends to reduce wider adoption of these new technologies throughout the clinical and scientific communities is the challenge of managing, querying, and integrating the vast amounts of data resulting from the analysis of large digital pathology datasets. This paper presents a data model, which addresses these challenges, and demonstrates its implementation in a relational database system. This paper describes a data model, referred to as Pathology Analytic Imaging Standards (PAIS), and a database implementation, which are designed to support the data management and query requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines on whole-slide images and tissue microarrays (TMAs). (1) Development of a data model capable of efficiently representing and storing virtual slide related image, annotation, markup, and feature information. (2) Development of a database, based on the data model, capable of supporting queries for data retrieval based on analysis and image metadata, queries for comparison of results from different analyses, and spatial queries on segmented regions, features, and classified objects. The work described in this paper is motivated by the challenges associated with characterization of micro-scale features for comparative and correlative analyses involving whole-slides tissue images and TMAs. Technologies for digitizing tissues have advanced significantly in the past decade. Slide scanners are capable of producing high-magnification, high-resolution images from whole slides and TMAs within several minutes. Hence, it is becoming increasingly feasible for basic, clinical, and translational research studies to produce thousands of whole-slide images. Systematic analysis of these large datasets requires efficient data management support for representing and indexing results from hundreds of interrelated analyses generating very large volumes of quantifications such as shape and texture and of classifications of the quantified features. We have designed a data model and a database to address the data management requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines. The data model represents virtual slide related image, annotation, markup and feature information. The database supports a wide range of metadata and spatial queries on images, annotations, markups, and features. We currently have three databases running on a Dell PowerEdge T410 server with CentOS 5.5 Linux operating system. The database server is IBM DB2 Enterprise Edition 9.7.2. The set of databases consists of 1) a TMA database containing image analysis results from 4740 cases of breast cancer, with 641 MB storage size; 2) an algorithm validation database, which stores markups and annotations from two segmentation algorithms and two parameter sets on 18 selected slides, with 66 GB storage size; and 3) an in silico brain tumor study database comprising results from 307 TCGA slides, with 365 GB storage size. The latter two databases also contain human-generated annotations and markups for regions and nuclei. Modeling and managing pathology image analysis results in a database provide immediate benefits on the value and usability of data in a research study. The database provides powerful query capabilities, which are otherwise difficult or cumbersome to support by other approaches such as programming languages. Standardized, semantic annotated data representation and interfaces also make it possible to more efficiently share image data and analysis results.

The I4 Online Query Tool for Earth Observations Data

NASA Technical Reports Server (NTRS)

Stefanov, William L.; Vanderbloemen, Lisa A.; Lawrence, Samuel J.

2015-01-01

The NASA Earth Observation System Data and Information System (EOSDIS) delivers an average of 22 terabytes per day of data collected by orbital and airborne sensor systems to end users through an integrated online search environment (the Reverb/ECHO system). Earth observations data collected by sensors on the International Space Station (ISS) are not currently included in the EOSDIS system, and are only accessible through various individual online locations. This increases the effort required by end users to query multiple datasets, and limits the opportunity for data discovery and innovations in analysis. The Earth Science and Remote Sensing Unit of the Exploration Integration and Science Directorate at NASA Johnson Space Center has collaborated with the School of Earth and Space Exploration at Arizona State University (ASU) to develop the ISS Instrument Integration Implementation (I4) data query tool to provide end users a clean, simple online interface for querying both current and historical ISS Earth Observations data. The I4 interface is based on the Lunaserv and Lunaserv Global Explorer (LGE) open-source software packages developed at ASU for query of lunar datasets. In order to avoid mirroring existing databases - and the need to continually sync/update those mirrors - our design philosophy is for the I4 tool to be a pure query engine only. Once an end user identifies a specific scene or scenes of interest, I4 transparently takes the user to the appropriate online location to download the data. The tool consists of two public-facing web interfaces. The Map Tool provides a graphic geobrowser environment where the end user can navigate to an area of interest and select single or multiple datasets to query. The Map Tool displays active image footprints for the selected datasets (Figure 1). Selecting a footprint will open a pop-up window that includes a browse image and a link to available image metadata, along with a link to the online location to order or download the actual data. Search results are either delivered in the form of browse images linked to the appropriate online database, similar to the Map Tool, or they may be transferred within the I4 environment for display as footprints in the Map Tool. Datasets searchable through I4 (http://eol.jsc.nasa.gov/I4_tool) currently include: Crew Earth Observations (CEO) cataloged and uncataloged handheld astronaut photography; Sally Ride EarthKAM; Hyperspectral Imager for the Coastal Ocean (HICO); and the ISS SERVIR Environmental Research and Visualization System (ISERV). The ISS is a unique platform in that it will have multiple users over its lifetime, and that no single remote sensing system has a permanent internal or external berth. The open source I4 tool is designed to enable straightforward addition of new datasets as they become available such as ISS-RapidSCAT, Cloud Aerosol Transport System (CATS), and the High Definition Earth Viewing (HDEV) system. Data from other sensor systems, such as those operated by the ISS International Partners or under the auspices of the US National Laboratory program, can also be added to I4 provided sufficient access to enable searching of data or metadata is available. Commercial providers of remotely sensed data from the ISS may be particularly interested in I4 as an additional means of directing potential customers and clients to their products.

A SOA broker solution for standard discovery and access services: the GI-cat framework

NASA Astrophysics Data System (ADS)

Boldrini, Enrico

2010-05-01

GI-cat ideal users are data providers or service providers within the geoscience community. The former have their data already available through an access service (e.g. an OGC Web Service) and would have it published through a standard catalog service, in a seamless way. The latter would develop a catalog broker and let users query and access different geospatial resources through one or more standard interfaces and Application Profiles (AP) (e.g. OGC CSW ISO AP, CSW ebRIM/EO AP, etc.). GI-cat actually implements a broker components (i.e. a middleware service) which carries out distribution and mediation functionalities among "well-adopted" catalog interfaces and data access protocols. GI-cat also publishes different discovery interfaces: the OGC CSW ISO and ebRIM Application Profiles (the latter coming with support for the EO and CIM extension packages) and two different OpenSearch interfaces developed in order to explore Web 2.0 possibilities. An extended interface is also available to exploit all available GI-cat features, such as interruptible incremental queries and queries feedback. Interoperability tests performed in the context of different projects have also pointed out the importance to enforce compatibility with existing and wide-spread tools of the open source community (e.g. GeoNetwork and Deegree catalogs), which was then achieved. Based on a service-oriented framework of modular components, GI-cat can effectively be customized and tailored to support different deployment scenarios. In addition to the distribution functionality an harvesting approach has been lately experimented, allowing the user to switch between a distributed and a local search giving thus more possibilities to support different deployment scenarios. A configurator tool is available in order to enable an effective high level configuration of the broker service. A specific geobrowser was also naturally developed, for demonstrating the advanced GI-cat functionalities. This client, called GI-go, is an example of the possible applications which may be built on top of the GI-cat broker component. GI-go allows discovering and browsing of the available datasets, retrieving and evaluating their description and performing distributed queries according to any combination of the following criteria: geographic area, temporal interval, topic of interest (free-text and/or keyword selection are allowed) and data source (i.e. where, when, what, who). The results set of a query (e.g. datasets metadata) are then displayed in an incremental way leveraging the asynchronous interactions approach implemented by GI-cat. This feature allows the user to access the intermediate query results. Query interruption and feedback features are also provided to the user. Alternatively, user may perform a browsing task by selecting a catalog resource from the current configuration and navigate through its aggregated and/or leaf datasets. In both cases datasets metadata, expressed according to ISO 19139 (and also Dublin Core and ebRIM if available), are displayed for download, along with a resource portrayal and actual data access (when this is meaningful and possible). The GI-cat distributed catalog service has been successfully deployed and experimented in the framework of different projects and initiative, including the SeaDataNet FP6 project, GEOSS IP3 (Interoperability Process Pilot Project), GEOSS AIP-2 (Architectural Implementation Project - Phase 2), FP7 GENESI-DR, CNR GIIDA, FP7 EUROGEOSS and ESA HMA project.

Explorative visual analytics on interval-based genomic data and their metadata.

PubMed

Jalili, Vahid; Matteucci, Matteo; Masseroli, Marco; Ceri, Stefano

2017-12-04

With the wide-spreading of public repositories of NGS processed data, the availability of user-friendly and effective tools for data exploration, analysis and visualization is becoming very relevant. These tools enable interactive analytics, an exploratory approach for the seamless "sense-making" of data through on-the-fly integration of analysis and visualization phases, suggested not only for evaluating processing results, but also for designing and adapting NGS data analysis pipelines. This paper presents abstractions for supporting the early analysis of NGS processed data and their implementation in an associated tool, named GenoMetric Space Explorer (GeMSE). This tool serves the needs of the GenoMetric Query Language, an innovative cloud-based system for computing complex queries over heterogeneous processed data. It can also be used starting from any text files in standard BED, BroadPeak, NarrowPeak, GTF, or general tab-delimited format, containing numerical features of genomic regions; metadata can be provided as text files in tab-delimited attribute-value format. GeMSE allows interactive analytics, consisting of on-the-fly cycling among steps of data exploration, analysis and visualization that help biologists and bioinformaticians in making sense of heterogeneous genomic datasets. By means of an explorative interaction support, users can trace past activities and quickly recover their results, seamlessly going backward and forward in the analysis steps and comparative visualizations of heatmaps. GeMSE effective application and practical usefulness is demonstrated through significant use cases of biological interest. GeMSE is available at http://www.bioinformatics.deib.polimi.it/GeMSE/ , and its source code is available at https://github.com/Genometric/GeMSE under GPLv3 open-source license.

The IRIS Federator: Accessing Seismological Data Across Data Centers

NASA Astrophysics Data System (ADS)

Trabant, C. M.; Van Fossen, M.; Ahern, T. K.; Weekly, R. T.

2015-12-01

In 2013 the International Federation of Digital Seismograph Networks (FDSN) approved a specification for web service interfaces for accessing seismological station metadata, time series and event parameters. Since then, a number of seismological data centers have implemented FDSN service interfaces, with more implementations in development. We have developed a new system called the IRIS Federator which leverages this standardization and provides the scientific community with a service for easy discovery and access of seismological data across FDSN data centers. These centers are located throughout the world and this work represents one model of a system for data collection across geographic and political boundaries.The main components of the IRIS Federator are a catalog of time series metadata holdings at each data center and a web service interface for searching the catalog. The service interface is designed to support client­-side federated data access, a model in which the client (software run by the user) queries the catalog and then collects the data from each identified center. By default the results are returned in a format suitable for direct submission to those web services, but could also be formatted in a simple text format for general data discovery purposes. The interface will remove any duplication of time series channels between data centers according to a set of business rules by default, however a user may request results with all duplicate time series entries included. We will demonstrate how client­-side federation is being incorporated into some of the DMC's data access tools. We anticipate further enhancement of the IRIS Federator to improve data discovery in various scenarios and to improve usefulness to communities beyond seismology.Data centers with FDSN web services: http://www.fdsn.org/webservices/The IRIS Federator query interface: http://service.iris.edu/irisws/fedcatalog/1/

Hierarchical video surveillance architecture: a chassis for video big data analytics and exploration

NASA Astrophysics Data System (ADS)

Ajiboye, Sola O.; Birch, Philip; Chatwin, Christopher; Young, Rupert

2015-03-01

There is increasing reliance on video surveillance systems for systematic derivation, analysis and interpretation of the data needed for predicting, planning, evaluating and implementing public safety. This is evident from the massive number of surveillance cameras deployed across public locations. For example, in July 2013, the British Security Industry Association (BSIA) reported that over 4 million CCTV cameras had been installed in Britain alone. The BSIA also reveal that only 1.5% of these are state owned. In this paper, we propose a framework that allows access to data from privately owned cameras, with the aim of increasing the efficiency and accuracy of public safety planning, security activities, and decision support systems that are based on video integrated surveillance systems. The accuracy of results obtained from government-owned public safety infrastructure would improve greatly if privately owned surveillance systems `expose' relevant video-generated metadata events, such as triggered alerts and also permit query of a metadata repository. Subsequently, a police officer, for example, with an appropriate level of system permission can query unified video systems across a large geographical area such as a city or a country to predict the location of an interesting entity, such as a pedestrian or a vehicle. This becomes possible with our proposed novel hierarchical architecture, the Fused Video Surveillance Architecture (FVSA). At the high level, FVSA comprises of a hardware framework that is supported by a multi-layer abstraction software interface. It presents video surveillance systems as an adapted computational grid of intelligent services, which is integration-enabled to communicate with other compatible systems in the Internet of Things (IoT).

A Query Language for Handling Big Observation Data Sets in the Sensor Web

NASA Astrophysics Data System (ADS)

Autermann, Christian; Stasch, Christoph; Jirka, Simon; Koppe, Roland

2017-04-01

The Sensor Web provides a framework for the standardized Web-based sharing of environmental observations and sensor metadata. While the issue of varying data formats and protocols is addressed by these standards, the fast growing size of observational data is imposing new challenges for the application of these standards. Most solutions for handling big observational datasets currently focus on remote sensing applications, while big in-situ datasets relying on vector features still lack a solid approach. Conventional Sensor Web technologies may not be adequate, as the sheer size of the data transmitted and the amount of metadata accumulated may render traditional OGC Sensor Observation Services (SOS) unusable. Besides novel approaches to store and process observation data in place, e.g. by harnessing big data technologies from mainstream IT, the access layer has to be amended to utilize and integrate these large observational data archives into applications and to enable analysis. For this, an extension to the SOS will be discussed that establishes a query language to dynamically process and filter observations at storage level, similar to the OGC Web Coverage Service (WCS) and it's Web Coverage Processing Service (WCPS) extension. This will enable applications to request e.g. spatial or temporal aggregated data sets in a resolution it is able to display or it requires. The approach will be developed and implemented in cooperation with the The Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research whose catalogue of data compromises marine observations of physical, chemical and biological phenomena from a wide variety of sensors, including mobile (like research vessels, aircrafts or underwater vehicles) and stationary (like buoys or research stations). Observations are made with a high temporal resolution and the resulting time series may span multiple decades.

Space environment data storage and access: lessons learned and recommendations for the future

NASA Astrophysics Data System (ADS)

Evans, Hugh; Heynderickx, Daniel

2012-07-01

With the ever increasing volume of space environment data available at present and planned for the near future, the demands on data storage and access methods are increasing as well. In addition, continued access to historical, archived data remains crucial. On the basis of many years of experience, the authors identify the following issues as important for continued and efficient handling of datasets now and in the future: The huge data volumes currently or very soon avaiable from a number of space missions will limi direct Internet download access to even relatively short epoch ranges of data. Therefore, data providers should establish or extend standardised data (post-) processing services so that only data query results should be downloaded. Although a single standardised data format will in all likelihood remain utopia, data providers should at least include extensive metadata with their data products, according to established standards and practices (e.g. ISTP, SPASE). Standardisation of (sets of) metadata greatly facilitates data mining and querying. The use of SQL database storage should be considered instead of, or in parallel with, classic storage of data files. The use of SQL does away with having to handle file parsing and processing, while at the same time standard access protocols can be used to (remotely) connect to such data repositories. Many data holdings are still lacking in extensive descriptions of data provenance (e.g. instrument description), content and format. Unfortunately, detailed data information is usually rejected by scientific and technical journals. Re-processing of historical archived datasets into modern formats, making them easily available and usable, is urgently required, as knowledge is being lost. A global data directory has still not been achieved; policy makers should enforce stricter rules for "broadcasting" dataset information.

Computer systems and methods for the query and visualization of multidimensional databases

DOEpatents

Stolte, Chris; Tang, Diane L.; Hanrahan, Patrick

2006-08-08

A method and system for producing graphics. A hierarchical structure of a database is determined. A visual table, comprising a plurality of panes, is constructed by providing a specification that is in a language based on the hierarchical structure of the database. In some cases, this language can include fields that are in the database schema. The database is queried to retrieve a set of tuples in accordance with the specification. A subset of the set of tuples is associated with a pane in the plurality of panes.

Computer systems and methods for the query and visualization of multidimensional database

DOEpatents

Stolte, Chris; Tang, Diane L.; Hanrahan, Patrick

2010-05-11

A method and system for producing graphics. A hierarchical structure of a database is determined. A visual table, comprising a plurality of panes, is constructed by providing a specification that is in a language based on the hierarchical structure of the database. In some cases, this language can include fields that are in the database schema. The database is queried to retrieve a set of tuples in accordance with the specification. A subset of the set of tuples is associated with a pane in the plurality of panes.

Minimal Information for Neural Electromagnetic Ontologies (MINEMO): A standards-compliant method for analysis and integration of event-related potentials (ERP) data

PubMed Central

Frishkoff, Gwen; Sydes, Jason; Mueller, Kurt; Frank, Robert; Curran, Tim; Connolly, John; Kilborn, Kerry; Molfese, Dennis; Perfetti, Charles; Malony, Allen

2011-01-01

We present MINEMO (Minimal Information for Neural ElectroMagnetic Ontologies), a checklist for the description of event-related potentials (ERP) studies. MINEMO extends MINI (Minimal Information for Neuroscience Investigations)to the ERP domain. Checklist terms are explicated in NEMO, a formal ontology that is designed to support ERP data sharing and integration. MINEMO is also linked to an ERP database and web application (the NEMO portal). Users upload their data and enter MINEMO information through the portal. The database then stores these entries in RDF (Resource Description Framework), along with summary metrics, i.e., spatial and temporal metadata. Together these spatial, temporal, and functional metadata provide a complete description of ERP data and the context in which these data were acquired. The RDF files then serve as inputs to ontology-based labeling and meta-analysis. Our ultimate goal is to represent ERPs using a rich semantic structure, so results can be queried at multiple levels, to stimulate novel hypotheses and to promote a high-level, integrative account of ERP results across diverse study methods and paradigms. PMID:22180824

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.

Information System through ANIS at CeSAM

NASA Astrophysics Data System (ADS)

Moreau, C.; Agneray, F.; Gimenez, S.

2015-09-01

ANIS (AstroNomical Information System) is a web generic tool developed at CeSAM to facilitate and standardize the implementation of astronomical data of various kinds through private and/or public dedicated Information Systems. The architecture of ANIS is composed of a database server which contains the project data, a web user interface template which provides high level services (search, extract and display imaging and spectroscopic data using a combination of criteria, an object list, a sql query module or a cone search interfaces), a framework composed of several packages, and a metadata database managed by a web administration entity. The process to implement a new ANIS instance at CeSAM is easy and fast : the scientific project has to submit data or a data secure access, the CeSAM team installs the new instance (web interface template and the metadata database), and the project administrator can configure the instance with the web ANIS-administration entity. Currently, the CeSAM offers through ANIS a web access to VO compliant Information Systems for different projects (HeDaM, HST-COSMOS, CFHTLS-ZPhots, ExoDAT,...).

The new Planetary Science Archive: A tool for exploration and discovery of scientific datasets from ESA's planetary missions

NASA Astrophysics Data System (ADS)

Heather, David

2016-07-01

Introduction: The Planetary Science Archive (PSA) is the European Space Agency's (ESA) repository of science data from all planetary science and exploration missions. The PSA provides access to scientific datasets through various interfaces (e.g. FTP browser, Map based, Advanced search, and Machine interface): http://archives.esac.esa.int/psa All datasets are scientifically peer-reviewed by independent scientists, and are compliant with the Planetary Data System (PDS) standards. Updating the PSA: The PSA is currently implementing a number of significant changes, both to its web-based interface to the scientific community, and to its database structure. The new PSA will be up-to-date with versions 3 and 4 of the PDS standards, as PDS4 will be used for ESA's upcoming ExoMars and BepiColombo missions. The newly designed PSA homepage will provide direct access to scientific datasets via a text search for targets or missions. This will significantly reduce the complexity for users to find their data and will promote one-click access to the datasets. Additionally, the homepage will provide direct access to advanced views and searches of the datasets. Users will have direct access to documentation, information and tools that are relevant to the scientific use of the dataset, including ancillary datasets, Software Interface Specification (SIS) documents, and any tools/help that the PSA team can provide. A login mechanism will provide additional functionalities to the users to aid / ease their searches (e.g. saving queries, managing default views). Queries to the PSA database will be possible either via the homepage (for simple searches of missions or targets), or through a filter menu for more tailored queries. The filter menu will offer multiple options to search for a particular dataset or product, and will manage queries for both in-situ and remote sensing instruments. Parameters such as start-time, phase angle, and heliocentric distance will be emphasized. A further advanced search function will allow users to query all the metadata present in the PSA database. Results will be displayed in 3 different ways: 1) A table listing all the corresponding data matching the criteria in the filter menu, 2) a projection of the products onto the surface of the object when applicable (i.e. planets, small bodies), and 3) a list of images for the relevant instruments to enjoy the beauty of our Solar System. These different ways of viewing the datasets will ensure that scientists and non-professionals alike will have access to the specific data they are looking for, regardless of their background. Conclusions: The new PSA will maintain the various interfaces and services it had in the past, and will include significant improvements designed to allow easier and more effective access to the scientific data and supporting materials. The new PSA is expected to be released by mid-2016. It will support the past, present and future missions, ancillary datasets, and will enhance the scientific output of ESA's missions. As such, the PSA will become a unique archive ensuring the long-term preservation and usage of scientific datasets together with user-friendly access.

The new Planetary Science Archive: A tool for exploration and discovery of scientific datasets from ESA's planetary missions.

NASA Astrophysics Data System (ADS)

Heather, David; Besse, Sebastien; Barbarisi, Isa; Arviset, Christophe; de Marchi, Guido; Barthelemy, Maud; Docasal, Ruben; Fraga, Diego; Grotheer, Emmanuel; Lim, Tanya; Macfarlane, Alan; Martinez, Santa; Rios, Carlos

2016-04-01

Introduction: The Planetary Science Archive (PSA) is the European Space Agency's (ESA) repository of science data from all planetary science and exploration missions. The PSA provides access to scientific datasets through various interfaces (e.g. FTP browser, Map based, Advanced search, and Machine interface): http://archives.esac.esa.int/psa All datasets are scientifically peer-reviewed by independent scientists, and are compliant with the Planetary Data System (PDS) standards. Updating the PSA: The PSA is currently implementing a number of significant changes, both to its web-based interface to the scientific community, and to its database structure. The new PSA will be up-to-date with versions 3 and 4 of the PDS standards, as PDS4 will be used for ESA's upcoming ExoMars and BepiColombo missions. The newly designed PSA homepage will provide direct access to scientific datasets via a text search for targets or missions. This will significantly reduce the complexity for users to find their data and will promote one-click access to the datasets. Additionally, the homepage will provide direct access to advanced views and searches of the datasets. Users will have direct access to documentation, information and tools that are relevant to the scientific use of the dataset, including ancillary datasets, Software Interface Specification (SIS) documents, and any tools/help that the PSA team can provide. A login mechanism will provide additional functionalities to the users to aid / ease their searches (e.g. saving queries, managing default views). Queries to the PSA database will be possible either via the homepage (for simple searches of missions or targets), or through a filter menu for more tailored queries. The filter menu will offer multiple options to search for a particular dataset or product, and will manage queries for both in-situ and remote sensing instruments. Parameters such as start-time, phase angle, and heliocentric distance will be emphasized. A further advanced search function will allow users to query all the metadata present in the PSA database. Results will be displayed in 3 different ways: 1) A table listing all the corresponding data matching the criteria in the filter menu, 2) a projection of the products onto the surface of the object when applicable (i.e. planets, small bodies), and 3) a list of images for the relevant instruments to enjoy the beauty of our Solar System. These different ways of viewing the datasets will ensure that scientists and non-professionals alike will have access to the specific data they are looking for, regardless of their background. Conclusions: The new PSA will maintain the various interfaces and services it had in the past, and will include significant improvements designed to allow easier and more effective access to the scientific data and supporting materials. The new PSA is expected to be released by mid-2016. It will support the past, present and future missions, ancillary datasets, and will enhance the scientific output of ESA's missions. As such, the PSA will become a unique archive ensuring the long-term preservation and usage of scientific datasets together with user-friendly access.

SkyQuery - A Prototype Distributed Query and Cross-Matching Web Service for the Virtual Observatory

NASA Astrophysics Data System (ADS)

Thakar, A. R.; Budavari, T.; Malik, T.; Szalay, A. S.; Fekete, G.; Nieto-Santisteban, M.; Haridas, V.; Gray, J.

2002-12-01

We have developed a prototype distributed query and cross-matching service for the VO community, called SkyQuery, which is implemented with hierarchichal Web Services. SkyQuery enables astronomers to run combined queries on existing distributed heterogeneous astronomy archives. SkyQuery provides a simple, user-friendly interface to run distributed queries over the federation of registered astronomical archives in the VO. The SkyQuery client connects to the portal Web Service, which farms the query out to the individual archives, which are also Web Services called SkyNodes. The cross-matching algorithm is run recursively on each SkyNode. Each archive is a relational DBMS with a HTM index for fast spatial lookups. The results of the distributed query are returned as an XML DataSet that is automatically rendered by the client. SkyQuery also returns the image cutout corresponding to the query result. SkyQuery finds not only matches between the various catalogs, but also dropouts - objects that exist in some of the catalogs but not in others. This is often as important as finding matches. We demonstrate the utility of SkyQuery with a brown-dwarf search between SDSS and 2MASS, and a search for radio-quiet quasars in SDSS, 2MASS and FIRST. The importance of a service like SkyQuery for the worldwide astronomical community cannot be overstated: data on the same objects in various archives is mapped in different wavelength ranges and looks very different due to different errors, instrument sensitivities and other peculiarities of each archive. Our cross-matching algorithm preforms a fuzzy spatial join across multiple catalogs. This type of cross-matching is currently often done by eye, one object at a time. A static cross-identification table for a set of archives would become obsolete by the time it was built - the exponential growth of astronomical data means that a dynamic cross-identification mechanism like SkyQuery is the only viable option. SkyQuery was funded by a grant from the NASA AISR program.

Titanbrowse: a new paradigm for access, visualization and analysis of hyperspectral imaging

NASA Astrophysics Data System (ADS)

Penteado, Paulo F.

2016-10-01

Currently there are archives and tools to explore remote sensing imaging, but these lack some functionality needed for hyperspectral imagers: 1) Querying and serving only whole datacubes is not enough, since in each cube there is typically a large variation in observation geometry over the spatial pixels. Thus, often the most useful unit for selecting observations of interest is not a whole cube but rather a single spectrum. 2) Pixel-specific geometric data included in the standard pipelines is calculated at only one point per pixel. Particularly for selections of pixels from many different cubes, or observations near the limb, it is necessary to know the actual extent of each pixel. 3) Database queries need not only metadata, but also by the spectral data. For instance, one query might look for atypical values of some band, or atypical relations between bands, denoting spectral features (such as ratios or differences between bands). 4) There is the need to evaluate arbitrary, dynamically-defined, complex functions of the data (beyond just simple arithmetic operations), both for selection in the queries, and for visualization, to interactively tune the queries to the observations of interest. 5) Making the most useful query for some analysis often requires interactive visualization integrated with data selection and processing, because the user needs to explore how different functions of the data vary over the observations without having to download data and import it into visualization software. 6) Complementary to interactive use, an API allowing programmatic access to the system is needed for systematic data analyses. 7) Direct access to calibrated and georeferenced data, without the need to download data and software and learn to process it.We present titanbrowse, a database, exploration and visualization system for Cassini VIMS observations of Titan, designed to fullfill the aforementioned needs. While it originallly ran on data in the user's computer, we are now developing an online version, so that users do not need to download software and data. The server, which we maintain, processes the queries and communicates the results to the client the user runs. http://ppenteado.net/titanbrowse.

Interoperability Using Lightweight Metadata Standards: Service & Data Casting, OpenSearch, OPM Provenance, and Shared SciFlo Workflows

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E.

2011-12-01

Under several NASA grants, we are generating multi-sensor merged atmospheric datasets to enable the detection of instrument biases and studies of climate trends over decades of data. For example, under a NASA MEASURES grant we are producing a water vapor climatology from the A-Train instruments, stratified by the Cloudsat cloud classification for each geophysical scene. The generation and proper use of such multi-sensor climate data records (CDR's) requires a high level of openness, transparency, and traceability. To make the datasets self-documenting and provide access to full metadata and traceability, we have implemented a set of capabilities and services using known, interoperable protocols. These protocols include OpenSearch, OPeNDAP, Open Provenance Model, service & data casting technologies using Atom feeds, and REST-callable analysis workflows implemented as SciFlo (XML) documents. We advocate that our approach can serve as a blueprint for how to openly "document and serve" complex, multi-sensor CDR's with full traceability. The capabilities and services provided include: - Discovery of the collections by keyword search, exposed using OpenSearch protocol; - Space/time query across the CDR's granules and all of the input datasets via OpenSearch; - User-level configuration of the production workflows so that scientists can select additional physical variables from the A-Train to add to the next iteration of the merged datasets; - Efficient data merging using on-the-fly OPeNDAP variable slicing & spatial subsetting of data out of input netCDF and HDF files (without moving the entire files); - Self-documenting CDR's published in a highly usable netCDF4 format with groups used to organize the variables, CF-style attributes for each variable, numeric array compression, & links to OPM provenance; - Recording of processing provenance and data lineage into a query-able provenance trail in Open Provenance Model (OPM) format, auto-captured by the workflow engine; - Open Publishing of all of the workflows used to generate products as machine-callable REST web services, using the capabilities of the SciFlo workflow engine; - Advertising of the metadata (e.g. physical variables provided, space/time bounding box, etc.) for our prepared datasets as "datacasts" using the Atom feed format; - Publishing of all datasets via our "DataDrop" service, which exploits the WebDAV protocol to enable scientists to access remote data directories as local files on their laptops; - Rich "web browse" of the CDR's with full metadata and the provenance trail one click away; - Advertising of all services as Google-discoverable "service casts" using the Atom format. The presentation will describe our use of the interoperable protocols and demonstrate the capabilities and service GUI's.

Formal Provenance Representation of the Data and Information Supporting the National Climate Assessment

NASA Technical Reports Server (NTRS)

Tilmes, Curt

2014-01-01

The Global Change Information System (GCIS) provides a framework for the formal representation of structured metadata about data and information about global change. The pilot deployment of the system supports the National Climate Assessment (NCA), a major report of the U.S. Global Change Research Program (USGCRP). A consumer of that report can use the system to browse and explore that supporting information. Additionally, capturing that information into a structured data model and presenting it in standard formats through well defined open inter- faces, including query interfaces suitable for data mining and linking with other databases, the information becomes valuable for other analytic uses as well.

NCBI GEO: archive for functional genomics data sets--update.

PubMed

Barrett, Tanya; Wilhite, Stephen E; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Holko, Michelle; Yefanov, Andrey; Lee, Hyeseung; Zhang, Naigong; Robertson, Cynthia L; Serova, Nadezhda; Davis, Sean; Soboleva, Alexandra

2013-01-01

The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data.

The interoperability skill of the Geographic Portal of the ISPRA - Geological Survey of Italy

NASA Astrophysics Data System (ADS)

Pia Congi, Maria; Campo, Valentina; Cipolloni, Carlo; Delogu, Daniela; Ventura, Renato; Battaglini, Loredana

2010-05-01

The Geographic Portal of Geological Survey of Italy (ISPRA) available at http://serviziogeologico.apat.it/Portal was planning according to standard criteria of the INSPIRE directive. ArcIMS services and at the same time WMS and WFS services had been realized to satisfy the different clients. For each database and web-services the metadata had been wrote in agreement with the ISO 19115. The management architecture of the portal allow it to encode the clients input and output requests both in ArcXML and in GML language. The web-applications and web-services had been realized for each database owner of Land Protection and Georesources Department concerning the geological map at the scale 1:50.000 (CARG Project) and 1:100.000, the IFFI landslide inventory, the boreholes due Law 464/84, the large-scale geological map and all the raster format maps. The portal thus far published is at the experimental stage but through the development of a new graphical interface achieves the final version. The WMS and WFS services including metadata will be re-designed. The validity of the methodology and the applied standards allow to look ahead to the growing developments. In addition to this it must be borne in mind that the capacity of the new geological standard language (GeoSciML), which is already incorporated in the web-services deployed, will be allow a better display and query of the geological data according to the interoperability. The characteristics of the geological data demand for the cartographic mapping specific libraries of symbols not yet available in a WMS service. This is an other aspect regards the standards of the geological informations. Therefore at the moment were carried out: - a library of geological symbols to be used for printing, with a sketch of system colors and a library for displaying data on video, which almost completely solves the problems of the coverage point and area data (also directed) but that still introduces problems for the linear data (solutions: ArcIMS services from Arcmap projects or a specific SLD implementation for WMS services); - an update of "Guidelines for the supply of geological data" in a short time will be published; - the Geological Survey of Italy is officially involved in the IUGS-CGI working group for the processing and experimentation on the new GeoSciML language with the WMS/WFS services. The availability of geographic informations occurs through the metadata that can be distributed online so that search engines can find them through specialized research. The collected metadata in catalogs are structured in a standard (ISO 19135). The catalogs are a ‘common' interface to locate, view and query data and metadata services, web services and other resources. Then, while working in a growing sector of the environmental knowledgement the focus is to collect the participation of other subjects that contribute to the enrichment of the informative content available, so as to be able to arrive to a real portal of national interest especially in case of disaster management.

STILTS -- Starlink Tables Infrastructure Library Tool Set

NASA Astrophysics Data System (ADS)

Taylor, Mark

STILTS is a set of command-line tools for processing tabular data. It has been designed for, but is not restricted to, use on astronomical data such as source catalogues. It contains both generic (format-independent) table processing tools and tools for processing VOTable documents. Facilities offered include crossmatching, format conversion, format validation, column calculation and rearrangement, row selection, sorting, plotting, statistical calculations and metadata display. Calculations on cell data can be performed using a powerful and extensible expression language. The package is written in pure Java and based on STIL, the Starlink Tables Infrastructure Library. This gives it high portability, support for many data formats (including FITS, VOTable, text-based formats and SQL databases), extensibility and scalability. Where possible the tools are written to accept streamed data so the size of tables which can be processed is not limited by available memory. As well as the tutorial and reference information in this document, detailed on-line help is available from the tools themselves. STILTS is available under the GNU General Public Licence.

A federated semantic metadata registry framework for enabling interoperability across clinical research and care domains.

PubMed

Sinaci, A Anil; Laleci Erturkmen, Gokce B

2013-10-01

In order to enable secondary use of Electronic Health Records (EHRs) by bridging the interoperability gap between clinical care and research domains, in this paper, a unified methodology and the supporting framework is introduced which brings together the power of metadata registries (MDR) and semantic web technologies. We introduce a federated semantic metadata registry framework by extending the ISO/IEC 11179 standard, and enable integration of data element registries through Linked Open Data (LOD) principles where each Common Data Element (CDE) can be uniquely referenced, queried and processed to enable the syntactic and semantic interoperability. Each CDE and their components are maintained as LOD resources enabling semantic links with other CDEs, terminology systems and with implementation dependent content models; hence facilitating semantic search, much effective reuse and semantic interoperability across different application domains. There are several important efforts addressing the semantic interoperability in healthcare domain such as IHE DEX profile proposal, CDISC SHARE and CDISC2RDF. Our architecture complements these by providing a framework to interlink existing data element registries and repositories for multiplying their potential for semantic interoperability to a greater extent. Open source implementation of the federated semantic MDR framework presented in this paper is the core of the semantic interoperability layer of the SALUS project which enables the execution of the post marketing safety analysis studies on top of existing EHR systems. Copyright © 2013 Elsevier Inc. All rights reserved.

PMAG: Relational Database Definition

NASA Astrophysics Data System (ADS)

Keizer, P.; Koppers, A.; Tauxe, L.; Constable, C.; Genevey, A.; Staudigel, H.; Helly, J.

2002-12-01

The Scripps center for Physical and Chemical Earth References (PACER) was established to help create databases for reference data and make them available to the Earth science community. As part of these efforts PACER supports GERM, REM and PMAG and maintains multiple online databases under the http://earthref.org umbrella website. This website has been built on top of a relational database that allows for the archiving and electronic access to a great variety of data types and formats, permitting data queries using a wide range of metadata. These online databases are designed in Oracle 8.1.5 and they are maintained at the San Diego Supercomputer Center. They are directly available via http://earthref.org/databases/. A prototype of the PMAG relational database is now operational within the existing EarthRef.org framework under http://earthref.org/databases/PMAG/. As will be shown in our presentation, the PMAG design focuses around the general workflow that results in the determination of typical paleo-magnetic analyses. This ensures that individual data points can be traced between the actual analysis and the specimen, sample, site, locality and expedition it belongs to. These relations guarantee traceability of the data by distinguishing between original and derived data, where the actual (raw) measurements are performed on the specimen level, and data on the sample level and higher are then derived products in the database. These relations may also serve to recalculate site means when new data becomes available for that locality. The PMAG data records are extensively described in terms of metadata. These metadata are used when scientists search through this online database in order to view and download their needed data. They minimally include method descriptions for field sampling, laboratory techniques and statistical analyses. They also include selection criteria used during the interpretation of the data and, most importantly, critical information about the site location (latitude, longitude, elevation), geography (continent, country, region), geological setting (lithospheric plate or block, tectonic setting), geological age (age range, timescale name, stratigraphic position) and materials (rock type, classification, alteration state). Each data point and method description is also related to its peer-reviewed reference [citation ID] as archived in the EarthRef Reference Database (ERR). This guarantees direct traceability all the way to its original source, where the user can find the bibliography of each PMAG reference along with every abstract, data table, technical note and/or appendix that are available in digital form and that can be downloaded as PDF/JPEG images and Microsoft Excel/Word data files. This may help scientists and teachers in performing their research since they have easy access to all the scientific data. It also allows for checking potential errors during the digitization process. Please visit the PMAG website at http://earthref.org/PMAG/ for more information.

Menopause and big data: Word Adjacency Graph modeling of menopause-related ChaCha data.

PubMed

Carpenter, Janet S; Groves, Doyle; Chen, Chen X; Otte, Julie L; Miller, Wendy R

2017-07-01

To detect and visualize salient queries about menopause using Big Data from ChaCha. We used Word Adjacency Graph (WAG) modeling to detect clusters and visualize the range of menopause-related topics and their mutual proximity. The subset of relevant queries was fully modeled. We split each query into token words (ie, meaningful words and phrases) and removed stopwords (ie, not meaningful functional words). The remaining words were considered in sequence to build summary tables of words and two and three-word phrases. Phrases occurring at least 10 times were used to build a network graph model that was iteratively refined by observing and removing clusters of unrelated content. We identified two menopause-related subsets of queries by searching for questions containing menopause and menopause-related terms (eg, climacteric, hot flashes, night sweats, hormone replacement). The first contained 263,363 queries from individuals aged 13 and older and the second contained 5,892 queries from women aged 40 to 62 years. In the first set, we identified 12 topic clusters: 6 relevant to menopause and 6 less relevant. In the second set, we identified 15 topic clusters: 11 relevant to menopause and 4 less relevant. Queries about hormones were pervasive within both WAG models. Many of the queries reflected low literacy levels and/or feelings of embarrassment. We modeled menopause-related queries posed by ChaCha users between 2009 and 2012. ChaCha data may be used on its own or in combination with other Big Data sources to identify patient-driven educational needs and create patient-centered interventions.

biologically relevant effects of dipentyl phthalate

EPA Pesticide Factsheets

metadata sheet, data sheet for each table and figure in the published manuscriptThis dataset is associated with the following publication:Gray , E., J. Furr , K. Tatum-Gibbs, C. Lambright , H. Sampson, B. Hannas, V. Wilson , A. Hotchkiss , and P. Foster. Establishing the Biological Relevance of Dipentyl Phthalate Reductions in Fetal Rat Testosterone Production and Plasma and Testis Testosterone Levels. TOXICOLOGICAL SCIENCES. Society of Toxicology, 149(1): 178-91, (2016).

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.

NeuroTransDB: highly curated and structured transcriptomic metadata for neurodegenerative diseases

PubMed Central

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

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 PMID:26475471

Video Analytics for Indexing, Summarization and Searching of Video Archives

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

Trease, Harold E.; Trease, Lynn L.

This paper will be submitted to the proceedings The Eleventh IASTED International Conference on. Signal and Image Processing. Given a video or video archive how does one effectively and quickly summarize, classify, and search the information contained within the data? This paper addresses these issues by describing a process for the automated generation of a table-of-contents and keyword, topic-based index tables that can be used to catalogue, summarize, and search large amounts of video data. Having the ability to index and search the information contained within the videos, beyond just metadata tags, provides a mechanism to extract and identify "useful"more » content from image and video data.« less

The MMI Device Ontology: Enabling Sensor Integration

NASA Astrophysics Data System (ADS)

Rueda, C.; Galbraith, N.; Morris, R. A.; Bermudez, L. E.; Graybeal, J.; Arko, R. A.; Mmi Device Ontology Working Group

2010-12-01

The Marine Metadata Interoperability (MMI) project has developed an ontology for devices to describe sensors and sensor networks. This ontology is implemented in the W3C Web Ontology Language (OWL) and provides an extensible conceptual model and controlled vocabularies for describing heterogeneous instrument types, with different data characteristics, and their attributes. It can help users populate metadata records for sensors; associate devices with their platforms, deployments, measurement capabilities and restrictions; aid in discovery of sensor data, both historic and real-time; and improve the interoperability of observational oceanographic data sets. We developed the MMI Device Ontology following a community-based approach. By building on and integrating other models and ontologies from related disciplines, we sought to facilitate semantic interoperability while avoiding duplication. Key concepts and insights from various communities, including the Open Geospatial Consortium (eg., SensorML and Observations and Measurements specifications), Semantic Web for Earth and Environmental Terminology (SWEET), and W3C Semantic Sensor Network Incubator Group, have significantly enriched the development of the ontology. Individuals ranging from instrument designers, science data producers and consumers to ontology specialists and other technologists contributed to the work. Applications of the MMI Device Ontology are underway for several community use cases. These include vessel-mounted multibeam mapping sonars for the Rolling Deck to Repository (R2R) program and description of diverse instruments on deepwater Ocean Reference Stations for the OceanSITES program. These trials involve creation of records completely describing instruments, either by individual instances or by manufacturer and model. Individual terms in the MMI Device Ontology can be referenced with their corresponding Uniform Resource Identifiers (URIs) in sensor-related metadata specifications (e.g., SensorML, NetCDF). These identifiers can be resolved through a web browser, or other client applications via HTTP against the MMI Ontology Registry and Repository (ORR), where the ontology is maintained. SPARQL-based query capabilities, which are enhanced with reasoning, along with several supported output formats, allow the effective interaction of diverse client applications with the semantic information associated with the device ontology. In this presentation we describe the process for the development of the MMI Device Ontology and illustrate extensions and applications that demonstrate the benefits of adopting this semantic approach, including example queries involving inference. We also highlight the issues encountered and future work.

Relational similarity-based model of data part 1: foundations and query systems

NASA Astrophysics Data System (ADS)

Belohlavek, Radim; Vychodil, Vilem

2017-10-01

We present a general rank-aware model of data which supports handling of similarity in relational databases. The model is based on the assumption that in many cases it is desirable to replace equalities on values in data tables by similarity relations expressing degrees to which the values are similar. In this context, we study various phenomena which emerge in the model, including similarity-based queries and similarity-based data dependencies. Central notion in our model is that of a ranked data table over domains with similarities which is our counterpart to the notion of relation on relation scheme from the classical relational model. Compared to other approaches which cover related problems, we do not propose a similarity-based or ranking module on top of the classical relational model. Instead, we generalize the very core of the model by replacing the classical, two-valued logic upon which the classical model is built by a more general logic involving a scale of truth degrees that, in addition to the classical truth degrees 0 and 1, contains intermediate truth degrees. While the classical truth degrees 0 and 1 represent nonequality and equality of values, and subsequently mismatch and match of queries, the intermediate truth degrees in the new model represent similarity of values and partial match of queries. Moreover, the truth functions of many-valued logical connectives in the new model serve to aggregate degrees of similarity. The presented approach is conceptually clean, logically sound, and retains most properties of the classical model while enabling us to employ new types of queries and data dependencies. Most importantly, similarity is not handled in an ad hoc way or by putting a "similarity module" atop the classical model in our approach. Rather, it is consistently viewed as a notion that generalizes and replaces equality in the very core of the relational model. We present fundamentals of the formal model and two equivalent query systems which are analogues of the classical relational algebra and domain relational calculus with range declarations. In the sequel to this paper, we deal with similarity-based dependencies.

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

PubMed Central

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

2016-01-01

Objective 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. Materials and Methods 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. Results 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. Discussion 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. Conclusion 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. PMID:26911818

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.

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).

Nosql for Storage and Retrieval of Large LIDAR Data Collections

NASA Astrophysics Data System (ADS)

Boehm, J.; Liu, K.

2015-08-01

Developments in LiDAR technology over the past decades have made LiDAR to become a mature and widely accepted source of geospatial information. This in turn has led to an enormous growth in data volume. The central idea for a file-centric storage of LiDAR point clouds is the observation that large collections of LiDAR data are typically delivered as large collections of files, rather than single files of terabyte size. This split of the dataset, commonly referred to as tiling, was usually done to accommodate a specific processing pipeline. It makes therefore sense to preserve this split. A document oriented NoSQL database can easily emulate this data partitioning, by representing each tile (file) in a separate document. The document stores the metadata of the tile. The actual files are stored in a distributed file system emulated by the NoSQL database. We demonstrate the use of MongoDB a highly scalable document oriented NoSQL database for storing large LiDAR files. MongoDB like any NoSQL database allows for queries on the attributes of the document. As a specialty MongoDB also allows spatial queries. Hence we can perform spatial queries on the bounding boxes of the LiDAR tiles. Inserting and retrieving files on a cloud-based database is compared to native file system and cloud storage transfer speed.

The EarthServer Federation: State, Role, and Contribution to GEOSS

NASA Astrophysics Data System (ADS)

Merticariu, Vlad; Baumann, Peter

2016-04-01

The intercontinental EarthServer initiative has established a European datacube platform with proven scalability: known databases exceed 100 TB, and single queries have been split across more than 1,000 cloud nodes. Its service interface being rigorously based on the OGC "Big Geo Data" standards, Web Coverage Service (WCS) and Web Coverage Processing Service (WCPS), a series of clients can dock into the services, ranging from open-source OpenLayers and QGIS over open-source NASA WorldWind to proprietary ESRI ArcGIS. Datacube fusion in a "mix and match" style is supported by the platform technolgy, the rasdaman Array Database System, which transparently federates queries so that users simply approach any node of the federation to access any data item, internally optimized for minimal data transfer. Notably, rasdaman is part of GEOSS GCI. NASA is contributing its Web WorldWind virtual globe for user-friendly data extraction, navigation, and analysis. Integrated datacube / metadata queries are contributed by CITE. Current federation members include ESA (managed by MEEO sr.l.), Plymouth Marine Laboratory (PML), the European Centre for Medium-Range Weather Forecast (ECMWF), Australia's National Computational Infrastructure, and Jacobs University (adding in Planetary Science). Further data centers have expressed interest in joining. We present the EarthServer approach, discuss its underlying technology, and illustrate the contribution this datacube platform can make to GEOSS.

A Taxonomic Search Engine: Federating taxonomic databases using web services

PubMed Central

Page, Roderic DM

2005-01-01

Background The taxonomic name of an organism is a key link between different databases that store information on that organism. However, in the absence of a single, comprehensive database of organism names, individual databases lack an easy means of checking the correctness of a name. Furthermore, the same organism may have more than one name, and the same name may apply to more than one organism. Results The Taxonomic Search Engine (TSE) is a web application written in PHP that queries multiple taxonomic databases (ITIS, Index Fungorum, IPNI, NCBI, and uBIO) and summarises the results in a consistent format. It supports "drill-down" queries to retrieve a specific record. The TSE can optionally suggest alternative spellings the user can try. It also acts as a Life Science Identifier (LSID) authority for the source taxonomic databases, providing globally unique identifiers (and associated metadata) for each name. Conclusion The Taxonomic Search Engine is available at and provides a simple demonstration of the potential of the federated approach to providing access to taxonomic names. PMID:15757517

PDBj Mine: design and implementation of relational database interface for Protein Data Bank Japan

PubMed Central

Kinjo, Akira R.; Yamashita, Reiko; Nakamura, Haruki

2010-01-01

This article is a tutorial for PDBj Mine, a new database and its interface for Protein Data Bank Japan (PDBj). In PDBj Mine, data are loaded from files in the PDBMLplus format (an extension of PDBML, PDB's canonical XML format, enriched with annotations), which are then served for the user of PDBj via the worldwide web (WWW). We describe the basic design of the relational database (RDB) and web interfaces of PDBj Mine. The contents of PDBMLplus files are first broken into XPath entities, and these paths and data are indexed in the way that reflects the hierarchical structure of the XML files. The data for each XPath type are saved into the corresponding relational table that is named as the XPath itself. The generation of table definitions from the PDBMLplus XML schema is fully automated. For efficient search, frequently queried terms are compiled into a brief summary table. Casual users can perform simple keyword search, and 'Advanced Search' which can specify various conditions on the entries. More experienced users can query the database using SQL statements which can be constructed in a uniform manner. Thus, PDBj Mine achieves a combination of the flexibility of XML documents and the robustness of the RDB. Database URL: http://www.pdbj.org/ PMID:20798081

PDBj Mine: design and implementation of relational database interface for Protein Data Bank Japan.

PubMed

Kinjo, Akira R; Yamashita, Reiko; Nakamura, Haruki

2010-08-25

This article is a tutorial for PDBj Mine, a new database and its interface for Protein Data Bank Japan (PDBj). In PDBj Mine, data are loaded from files in the PDBMLplus format (an extension of PDBML, PDB's canonical XML format, enriched with annotations), which are then served for the user of PDBj via the worldwide web (WWW). We describe the basic design of the relational database (RDB) and web interfaces of PDBj Mine. The contents of PDBMLplus files are first broken into XPath entities, and these paths and data are indexed in the way that reflects the hierarchical structure of the XML files. The data for each XPath type are saved into the corresponding relational table that is named as the XPath itself. The generation of table definitions from the PDBMLplus XML schema is fully automated. For efficient search, frequently queried terms are compiled into a brief summary table. Casual users can perform simple keyword search, and 'Advanced Search' which can specify various conditions on the entries. More experienced users can query the database using SQL statements which can be constructed in a uniform manner. Thus, PDBj Mine achieves a combination of the flexibility of XML documents and the robustness of the RDB. Database URL: http://www.pdbj.org/

Microreact: visualizing and sharing data for genomic epidemiology and phylogeography

PubMed Central

Argimón, Silvia; Abudahab, Khalil; Goater, Richard J. E.; Fedosejev, Artemij; Bhai, Jyothish; Glasner, Corinna; Feil, Edward J.; Holden, Matthew T. G.; Yeats, Corin A.; Grundmann, Hajo; Spratt, Brian G.

2016-01-01

Visualization is frequently used to aid our interpretation of complex datasets. Within microbial genomics, visualizing the relationships between multiple genomes as a tree provides a framework onto which associated data (geographical, temporal, phenotypic and epidemiological) are added to generate hypotheses and to explore the dynamics of the system under investigation. Selected static images are then used within publications to highlight the key findings to a wider audience. However, these images are a very inadequate way of exploring and interpreting the richness of the data. There is, therefore, a need for flexible, interactive software that presents the population genomic outputs and associated data in a user-friendly manner for a wide range of end users, from trained bioinformaticians to front-line epidemiologists and health workers. Here, we present Microreact, a web application for the easy visualization of datasets consisting of any combination of trees, geographical, temporal and associated metadata. Data files can be uploaded to Microreact directly via the web browser or by linking to their location (e.g. from Google Drive/Dropbox or via API), and an integrated visualization via trees, maps, timelines and tables provides interactive querying of the data. The visualization can be shared as a permanent web link among collaborators, or embedded within publications to enable readers to explore and download the data. Microreact can act as an end point for any tool or bioinformatic pipeline that ultimately generates a tree, and provides a simple, yet powerful, visualization method that will aid research and discovery and the open sharing of datasets. PMID:28348833

Joint Battlespace Infosphere: Information Management Within a C2 Enterprise

DTIC Science & Technology

2005-06-01

using. In version 1.2, we support both MySQL and Oracle as underlying implementations where the XML metadata schema is mapped into relational tables in...Identity Servers, Role-Based Access Control, and Policy Representation – Databases: Oracle , MySQL , TigerLogic, Berkeley XML DB 15 Instrumentation Services...converted to SQL for execution. Invocations are then forwarded to the appropriate underlying IOR core components that have the responsibility of issuing

A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases

PubMed Central

Ke, Shengnan; Gong, Jun; Li, Songnian; Zhu, Qing; Liu, Xintao; Zhang, Yeting

2014-01-01

In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type. PMID:25051028

A hybrid spatio-temporal data indexing method for trajectory databases.

PubMed

Ke, Shengnan; Gong, Jun; Li, Songnian; Zhu, Qing; Liu, Xintao; Zhang, Yeting

2014-07-21

In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type.

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.

The ANSS Station Information System: A Centralized Station Metadata Repository for Populating, Managing and Distributing Seismic Station Metadata

NASA Astrophysics Data System (ADS)

Thomas, V. I.; Yu, E.; Acharya, P.; Jaramillo, J.; Chowdhury, F.

2015-12-01

Maintaining and archiving accurate site metadata is critical for seismic network operations. The Advanced National Seismic System (ANSS) Station Information System (SIS) is a repository of seismic network field equipment, equipment response, and other site information. Currently, there are 187 different sensor models and 114 data-logger models in SIS. SIS has a web-based user interface that allows network operators to enter information about seismic equipment and assign response parameters to it. It allows users to log entries for sites, equipment, and data streams. Users can also track when equipment is installed, updated, and/or removed from sites. When seismic equipment configurations change for a site, SIS computes the overall gain of a data channel by combining the response parameters of the underlying hardware components. Users can then distribute this metadata in standardized formats such as FDSN StationXML or dataless SEED. One powerful advantage of SIS is that existing data in the repository can be leveraged: e.g., new instruments can be assigned response parameters from the Incorporated Research Institutions for Seismology (IRIS) Nominal Response Library (NRL), or from a similar instrument already in the inventory, thereby reducing the amount of time needed to determine parameters when new equipment (or models) are introduced into a network. SIS is also useful for managing field equipment that does not produce seismic data (eg power systems, telemetry devices or GPS receivers) and gives the network operator a comprehensive view of site field work. SIS allows users to generate field logs to document activities and inventory at sites. Thus, operators can also use SIS reporting capabilities to improve planning and maintenance of the network. Queries such as how many sensors of a certain model are installed or what pieces of equipment have active problem reports are just a few examples of the type of information that is available to SIS users.

Modular design, application architecture, and usage of a self-service model for enterprise data delivery: The Duke Enterprise Data Unified Content Explorer (DEDUCE)

PubMed Central

Horvath, Monica M.; Rusincovitch, Shelley A.; Brinson, Stephanie; Shang, Howard C.; Evans, Steve; Ferranti, Jeffrey M.

2015-01-01

Purpose Data generated in the care of patients are widely used to support clinical research and quality improvement, which has hastened the development of self-service query tools. User interface design for such tools, execution of query activity, and underlying application architecture have not been widely reported, and existing tools reflect a wide heterogeneity of methods and technical frameworks. We describe the design, application architecture, and use of a self-service model for enterprise data delivery within Duke Medicine. Methods Our query platform, the Duke Enterprise Data Unified Content Explorer (DEDUCE), supports enhanced data exploration, cohort identification, and data extraction from our enterprise data warehouse (EDW) using a series of modular environments that interact with a central keystone module, Cohort Manager (CM). A data-driven application architecture is implemented through three components: an application data dictionary, the concept of “smart dimensions”, and dynamically-generated user interfaces. Results DEDUCE CM allows flexible hierarchies of EDW queries within a grid-like workspace. A cohort “join” functionality allows switching between filters based on criteria occurring within or across patient encounters. To date, 674 users have been trained and activated in DEDUCE, and logon activity shows a steady increase, with variability between months. A comparison of filter conditions and export criteria shows that these activities have different patterns of usage across subject areas. Conclusions Organizations with sophisticated EDWs may find that users benefit from development of advanced query functionality, complimentary to the user interfaces and infrastructure used in other well-published models. Driven by its EDW context, the DEDUCE application architecture was also designed to be responsive to source data and to allow modification through alterations in metadata rather than programming, allowing an agile response to source system changes. PMID:25051403

Modular design, application architecture, and usage of a self-service model for enterprise data delivery: the Duke Enterprise Data Unified Content Explorer (DEDUCE).

PubMed

Horvath, Monica M; Rusincovitch, Shelley A; Brinson, Stephanie; Shang, Howard C; Evans, Steve; Ferranti, Jeffrey M

2014-12-01

Data generated in the care of patients are widely used to support clinical research and quality improvement, which has hastened the development of self-service query tools. User interface design for such tools, execution of query activity, and underlying application architecture have not been widely reported, and existing tools reflect a wide heterogeneity of methods and technical frameworks. We describe the design, application architecture, and use of a self-service model for enterprise data delivery within Duke Medicine. Our query platform, the Duke Enterprise Data Unified Content Explorer (DEDUCE), supports enhanced data exploration, cohort identification, and data extraction from our enterprise data warehouse (EDW) using a series of modular environments that interact with a central keystone module, Cohort Manager (CM). A data-driven application architecture is implemented through three components: an application data dictionary, the concept of "smart dimensions", and dynamically-generated user interfaces. DEDUCE CM allows flexible hierarchies of EDW queries within a grid-like workspace. A cohort "join" functionality allows switching between filters based on criteria occurring within or across patient encounters. To date, 674 users have been trained and activated in DEDUCE, and logon activity shows a steady increase, with variability between months. A comparison of filter conditions and export criteria shows that these activities have different patterns of usage across subject areas. Organizations with sophisticated EDWs may find that users benefit from development of advanced query functionality, complimentary to the user interfaces and infrastructure used in other well-published models. Driven by its EDW context, the DEDUCE application architecture was also designed to be responsive to source data and to allow modification through alterations in metadata rather than programming, allowing an agile response to source system changes. Copyright © 2014 Elsevier Inc. All rights reserved.

Unclassified Data Export from the Containment Database

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

Gaylord, Jessie M.; Myers, K. B. L.

2016-08-03

The attached dataset is an unclassified subset of data copied from the CDB for release to a wider audience. It includes only the clearly unclassified columns from each of the tables in the CDB, and only the rows related to announced tests. Also included is a glossary that lists each of the tables and columns included in the export with its definition, historical labels, unit of measure, and reference information. Our objective is to make this unclassified dataset available for querying on an unclassified server through a repeatable process.

Karst database development in Minnesota: Design and data assembly

USGS Publications Warehouse

Gao, Y.; Alexander, E.C.; Tipping, R.G.

2005-01-01

The Karst Feature Database (KFD) of Minnesota is a relational GIS-based Database Management System (DBMS). Previous karst feature datasets used inconsistent attributes to describe karst features in different areas of Minnesota. Existing metadata were modified and standardized to represent a comprehensive metadata for all the karst features in Minnesota. Microsoft Access 2000 and ArcView 3.2 were used to develop this working database. Existing county and sub-county karst feature datasets have been assembled into the KFD, which is capable of visualizing and analyzing the entire data set. By November 17 2002, 11,682 karst features were stored in the KFD of Minnesota. Data tables are stored in a Microsoft Access 2000 DBMS and linked to corresponding ArcView applications. The current KFD of Minnesota has been moved from a Windows NT server to a Windows 2000 Citrix server accessible to researchers and planners through networked interfaces. ?? Springer-Verlag 2005.

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.

Software Application Profile: Opal and Mica: open-source software solutions for epidemiological data management, harmonization and dissemination

PubMed Central

Doiron, Dany; Marcon, Yannick; Fortier, Isabel; Burton, Paul; Ferretti, Vincent

2017-01-01

Abstract Motivation Improving the dissemination of information on existing epidemiological studies and facilitating the interoperability of study databases are essential to maximizing the use of resources and accelerating improvements in health. To address this, Maelstrom Research proposes Opal and Mica, two inter-operable open-source software packages providing out-of-the-box solutions for epidemiological data management, harmonization and dissemination. Implementation Opal and Mica are two standalone but inter-operable web applications written in Java, JavaScript and PHP. They provide web services and modern user interfaces to access them. General features Opal allows users to import, manage, annotate and harmonize study data. Mica is used to build searchable web portals disseminating study and variable metadata. When used conjointly, Mica users can securely query and retrieve summary statistics on geographically dispersed Opal servers in real-time. Integration with the DataSHIELD approach allows conducting more complex federated analyses involving statistical models. Availability Opal and Mica are open-source and freely available at [www.obiba.org] under a General Public License (GPL) version 3, and the metadata models and taxonomies that accompany them are available under a Creative Commons licence. PMID:29025122

GeoCrystal: graphic-interactive access to geodata archives

NASA Astrophysics Data System (ADS)

Goebel, Stefan; Haist, Joerg; Jasnoch, Uwe

2002-03-01

Recently there is spent a lot of effort to establish information systems and global infrastructures enabling both data suppliers and users to describe (-> eCommerce, metadata) as well as to find appropriate data. Examples for this are metadata information systems, online-shops or portals for geodata. The main disadvantages of existing approaches are insufficient methods and mechanisms leading users to (e.g. spatial) data archives. This affects aspects concerning usability and personalization in general as well as visual feedback techniques in the different steps of the information retrieval process. Several approaches aim at the improvement of graphical user interfaces by using intuitive metaphors, but only some of them offer 3D interfaces in the form of information landscapes or geographic result scenes in the context of information systems for geodata. This paper presents GeoCrystal, which basic idea is to adopt Venn diagrams to compose complex queries and to visualize search results in a 3D information and navigation space for geodata. These concepts are enhanced with spatial metaphors and 3D information landscapes (library for geodata) wherein users can specify searches for appropriate geodata and are enabled to graphic-interactively communicate with search results (book metaphor).

Making Temporal Search More Central in Spatial Data Infrastructures

NASA Astrophysics Data System (ADS)

Corti, P.; Lewis, B.

2017-10-01

A temporally enabled Spatial Data Infrastructure (SDI) is a framework of geospatial data, metadata, users, and tools intended to provide an efficient and flexible way to use spatial information which includes the historical dimension. One of the key software components of an SDI is the catalogue service which is needed to discover, query, and manage the metadata. A search engine is a software system capable of supporting fast and reliable search, which may use any means necessary to get users to the resources they need quickly and efficiently. These techniques may include features such as full text search, natural language processing, weighted results, temporal search based on enrichment, visualization of patterns in distributions of results in time and space using temporal and spatial faceting, and many others. In this paper we will focus on the temporal aspects of search which include temporal enrichment using a time miner - a software engine able to search for date components within a larger block of text, the storage of time ranges in the search engine, handling historical dates, and the use of temporal histograms in the user interface to display the temporal distribution of search results.

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

DOE PAGES

Paez-Espino, David; Chen, I. -Min A.; Palaniappan, Krishna; ...

2016-10-30

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 aremore » 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 comparingwith external sequences, thus serving as an essential resource in the viral genomics community.« less

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

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

Paez-Espino, David; Chen, I. -Min A.; Palaniappan, Krishna

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 aremore » 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 comparingwith external sequences, thus serving as an essential resource in the viral genomics community.« less

Automatically exposing OpenLifeData via SADI semantic Web Services.

PubMed

González, Alejandro Rodríguez; Callahan, Alison; Cruz-Toledo, José; Garcia, Adrian; Egaña Aranguren, Mikel; Dumontier, Michel; Wilkinson, Mark D

2014-01-01

Two distinct trends are emerging with respect to how data is shared, collected, and analyzed within the bioinformatics community. First, Linked Data, exposed as SPARQL endpoints, promises to make data easier to collect and integrate by moving towards the harmonization of data syntax, descriptive vocabularies, and identifiers, as well as providing a standardized mechanism for data access. Second, Web Services, often linked together into workflows, normalize data access and create transparent, reproducible scientific methodologies that can, in principle, be re-used and customized to suit new scientific questions. Constructing queries that traverse semantically-rich Linked Data requires substantial expertise, yet traditional RESTful or SOAP Web Services cannot adequately describe the content of a SPARQL endpoint. We propose that content-driven Semantic Web Services can enable facile discovery of Linked Data, independent of their location. We use a well-curated Linked Dataset - OpenLifeData - and utilize its descriptive metadata to automatically configure a series of more than 22,000 Semantic Web Services that expose all of its content via the SADI set of design principles. The OpenLifeData SADI services are discoverable via queries to the SHARE registry and easy to integrate into new or existing bioinformatics workflows and analytical pipelines. We demonstrate the utility of this system through comparison of Web Service-mediated data access with traditional SPARQL, and note that this approach not only simplifies data retrieval, but simultaneously provides protection against resource-intensive queries. We show, through a variety of different clients and examples of varying complexity, that data from the myriad OpenLifeData can be recovered without any need for prior-knowledge of the content or structure of the SPARQL endpoints. We also demonstrate that, via clients such as SHARE, the complexity of federated SPARQL queries is dramatically reduced.

Modeling and interoperability of heterogeneous genomic big data for integrative processing and querying.

PubMed

Masseroli, Marco; Kaitoua, Abdulrahman; Pinoli, Pietro; Ceri, Stefano

2016-12-01

While a huge amount of (epi)genomic data of multiple types is becoming available by using Next Generation Sequencing (NGS) technologies, the most important emerging problem is the so-called tertiary analysis, concerned with sense making, e.g., discovering how different (epi)genomic regions and their products interact and cooperate with each other. We propose a paradigm shift in tertiary analysis, based on the use of the Genomic Data Model (GDM), a simple data model which links genomic feature data to their associated experimental, biological and clinical metadata. GDM encompasses all the data formats which have been produced for feature extraction from (epi)genomic datasets. We specifically describe the mapping to GDM of SAM (Sequence Alignment/Map), VCF (Variant Call Format), NARROWPEAK (for called peaks produced by NGS ChIP-seq or DNase-seq methods), and BED (Browser Extensible Data) formats, but GDM supports as well all the formats describing experimental datasets (e.g., including copy number variations, DNA somatic mutations, or gene expressions) and annotations (e.g., regarding transcription start sites, genes, enhancers or CpG islands). We downloaded and integrated samples of all the above-mentioned data types and formats from multiple sources. The GDM is able to homogeneously describe semantically heterogeneous data and makes the ground for providing data interoperability, e.g., achieved through the GenoMetric Query Language (GMQL), a high-level, declarative query language for genomic big data. The combined use of the data model and the query language allows comprehensive processing of multiple heterogeneous data, and supports the development of domain-specific data-driven computations and bio-molecular knowledge discovery. Copyright © 2016 Elsevier Inc. All rights reserved.

HTML5 PivotViewer: high-throughput visualization and querying of image data on the web

PubMed Central

Taylor, Stephen; Noble, Roger

2014-01-01

Motivation: Visualization and analysis of large numbers of biological images has generated a bottle neck in research. We present HTML5 PivotViewer, a novel, open source, platform-independent viewer making use of the latest web technologies that allows seamless access to images and associated metadata for each image. This provides a powerful method to allow end users to mine their data. Availability and implementation: Documentation, examples and links to the software are available from http://www.cbrg.ox.ac.uk/data/pivotviewer/. The software is licensed under GPLv2. Contact:  stephen.taylor@imm.ox.ac.uk and roger@coritsu.com PMID:24849578

NCBI GEO: archive for functional genomics data sets—update

PubMed Central

Barrett, Tanya; Wilhite, Stephen E.; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F.; Tomashevsky, Maxim; Marshall, Kimberly A.; Phillippy, Katherine H.; Sherman, Patti M.; Holko, Michelle; Yefanov, Andrey; Lee, Hyeseung; Zhang, Naigong; Robertson, Cynthia L.; Serova, Nadezhda; Davis, Sean; Soboleva, Alexandra

2013-01-01

The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data. PMID:23193258

Reliable and Persistent Identification of Linked Data Elements

NASA Astrophysics Data System (ADS)

Wood, David

Linked Data techniques rely upon common terminology in a manner similar to a relational database'vs reliance on a schema. Linked Data terminology anchors metadata descriptions and facilitates navigation of information. Common vocabularies ease the human, social tasks of understanding datasets sufficiently to construct queries and help to relate otherwise disparate datasets. Vocabulary terms must, when using the Resource Description Framework, be grounded in URIs. A current bestpractice on the World Wide Web is to serve vocabulary terms as Uniform Resource Locators (URLs) and present both human-readable and machine-readable representations to the public. Linked Data terminology published to theWorldWideWeb may be used by others without reference or notification to the publishing party. That presents a problem: Vocabulary publishers take on an implicit responsibility to maintain and publish their terms via the URLs originally assigned, regardless of the inconvenience such a responsibility may cause. Over the course of years, people change jobs, publishing organizations change Internet domain names, computers change IP addresses,systems administrators publish old material in new ways. Clearly, a mechanism is required to manageWeb-based vocabularies over a long term. This chapter places Linked Data vocabularies in context with the wider concepts of metadata in general and specifically metadata on the Web. Persistent identifier mechanisms are reviewed, with a particular emphasis on Persistent URLs, or PURLs. PURLs and PURL services are discussed in the context of Linked Data. Finally, historic weaknesses of PURLs are resolved by the introduction of a federation of PURL services to address needs specific to Linked Data.

Astronomical Data Processing Using SciQL, an SQL Based Query Language for Array Data

NASA Astrophysics Data System (ADS)

Zhang, Y.; Scheers, B.; Kersten, M.; Ivanova, M.; Nes, N.

2012-09-01

SciQL (pronounced as ‘cycle’) is a novel SQL-based array query language for scientific applications with both tables and arrays as first class citizens. SciQL lowers the entrance fee of adopting relational DBMS (RDBMS) in scientific domains, because it includes functionality often only found in mathematics software packages. In this paper, we demonstrate the usefulness of SciQL for astronomical data processing using examples from the Transient Key Project of the LOFAR radio telescope. In particular, how the LOFAR light-curve database of all detected sources can be constructed, by correlating sources across the spatial, frequency, time and polarisation domains.

Simulation of Tasks Distribution in Horizontally Scalable Management System

NASA Astrophysics Data System (ADS)

Kustov, D.; Sherstneva, A.; Botygin, I.

2016-08-01

This paper presents an imitational model of the task distribution system for the components of territorially-distributed automated management system with a dynamically changing topology. Each resource of the distributed automated management system is represented with an agent, which allows to set behavior of every resource in the best possible way and ensure their interaction. The agent work load imitation was done via service query imitation formed in a system dynamics style using a stream diagram. The query generation took place in the abstract-represented center - afterwards, they were sent to the drive to be distributed to management system resources according to a ranking table.

Method and system for efficiently searching an encoded vector index

DOEpatents

Bui, Thuan Quang; Egan, Randy Lynn; Kathmann, Kevin James

2001-09-04

Method and system aspects for efficiently searching an encoded vector index are provided. The aspects include the translation of a search query into a candidate bitmap, and the mapping of data from the candidate bitmap into a search result bitmap according to entry values in the encoded vector index. Further, the translation includes the setting of a bit in the candidate bitmap for each entry in a symbol table that corresponds to candidate of the search query. Also included in the mapping is the identification of a bit value in the candidate bitmap pointed to by an entry in an encoded vector.

Flexible querying of Web data to simulate bacterial growth in food.

PubMed

Buche, Patrice; Couvert, Olivier; Dibie-Barthélemy, Juliette; Hignette, Gaëlle; Mettler, Eric; Soler, Lydie

2011-06-01

A preliminary step in microbial risk assessment in foods is the gathering of experimental data. In the framework of the Sym'Previus project, we have designed a complete data integration system opened on the Web which allows a local database to be complemented by data extracted from the Web and annotated using a domain ontology. We focus on the Web data tables as they contain, in general, a synthesis of data published in the documents. We propose in this paper a flexible querying system using the domain ontology to scan simultaneously local and Web data, this in order to feed the predictive modeling tools available on the Sym'Previus platform. Special attention is paid on the way fuzzy annotations associated with Web data are taken into account in the querying process, which is an important and original contribution of the proposed system. Copyright © 2010 Elsevier Ltd. All rights reserved.

Data warehouse implementation with clinical pharmacokinetic/pharmacodynamic data.

PubMed

Koprowski, S P; Barrett, J S

2002-03-01

We have created a data warehouse for human pharmacokinetic (PK) and pharmacodynamic (PD) data generated primarily within the Clinical PK Group of the Drug Metabolism and Pharmacokinetics (DM&PK) Department of DuPont Pharmaceuticals. Data which enters an Oracle-based LIMS directly from chromatography systems or through files from contract research organizations are accessed via SAS/PH.Kinetics, GLP-compliant data analysis software residing on individual users' workstations. Upon completion of the final PK or PD analysis, data are pushed to a predefined location. Data analyzed/created with other software (i.e., WinNonlin, NONMEM, Adapt, etc.) are added to this file repository as well. The warehouse creates views to these data and accumulates metadata on all data sources defined in the warehouse. The warehouse is managed via the SAS/Warehouse Administrator product that defines the environment, creates summarized data structures, and schedules data refresh. The clinical PK/PD warehouse encompasses laboratory, biometric, PK and PD data streams. Detailed logical tables for each compound are created/updated as the clinical PK/PD data warehouse is populated. The data model defined to the warehouse is based on a star schema. Summarized data structures such as multidimensional data bases (MDDB), infomarts, and datamarts are created from detail tables. Data mining and querying of highly summarized data as well as drill-down to detail data is possible via the creation of exploitation tools which front-end the warehouse data. Based on periodic refreshing of the warehouse data, these applications are able to access the most current data available and do not require a manual interface to update/populate the data store. Prototype applications have been web-enabled to facilitate their usage to varied data customers across platform and location. The warehouse also contains automated mechanisms for the construction of study data listings and SAS transport files for eventual incorporation into an electronic submission. This environment permits the management of online analytical processing via a single administrator once the data model and warehouse configuration have been designed. The expansion of the current environment will eventually connect data from all phases of research and development ensuring the return on investment and hopefully efficiencies in data processing unforeseen with earlier legacy systems.

Review on the Celestial Sphere Positioning of FITS Format Image Based on WCS and Research on General Visualization

NASA Astrophysics Data System (ADS)

Song, W. M.; Fan, D. W.; Su, L. Y.; Cui, C. Z.

2017-11-01

Calculating the coordinate parameters recorded in the form of key/value pairs in FITS (Flexible Image Transport System) header is the key to determine FITS images' position in the celestial system. As a result, it has great significance in researching the general process of calculating the coordinate parameters. By combining CCD related parameters of astronomical telescope (such as field, focal length, and celestial coordinates in optical axis, etc.), astronomical images recognition algorithm, and WCS (World Coordinate System) theory, the parameters can be calculated effectively. CCD parameters determine the scope of star catalogue, so that they can be used to build a reference star catalogue by the corresponding celestial region of astronomical images; Star pattern recognition completes the matching between the astronomical image and reference star catalogue, and obtains a table with a certain number of stars between CCD plane coordinates and their celestial coordinates for comparison; According to different projection of the sphere to the plane, WCS can build different transfer functions between these two coordinates, and the astronomical position of image pixels can be determined by the table's data we have worked before. FITS images are used to carry out scientific data transmission and analyze as a kind of mainstream data format, but only to be viewed, edited, and analyzed in the professional astronomy software. It decides the limitation of popular science education in astronomy. The realization of a general image visualization method is significant. FITS is converted to PNG or JPEG images firstly. The coordinate parameters in the FITS header are converted to metadata in the form of AVM (Astronomy Visualization Metadata), and then the metadata is added to the PNG or JPEG header. This method can meet amateur astronomers' general needs of viewing and analyzing astronomical images in the non-astronomical software platform. The overall design flow is realized through the java program and tested by SExtractor, WorldWide Telescope, picture viewer, and other software.

XLWrap - Querying and Integrating Arbitrary Spreadsheets with SPARQL

NASA Astrophysics Data System (ADS)

Langegger, Andreas; Wöß, Wolfram

In this paper a novel approach is presented for generating RDF graphs of arbitrary complexity from various spreadsheet layouts. Currently, none of the available spreadsheet-to-RDF wrappers supports cross tables and tables where data is not aligned in rows. Similar to RDF123, XLWrap is based on template graphs where fragments of triples can be mapped to specific cells of a spreadsheet. Additionally, it features a full expression algebra based on the syntax of OpenOffice Calc and various shift operations, which can be used to repeat similar mappings in order to wrap cross tables including multiple sheets and spreadsheet files. The set of available expression functions includes most of the native functions of OpenOffice Calc and can be easily extended by users of XLWrap.

Ontology-Based Peer Exchange Network (OPEN)

ERIC Educational Resources Information Center

Dong, Hui

2010-01-01

In current Peer-to-Peer networks, distributed and semantic free indexing is widely used by systems adopting "Distributed Hash Table" ("DHT") mechanisms. Although such systems typically solve a. user query rather fast in a deterministic way, they only support a very narrow search scheme, namely the exact hash key match. Furthermore, DHT systems put…

Unifying Access to National Hydrologic Data Repositories via Web Services

NASA Astrophysics Data System (ADS)

Valentine, D. W.; Jennings, B.; Zaslavsky, I.; Maidment, D. R.

2006-12-01

The CUAHSI hydrologic information system (HIS) is designed to be a live, multiscale web portal system for accessing, querying, visualizing, and publishing distributed hydrologic observation data and models for any location or region in the United States. The HIS design follows the principles of open service oriented architecture, i.e. system components are represented as web services with well defined standard service APIs. WaterOneFlow web services are the main component of the design. The currently available services have been completely re-written compared to the previous version, and provide programmatic access to USGS NWIS. (steam flow, groundwater and water quality repositories), DAYMET daily observations, NASA MODIS, and Unidata NAM streams, with several additional web service wrappers being added (EPA STORET, NCDC and others.). Different repositories of hydrologic data use different vocabularies, and support different types of query access. Resolving semantic and structural heterogeneities across different hydrologic observation archives and distilling a generic set of service signatures is one of the main scalability challenges in this project, and a requirement in our web service design. To accomplish the uniformity of the web services API, data repositories are modeled following the CUAHSI Observation Data Model. The web service responses are document-based, and use an XML schema to express the semantics in a standard format. Access to station metadata is provided via web service methods, GetSites, GetSiteInfo and GetVariableInfo. The methdods form the foundation of CUAHSI HIS discovery interface and may execute over locally-stored metadata or request the information from remote repositories directly. Observation values are retrieved via a generic GetValues method which is executed against national data repositories. The service is implemented in ASP.Net, and other providers are implementing WaterOneFlow services in java. Reference implementation of WaterOneFlow web services is available. More information about the ongoing development of CUAHSI HIS is available from http://www.cuahsi.org/his/.

Cytometry metadata in XML

NASA Astrophysics Data System (ADS)

Leif, Robert C.; Leif, Stephanie H.

2016-04-01

Introduction: The International Society for Advancement of Cytometry (ISAC) has created a standard for the Minimum Information about a Flow Cytometry Experiment (MIFlowCyt 1.0). CytometryML will serve as a common metadata standard for flow and image cytometry (digital microscopy). Methods: The MIFlowCyt data-types were created, as is the rest of CytometryML, in the XML Schema Definition Language (XSD1.1). The datatypes are primarily based on the Flow Cytometry and the Digital Imaging and Communication (DICOM) standards. A small section of the code was formatted with standard HTML formatting elements (p, h1, h2, etc.). Results:1) The part of MIFlowCyt that describes the Experimental Overview including the specimen and substantial parts of several other major elements has been implemented as CytometryML XML schemas (www.cytometryml.org). 2) The feasibility of using MIFlowCyt to provide the combination of an overview, table of contents, and/or an index of a scientific paper or a report has been demonstrated. Previously, a sample electronic publication, EPUB, was created that could contain both MIFlowCyt metadata as well as the binary data. Conclusions: The use of CytometryML technology together with XHTML5 and CSS permits the metadata to be directly formatted and together with the binary data to be stored in an EPUB container. This will facilitate: formatting, data- mining, presentation, data verification, and inclusion in structured research, clinical, and regulatory documents, as well as demonstrate a publication's adherence to the MIFlowCyt standard, promote interoperability and should also result in the textual and numeric data being published using web technology without any change in composition.

A Spatially-Registered, Massively Parallelised Data Structure for Interacting with Large, Integrated Geodatasets

NASA Astrophysics Data System (ADS)

Irving, D. H.; Rasheed, M.; O'Doherty, N.

2010-12-01

The efficient storage, retrieval and interactive use of subsurface data present great challenges in geodata management. Data volumes are typically massive, complex and poorly indexed with inadequate metadata. Derived geomodels and interpretations are often tightly bound in application-centric and proprietary formats; open standards for long-term stewardship are poorly developed. Consequently current data storage is a combination of: complex Logical Data Models (LDMs) based on file storage formats; 2D GIS tree-based indexing of spatial data; and translations of serialised memory-based storage techniques into disk-based storage. Whilst adequate for working at the mesoscale over a short timeframes, these approaches all possess technical and operational shortcomings: data model complexity; anisotropy of access; scalability to large and complex datasets; and weak implementation and integration of metadata. High performance hardware such as parallelised storage and Relational Database Management System (RDBMS) have long been exploited in many solutions but the underlying data structure must provide commensurate efficiencies to allow multi-user, multi-application and near-realtime data interaction. We present an open Spatially-Registered Data Structure (SRDS) built on Massively Parallel Processing (MPP) database architecture implemented by a ANSI SQL 2008 compliant RDBMS. We propose a LDM comprising a 3D Earth model that is decomposed such that each increasing Level of Detail (LoD) is achieved by recursively halving the bin size until it is less than the error in each spatial dimension for that data point. The value of an attribute at that point is stored as a property of that point and at that LoD. It is key to the numerical efficiency of the SRDS that it is under-pinned by a power-of-two relationship thus precluding the need for computationally intensive floating point arithmetic. Our approach employed a tightly clustered MPP array with small clusters of storage, processors and memory communicating over a high-speed network inter-connect. This is a shared-nothing architecture where resources are managed within each cluster unlike most other RDBMSs. Data are accessed on this architecture by their primary index values which utilises the hashing algorithm for point-to-point access. The hashing algorithm’s main role is the efficient distribution of data across the clusters based on the primary index. In this study we used 3D seismic volumes, 2D seismic profiles and borehole logs to demonstrate application in both (x,y,TWT) and (x,y,z)-space. In the SRDS the primary index is a composite column index of (x,y) to avoid invoking time-consuming full table scans as is the case in tree-based systems. This means that data access is isotropic. A query for data in a specified spatial range permits retrieval recursively by point-to-point queries within each nested LoD yielding true linear performance up to the Petabyte scale with hardware scaling presenting the primary limiting factor. Our architecture and LDM promotes: realtime interaction with massive data volumes; streaming of result sets and server-rendered 2D/3D imagery; rigorous workflow control and auditing; and in-database algorithms run directly against data as a HPC cloud service.

A Data Integration Effort for Environmental and Epidemiological Risk Management: an Example from Latin America

NASA Astrophysics Data System (ADS)

Abad-Mota, S.; Guenni, L.; Salcedo, A.; Cardinale, Y.

2006-05-01

Climate variability, environmental degradation and poor livelihood conditions of an important proportion of the population are all key factors determining the high vulnerability of the population to natural disasters and vector-borne diseases as malaria and dengue in most tropical Latin American countries. It is not uncommon that basic bio-geophysical and hydro-meteorological data required for understanding vulnerability and risk of the population to these environmental hazards at present and on retrospective are disperse, have limited quality and are not easily accessible. In Venezuela for example, hydrometeorological data from ground based networks, are collected by different agencies for specific purposes and applications going from aviation, agriculture, hydropower generation and general public needs. In order to improve accessibility, visibility and output products, two public universities in Venezuela: Universidad Simón Bolívar (USB) and Universidad Central de Venezuela (UCV) have designed a data management project to integrate all these historical point data holdings together with the metadata relating to their origin, in a single data repository with facilities for storage, manipulation, extraction and dissemination. Several statistical analyses of the data will be presented as client tailored made products, for specific applications oriented to environmental and epidemiological risk assessments. The project has two main phases: modeling of the hidroclimatic data and its metadata and development of the web site through which services will be provided. We have collected historical data from different sources in the country. These sources use different formats and have their data at different levels of granularity. Our data model should be general enough to accomodate all these differences annotated with the appropriate metadata. The quality of these data will be evaluated, statistically and semantically. The modeled data will be stored in a database, so that queries are allowed. A web site specially designed for this project will provide an interface for querying the data, analyzing the data statistically and visualizing it in maps and images. A special module will be built to allow the execution of different applications and decision making procedures. In this module we plan to implement a scientific workflow facility which should simplify the construction of new applications over the existing data. In a final stage we will explore running some of these applications on a grid and interact with the Grid Venezuela Project being developed in our country by other groups of researchers. The development of this data project includes facilities to incorporate real time data from a newer generation of measurement devices to assure an ongoing data integration activity in the near future.

Treemap Visualization for Space Situational Awareness

DTIC Science & Technology

2015-10-18

virtually any display like a table with textual metadata, a hyperlink to a web page, or another treemap. Animation can be used to “explode” the tile to...release; distribution unlimited. 88ABW Cleared 07/30/2015; 88ABW-2015-3828. In Fig. 7 shown below, we have chosen to select “Size By Radar Cross...Section ( RCS )”. We’re still looking at the same Unclassified Space Catalog scenario, but we’ve simply chosen a different “Size by” option, and the view

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.

GEO Label Web Services for Dynamic and Effective Communication of Geospatial Metadata Quality

NASA Astrophysics Data System (ADS)

Lush, Victoria; Nüst, Daniel; Bastin, Lucy; Masó, Joan; Lumsden, Jo

2014-05-01

We present demonstrations of the GEO label Web services and their integration into a prototype extension of the GEOSS portal (http://scgeoviqua.sapienzaconsulting.com/web/guest/geo_home), the GMU portal (http://gis.csiss.gmu.edu/GADMFS/) and a GeoNetwork catalog application (http://uncertdata.aston.ac.uk:8080/geonetwork/srv/eng/main.home). The GEO label is designed to communicate, and facilitate interrogation of, geospatial quality information with a view to supporting efficient and effective dataset selection on the basis of quality, trustworthiness and fitness for use. The GEO label which we propose was developed and evaluated according to a user-centred design (UCD) approach in order to maximise the likelihood of user acceptance once deployed. The resulting label is dynamically generated from producer metadata in ISO or FDGC format, and incorporates user feedback on dataset usage, ratings and discovered issues, in order to supply a highly informative summary of metadata completeness and quality. The label was easily incorporated into a community portal as part of the GEO Architecture Implementation Programme (AIP-6) and has been successfully integrated into a prototype extension of the GEOSS portal, as well as the popular metadata catalog and editor, GeoNetwork. The design of the GEO label was based on 4 user studies conducted to: (1) elicit initial user requirements; (2) investigate initial user views on the concept of a GEO label and its potential role; (3) evaluate prototype label visualizations; and (4) evaluate and validate physical GEO label prototypes. The results of these studies indicated that users and producers support the concept of a label with drill-down interrogation facility, combining eight geospatial data informational aspects, namely: producer profile, producer comments, lineage information, standards compliance, quality information, user feedback, expert reviews, and citations information. These are delivered as eight facets of a wheel-like label, which are coloured according to metadata availability and are clickable to allow a user to engage with the original metadata and explore specific aspects in more detail. To support this graphical representation and allow for wider deployment architectures we have implemented two Web services, a PHP and a Java implementation, that generate GEO label representations by combining producer metadata (from standard catalogues or other published locations) with structured user feedback. Both services accept encoded URLs of publicly available metadata documents or metadata XML files as HTTP POST and GET requests and apply XPath and XSLT mappings to transform producer and feedback XML documents into clickable SVG GEO label representations. The label and services are underpinned by two XML-based quality models. The first is a producer model that extends ISO 19115 and 19157 to allow fuller citation of reference data, presentation of pixel- and dataset- level statistical quality information, and encoding of 'traceability' information on the lineage of an actual quality assessment. The second is a user quality model (realised as a feedback server and client) which allows reporting and query of ratings, usage reports, citations, comments and other domain knowledge. Both services are Open Source and are available on GitHub at https://github.com/lushv/geolabel-service and https://github.com/52North/GEO-label-java. The functionality of these services can be tested using our GEO label generation demos, available online at http://www.geolabel.net/demo.html and http://geoviqua.dev.52north.org/glbservice/index.jsf.

A similarity-based data warehousing environment for medical images.

PubMed

Teixeira, Jefferson William; Annibal, Luana Peixoto; Felipe, Joaquim Cezar; Ciferri, Ricardo Rodrigues; Ciferri, Cristina Dutra de Aguiar

2015-11-01

A core issue of the decision-making process in the medical field is to support the execution of analytical (OLAP) similarity queries over images in data warehousing environments. In this paper, we focus on this issue. We propose imageDWE, a non-conventional data warehousing environment that enables the storage of intrinsic features taken from medical images in a data warehouse and supports OLAP similarity queries over them. To comply with this goal, we introduce the concept of perceptual layer, which is an abstraction used to represent an image dataset according to a given feature descriptor in order to enable similarity search. Based on this concept, we propose the imageDW, an extended data warehouse with dimension tables specifically designed to support one or more perceptual layers. We also detail how to build an imageDW and how to load image data into it. Furthermore, we show how to process OLAP similarity queries composed of a conventional predicate and a similarity search predicate that encompasses the specification of one or more perceptual layers. Moreover, we introduce an index technique to improve the OLAP query processing over images. We carried out performance tests over a data warehouse environment that consolidated medical images from exams of several modalities. The results demonstrated the feasibility and efficiency of our proposed imageDWE to manage images and to process OLAP similarity queries. The results also demonstrated that the use of the proposed index technique guaranteed a great improvement in query processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

ScatterBlogs2: real-time monitoring of microblog messages through user-guided filtering.

PubMed

Bosch, Harald; Thom, Dennis; Heimerl, Florian; Püttmann, Edwin; Koch, Steffen; Krüger, Robert; Wörner, Michael; Ertl, Thomas

2013-12-01

The number of microblog posts published daily has reached a level that hampers the effective retrieval of relevant messages, and the amount of information conveyed through services such as Twitter is still increasing. Analysts require new methods for monitoring their topic of interest, dealing with the data volume and its dynamic nature. It is of particular importance to provide situational awareness for decision making in time-critical tasks. Current tools for monitoring microblogs typically filter messages based on user-defined keyword queries and metadata restrictions. Used on their own, such methods can have drawbacks with respect to filter accuracy and adaptability to changes in trends and topic structure. We suggest ScatterBlogs2, a new approach to let analysts build task-tailored message filters in an interactive and visual manner based on recorded messages of well-understood previous events. These message filters include supervised classification and query creation backed by the statistical distribution of terms and their co-occurrences. The created filter methods can be orchestrated and adapted afterwards for interactive, visual real-time monitoring and analysis of microblog feeds. We demonstrate the feasibility of our approach for analyzing the Twitter stream in emergency management scenarios.

Earth science big data at users' fingertips: the EarthServer Science Gateway Mobile

NASA Astrophysics Data System (ADS)

Barbera, Roberto; Bruno, Riccardo; Calanducci, Antonio; Fargetta, Marco; Pappalardo, Marco; Rundo, Francesco

2014-05-01

The EarthServer project (www.earthserver.eu), funded by the European Commission under its Seventh Framework Program, aims at establishing open access and ad-hoc analytics on extreme-size Earth Science data, based on and extending leading-edge Array Database technology. The core idea is to use database query languages as client/server interface to achieve barrier-free "mix & match" access to multi-source, any-size, multi-dimensional space-time data -- in short: "Big Earth Data Analytics" - based on the open standards of the Open Geospatial Consortium Web Coverage Processing Service (OGC WCPS) and the W3C XQuery. EarthServer combines both, thereby achieving a tight data/metadata integration. Further, the rasdaman Array Database System (www.rasdaman.com) is extended with further space-time coverage data types. On server side, highly effective optimizations - such as parallel and distributed query processing - ensure scalability to Exabyte volumes. In this contribution we will report on the EarthServer Science Gateway Mobile, an app for both iOS and Android-based devices that allows users to seamlessly access some of the EarthServer applications using SAML-based federated authentication and fine-grained authorisation mechanisms.

Using the Proteomics Identifications Database (PRIDE).

PubMed

Martens, Lennart; Jones, Phil; Côté, Richard

2008-03-01

The Proteomics Identifications Database (PRIDE) is a public data repository designed to store, disseminate, and analyze mass spectrometry based proteomics datasets. The PRIDE database can accommodate any level of detailed metadata about the submitted results, which can be queried, explored, viewed, or downloaded via the PRIDE Web interface. The PRIDE database also provides a simple, yet powerful, access control mechanism that fully supports confidential peer-reviewing of data related to a manuscript, ensuring that these results remain invisible to the general public while allowing referees and journal editors anonymized access to the data. This unit describes in detail the functionality that PRIDE provides with regards to searching, viewing, and comparing the available data, as well as different options for submitting data to PRIDE.

ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials

PubMed Central

2012-01-01

Clinical trials are mandatory protocols describing medical research on humans and among the most valuable sources of medical practice evidence. Searching for trials relevant to some query is laborious due to the immense number of existing protocols. Apart from search, writing new trials includes composing detailed eligibility criteria, which might be time-consuming, especially for new researchers. In this paper we present ASCOT, an efficient search application customised for clinical trials. ASCOT uses text mining and data mining methods to enrich clinical trials with metadata, that in turn serve as effective tools to narrow down search. In addition, ASCOT integrates a component for recommending eligibility criteria based on a set of selected protocols. PMID:22595088

ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials.

PubMed

Korkontzelos, Ioannis; Mu, Tingting; Ananiadou, Sophia

2012-04-30

Clinical trials are mandatory protocols describing medical research on humans and among the most valuable sources of medical practice evidence. Searching for trials relevant to some query is laborious due to the immense number of existing protocols. Apart from search, writing new trials includes composing detailed eligibility criteria, which might be time-consuming, especially for new researchers. In this paper we present ASCOT, an efficient search application customised for clinical trials. ASCOT uses text mining and data mining methods to enrich clinical trials with metadata, that in turn serve as effective tools to narrow down search. In addition, ASCOT integrates a component for recommending eligibility criteria based on a set of selected protocols.

Auspice: Automatic Service Planning in Cloud/Grid Environments

NASA Astrophysics Data System (ADS)

Chiu, David; Agrawal, Gagan

Recent scientific advances have fostered a mounting number of services and data sets available for utilization. These resources, though scattered across disparate locations, are often loosely coupled both semantically and operationally. This loosely coupled relationship implies the possibility of linking together operations and data sets to answer queries. This task, generally known as automatic service composition, therefore abstracts the process of complex scientific workflow planning from the user. We have been exploring a metadata-driven approach toward automatic service workflow composition, among other enabling mechanisms, in our system, Auspice: Automatic Service Planning in Cloud/Grid Environments. In this paper, we present a complete overview of our system's unique features and outlooks for future deployment as the Cloud computing paradigm becomes increasingly eminent in enabling scientific computing.

Noncredit Activities in Institutions of Higher Education, 1967-68, Institutional Distribution.

ERIC Educational Resources Information Center

Kemp, Florence B.

Of 2336 institutions of higher education queried on the distribution of noncredit activities in 1967-68, 1102 responded affirmatively. The bulk of this study is comprised of tables and charts based upon information received from these institutions. Highlights are summarized. A questionnaire, which is appended, was used to gather data. Some of the…

Data Management System for the National Energy-Water System (NEWS) Assessment Framework

NASA Astrophysics Data System (ADS)

Corsi, F.; Prousevitch, A.; Glidden, S.; Piasecki, M.; Celicourt, P.; Miara, A.; Fekete, B. M.; Vorosmarty, C. J.; Macknick, J.; Cohen, S. M.

2015-12-01

Aiming at providing a comprehensive assessment of the water-energy nexus, the National Energy-Water System (NEWS) project requires the integration of data to support a modeling framework that links climate, hydrological, power production, transmission, and economical models. Large amounts of Georeferenced data has to be streamed to the components of the inter-disciplinary model to explore future challenges and tradeoffs in the US power production, based on climate scenarios, power plant locations and technologies, available water resources, ecosystem sustainability, and economic demand. We used open source and in-house build software components to build a system that addresses two major data challenges: On-the-fly re-projection, re-gridding, interpolation, extrapolation, nodata patching, merging, temporal and spatial aggregation, of static and time series datasets in virtually any file formats and file structures, and any geographic extent for the models I/O, directly at run time; Comprehensive data management based on metadata cataloguing and discovery in repositories utilizing the MAGIC Table (Manipulation and Geographic Inquiry Control database). This innovative concept allows models to access data on-the-fly by data ID, irrespective of file path, file structure, file format and regardless its GIS specifications. In addition, a web-based information and computational system is being developed to control the I/O of spatially distributed Earth system, climate, and hydrological, power grid, and economical data flow within the NEWS framework. The system allows scenario building, data exploration, visualization, querying, and manipulation any loaded gridded, point, and vector polygon dataset. The system has demonstrated its potential for applications in other fields of Earth science modeling, education, and outreach. Over time, this implementation of the system will provide near real-time assessment of various current and future scenarios of the water-energy nexus.

Evaluating the Quality and Usability of Open Data for Public Health Research: A Systematic Review of Data Offerings on 3 Open Data Platforms.

PubMed

Martin, Erika G; Law, Jennie; Ran, Weijia; Helbig, Natalie; Birkhead, Guthrie S

Government datasets are newly available on open data platforms that are publicly accessible, available in nonproprietary formats, free of charge, and with unlimited use and distribution rights. They provide opportunities for health research, but their quality and usability are unknown. To describe available open health data, identify whether data are presented in a way that is aligned with best practices and usable for researchers, and examine differences across platforms. Two reviewers systematically reviewed a random sample of data offerings on NYC OpenData (New York City, all offerings, n = 37), Health Data NY (New York State, 25% sample, n = 71), and HealthData.gov (US Department of Health and Human Services, 5% sample, n = 75), using a standard coding guide. Three open health data platforms at the federal, New York State, and New York City levels. Data characteristics from the coding guide were aggregated into summary indices for intrinsic data quality, contextual data quality, adherence to the Dublin Core metadata standards, and the 5-star open data deployment scheme. One quarter of the offerings were structured datasets; other presentation styles included charts (14.7%), documents describing data (12.0%), maps (10.9%), and query tools (7.7%). Health Data NY had higher intrinsic data quality (P < .001), contextual data quality (P < .001), and Dublin Core metadata standards adherence (P < .001). All met basic "web availability" open data standards; fewer met higher standards of "hyperlinked to other data." Although all platforms need improvement, they already provide readily available data for health research. Sustained effort on improving open data websites and metadata is necessary for ensuring researchers use these data, thereby increasing their research value.

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.

MOPED 2.5—An Integrated Multi-Omics Resource: Multi-Omics Profiling Expression Database Now Includes Transcriptomics Data

PubMed Central

Montague, Elizabeth; Stanberry, Larissa; Higdon, Roger; Janko, Imre; Lee, Elaine; Anderson, Nathaniel; Choiniere, John; Stewart, Elizabeth; Yandl, Gregory; Broomall, William; Kolker, Natali

2014-01-01

Abstract Multi-omics data-driven scientific discovery crucially rests on high-throughput technologies and data sharing. Currently, data are scattered across single omics repositories, stored in varying raw and processed formats, and are often accompanied by limited or no metadata. The Multi-Omics Profiling Expression Database (MOPED, http://moped.proteinspire.org) version 2.5 is a freely accessible multi-omics expression database. Continual improvement and expansion of MOPED is driven by feedback from the Life Sciences Community. In order to meet the emergent need for an integrated multi-omics data resource, MOPED 2.5 now includes gene relative expression data in addition to protein absolute and relative expression data from over 250 large-scale experiments. To facilitate accurate integration of experiments and increase reproducibility, MOPED provides extensive metadata through the Data-Enabled Life Sciences Alliance (DELSA Global, http://delsaglobal.org) metadata checklist. MOPED 2.5 has greatly increased the number of proteomics absolute and relative expression records to over 500,000, in addition to adding more than four million transcriptomics relative expression records. MOPED has an intuitive user interface with tabs for querying different types of omics expression data and new tools for data visualization. Summary information including expression data, pathway mappings, and direct connection between proteins and genes can be viewed on Protein and Gene Details pages. These connections in MOPED provide a context for multi-omics expression data exploration. Researchers are encouraged to submit omics data which will be consistently processed into expression summaries. MOPED as a multi-omics data resource is a pivotal public database, interdisciplinary knowledge resource, and platform for multi-omics understanding. PMID:24910945

Software Application Profile: Opal and Mica: open-source software solutions for epidemiological data management, harmonization and dissemination.

PubMed

Doiron, Dany; Marcon, Yannick; Fortier, Isabel; Burton, Paul; Ferretti, Vincent

2017-10-01

Improving the dissemination of information on existing epidemiological studies and facilitating the interoperability of study databases are essential to maximizing the use of resources and accelerating improvements in health. To address this, Maelstrom Research proposes Opal and Mica, two inter-operable open-source software packages providing out-of-the-box solutions for epidemiological data management, harmonization and dissemination. Opal and Mica are two standalone but inter-operable web applications written in Java, JavaScript and PHP. They provide web services and modern user interfaces to access them. Opal allows users to import, manage, annotate and harmonize study data. Mica is used to build searchable web portals disseminating study and variable metadata. When used conjointly, Mica users can securely query and retrieve summary statistics on geographically dispersed Opal servers in real-time. Integration with the DataSHIELD approach allows conducting more complex federated analyses involving statistical models. Opal and Mica are open-source and freely available at [www.obiba.org] under a General Public License (GPL) version 3, and the metadata models and taxonomies that accompany them are available under a Creative Commons licence. © The Author 2017; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

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.

NASA's Global Change Master Directory: Discover and Access Earth Science Data Sets, Related Data Services, and Climate Diagnostics

NASA Astrophysics Data System (ADS)

Aleman, A.; Olsen, L. M.; Ritz, S.; Stevens, T.; Morahan, M.; Grebas, S. K.

2011-12-01

NASA's Global Change Master Directory provides the scientific community with the ability to discover, access, and use Earth science data, data-related services, and climate diagnostics worldwide.The GCMD offers descriptions of Earth science data sets using the Directory Interchange Format (DIF) metadata standard; Earth science related data services are described using the Service Entry Resource Format (SERF); and climate visualizations are described using the Climate Diagnostic (CD) standard. The DIF, SERF and CD standards each capture data attributes used to determine whether a data set, service, or climate visualization is relevant to a user's needs.Metadata fields include: title, summary, science keywords, service keywords, data center, data set citation, personnel, instrument, platform, quality, related URL, temporal and spatial coverage, data resolution and distribution information.In addition, nine valuable sets of controlled vocabularies have been developed to assist users in normalizing the search for data descriptions. An update to the GCMD's search functionality is planned to further capitalize on the controlled vocabularies during database queries.By implementing a dynamic keyword "tree", users will have the ability to search for data sets by combining keywords in new ways.This will allow users to conduct more relevant and efficient database searches to support the free exchange and re-use of Earth science data.

GIS tool for California state legislature electoral history

NASA Astrophysics Data System (ADS)

Artham, Swathi

The California State Legislature contains two bodies consisting of the lower house, the California State Assembly, with eighty members, and the upper house, the California State Senate, with forty members. Elections are held for every two years for both Senate and Assembly. The terms of the Senators are staggered so that half the membership is elected every two years, whereas all the Assembly members are elected every two years. The electoral district boundaries vary after every 10-year census. My main objective is to provide a summary of both California State Senate and California State Assembly election results in a single GIS tool, from the years 1970 to 2012. This tool provides information about different trends in the California State Senate and State Assembly elections along the years. This tool was designed to help students, and teachers to interactively learn about the California State Legislature elections. Users can view the election results by selecting a particular year for Senate or Assembly, which results in adding a new layer on the map with a coloring scheme for better understanding of change of parties; red for Republicans, blue for Democrats and green for Independents. Users can click on any district shown on the map using a hotlink tool to see the electoral trends for the districts for the past years. This application provides a powerful Stored Query Language (SQL) query option to enter queries and get election results in the form of tables with various fields. This data can be further used to aid other analysis as per user requirements. This tool also provides various visual statistics using graphs and tables for voter turnout, number of candidates won by each party, number of seats changed from one party to another. It also features a color matrix table that helps users to see trends in California State Senate and Assembly. Every two-year election results are shown in the form of graphs and tables for better understanding by the user. The tool provides two quiz options for users who are willing to test the knowledge they gained using the tool. This tool was developed in JAVA swing and AWT, Map Objects Java Objects (MOJO), Apache Derby, DBF Explorer, HTML5, CSS3 and JavaScript.

Virtual Observatory Interfaces to the Chandra Data Archive

NASA Astrophysics Data System (ADS)

Tibbetts, M.; Harbo, P.; Van Stone, D.; Zografou, P.

2014-05-01

The Chandra Data Archive (CDA) plays a central role in the operation of the Chandra X-ray Center (CXC) by providing access to Chandra data. Proprietary interfaces have been the backbone of the CDA throughout the Chandra mission. While these interfaces continue to provide the depth and breadth of mission specific access Chandra users expect, the CXC has been adding Virtual Observatory (VO) interfaces to the Chandra proposal catalog and observation catalog. VO interfaces provide standards-based access to Chandra data through simple positional queries or more complex queries using the Astronomical Data Query Language. Recent development at the CDA has generalized our existing VO services to create a suite of services that can be configured to provide VO interfaces to any dataset. This approach uses a thin web service layer for the individual VO interfaces, a middle-tier query component which is shared among the VO interfaces for parsing, scheduling, and executing queries, and existing web services for file and data access. The CXC VO services provide Simple Cone Search (SCS), Simple Image Access (SIA), and Table Access Protocol (TAP) implementations for both the Chandra proposal and observation catalogs within the existing archive architecture. Our work with the Chandra proposal and observation catalogs, as well as additional datasets beyond the CDA, illustrates how we can provide configurable VO services to extend core archive functionality.

Data Sharing in DHT Based P2P Systems

NASA Astrophysics Data System (ADS)

Roncancio, Claudia; Del Pilar Villamil, María; Labbé, Cyril; Serrano-Alvarado, Patricia

The evolution of peer-to-peer (P2P) systems triggered the building of large scale distributed applications. The main application domain is data sharing across a very large number of highly autonomous participants. Building such data sharing systems is particularly challenging because of the “extreme” characteristics of P2P infrastructures: massive distribution, high churn rate, no global control, potentially untrusted participants... This article focuses on declarative querying support, query optimization and data privacy on a major class of P2P systems, that based on Distributed Hash Table (P2P DHT). The usual approaches and the algorithms used by classic distributed systems and databases for providing data privacy and querying services are not well suited to P2P DHT systems. A considerable amount of work was required to adapt them for the new challenges such systems present. This paper describes the most important solutions found. It also identifies important future research trends in data management in P2P DHT systems.

UCSC genome browser: deep support for molecular biomedical research.

PubMed

Mangan, Mary E; Williams, Jennifer M; Lathe, Scott M; Karolchik, Donna; Lathe, Warren C

2008-01-01

The volume and complexity of genomic sequence data, and the additional experimental data required for annotation of the genomic context, pose a major challenge for display and access for biomedical researchers. Genome browsers organize this data and make it available in various ways to extract useful information to advance research projects. The UCSC Genome Browser is one of these resources. The official sequence data for a given species forms the framework to display many other types of data such as expression, variation, cross-species comparisons, and more. Visual representations of the data are available for exploration. Data can be queried with sequences. Complex database queries are also easily achieved with the Table Browser interface. Associated tools permit additional query types or access to additional data sources such as images of in situ localizations. Support for solving researcher's issues is provided with active discussion mailing lists and by providing updated training materials. The UCSC Genome Browser provides a source of deep support for a wide range of biomedical molecular research (http://genome.ucsc.edu).

Legacy2Drupal - Conversion of an existing oceanographic relational database to a semantically enabled Drupal content management system

NASA Astrophysics Data System (ADS)

Maffei, A. R.; Chandler, C. L.; Work, T.; Allen, J.; Groman, R. C.; Fox, P. A.

2009-12-01

Content Management Systems (CMSs) provide powerful features that can be of use to oceanographic (and other geo-science) data managers. However, in many instances, geo-science data management offices have previously designed customized schemas for their metadata. The WHOI Ocean Informatics initiative and the NSF funded Biological Chemical and Biological Data Management Office (BCO-DMO) have jointly sponsored a project to port an existing, relational database containing oceanographic metadata, along with an existing interface coded in Cold Fusion middleware, to a Drupal6 Content Management System. The goal was to translate all the existing database tables, input forms, website reports, and other features present in the existing system to employ Drupal CMS features. The replacement features include Drupal content types, CCK node-reference fields, themes, RDB, SPARQL, workflow, and a number of other supporting modules. Strategic use of some Drupal6 CMS features enables three separate but complementary interfaces that provide access to oceanographic research metadata via the MySQL database: 1) a Drupal6-powered front-end; 2) a standard SQL port (used to provide a Mapserver interface to the metadata and data; and 3) a SPARQL port (feeding a new faceted search capability being developed). Future plans include the creation of science ontologies, by scientist/technologist teams, that will drive semantically-enabled faceted search capabilities planned for the site. Incorporation of semantic technologies included in the future Drupal 7 core release is also anticipated. Using a public domain CMS as opposed to proprietary middleware, and taking advantage of the many features of Drupal 6 that are designed to support semantically-enabled interfaces will help prepare the BCO-DMO database for interoperability with other ecosystem databases.

Providing Web Interfaces to the NSF EarthScope USArray Transportable Array

NASA Astrophysics Data System (ADS)

Vernon, Frank; Newman, Robert; Lindquist, Kent

2010-05-01

Since April 2004 the EarthScope USArray seismic network has grown to over 850 broadband stations that stream multi-channel data in near real-time to the Array Network Facility in San Diego. Providing secure, yet open, access to real-time and archived data for a broad range of audiences is best served by a series of platform agnostic low-latency web-based applications. We present a framework of tools that mediate between the world wide web and Boulder Real Time Technologies Antelope Environmental Monitoring System data acquisition and archival software. These tools provide comprehensive information to audiences ranging from network operators and geoscience researchers, to funding agencies and the general public. This ranges from network-wide to station-specific metadata, state-of-health metrics, event detection rates, archival data and dynamic report generation over a station's two year life span. Leveraging open source web-site development frameworks for both the server side (Perl, Python and PHP) and client-side (Flickr, Google Maps/Earth and jQuery) facilitates the development of a robust extensible architecture that can be tailored on a per-user basis, with rapid prototyping and development that adheres to web-standards. Typical seismic data warehouses allow online users to query and download data collected from regional networks, without the scientist directly visually assessing data coverage and/or quality. Using a suite of web-based protocols, we have recently developed an online seismic waveform interface that directly queries and displays data from a relational database through a web-browser. Using the Python interface to Datascope and the Python-based Twisted network package on the server side, and the jQuery Javascript framework on the client side to send and receive asynchronous waveform queries, we display broadband seismic data using the HTML Canvas element that is globally accessible by anyone using a modern web-browser. We are currently creating additional interface tools to create a rich-client interface for accessing and displaying seismic data that can be deployed to any system running the Antelope Real Time System. The software is freely available from the Antelope contributed code Git repository (http://www.antelopeusersgroup.org).

A Semantically Enabled Metadata Repository for Solar Irradiance Data Products

NASA Astrophysics Data System (ADS)

Wilson, A.; Cox, M.; Lindholm, D. M.; Nadiadi, I.; Traver, T.

2014-12-01

The Laboratory for Atmospheric and Space Physics, LASP, has been conducting research in Atmospheric and Space science for over 60 years, and providing the associated data products to the public. LASP has a long history, in particular, of making space-based measurements of the solar irradiance, which serves as crucial input to several areas of scientific research, including solar-terrestrial interactions, atmospheric, and climate. LISIRD, the LASP Interactive Solar Irradiance Data Center, serves these datasets to the public, including solar spectral irradiance (SSI) and total solar irradiance (TSI) data. The LASP extended metadata repository, LEMR, is a database of information about the datasets served by LASP, such as parameters, uncertainties, temporal and spectral ranges, current version, alerts, etc. It serves as the definitive, single source of truth for that information. The database is populated with information garnered via web forms and automated processes. Dataset owners keep the information current and verified for datasets under their purview. This information can be pulled dynamically for many purposes. Web sites such as LISIRD can include this information in web page content as it is rendered, ensuring users get current, accurate information. It can also be pulled to create metadata records in various metadata formats, such as SPASE (for heliophysics) and ISO 19115. Once these records are be made available to the appropriate registries, our data will be discoverable by users coming in via those organizations. The database is implemented as a RDF triplestore, a collection of instances of subject-object-predicate data entities identifiable with a URI. This capability coupled with SPARQL over HTTP read access enables semantic queries over the repository contents. To create the repository we leveraged VIVO, an open source semantic web application, to manage and create new ontologies and populate repository content. A variety of ontologies were used in creating the triplestore, including ontologies that came with VIVO such as FOAF. Also, the W3C DCAT ontology was integrated and extended to describe properties of our data products that we needed to capture, such as spectral range. The presentation will describe the architecture, ontology issues, and tools used to create LEMR and plans for its evolution.

Case retrieval in medical databases by fusing heterogeneous information.

PubMed

Quellec, Gwénolé; Lamard, Mathieu; Cazuguel, Guy; Roux, Christian; Cochener, Béatrice

2011-01-01

A novel content-based heterogeneous information retrieval framework, particularly well suited to browse medical databases and support new generation computer aided diagnosis (CADx) systems, is presented in this paper. It was designed to retrieve possibly incomplete documents, consisting of several images and semantic information, from a database; more complex data types such as videos can also be included in the framework. The proposed retrieval method relies on image processing, in order to characterize each individual image in a document by their digital content, and information fusion. Once the available images in a query document are characterized, a degree of match, between the query document and each reference document stored in the database, is defined for each attribute (an image feature or a metadata). A Bayesian network is used to recover missing information if need be. Finally, two novel information fusion methods are proposed to combine these degrees of match, in order to rank the reference documents by decreasing relevance for the query. In the first method, the degrees of match are fused by the Bayesian network itself. In the second method, they are fused by the Dezert-Smarandache theory: the second approach lets us model our confidence in each source of information (i.e., each attribute) and take it into account in the fusion process for a better retrieval performance. The proposed methods were applied to two heterogeneous medical databases, a diabetic retinopathy database and a mammography screening database, for computer aided diagnosis. Precisions at five of 0.809 ± 0.158 and 0.821 ± 0.177, respectively, were obtained for these two databases, which is very promising.

Legacy2Drupal: Conversion of an existing relational oceanographic database to a Drupal 7 CMS

NASA Astrophysics Data System (ADS)

Work, T. T.; Maffei, A. R.; Chandler, C. L.; Groman, R. C.

2011-12-01

Content Management Systems (CMSs) such as Drupal provide powerful features that can be of use to oceanographic (and other geo-science) data managers. However, in many instances, geo-science data management offices have already designed and implemented customized schemas for their metadata. The NSF funded Biological Chemical and Biological Data Management Office (BCO-DMO) has ported an existing relational database containing oceanographic metadata, along with an existing interface coded in Cold Fusion middleware, to a Drupal 7 Content Management System. This is an update on an effort described as a proof-of-concept in poster IN21B-1051, presented at AGU2009. The BCO-DMO project has translated all the existing database tables, input forms, website reports, and other features present in the existing system into Drupal CMS features. The replacement features are made possible by the use of Drupal content types, CCK node-reference fields, a custom theme, and a number of other supporting modules. This presentation describes the process used to migrate content in the original BCO-DMO metadata database to Drupal 7, some problems encountered during migration, and the modules used to migrate the content successfully. Strategic use of Drupal 7 CMS features that enable three separate but complementary interfaces to provide access to oceanographic research metadata will also be covered: 1) a Drupal 7-powered user front-end; 2) REST-ful JSON web services (providing a Mapserver interface to the metadata and data; and 3) a SPARQL interface to a semantic representation of the repository metadata (this feeding a new faceted search capability currently under development). The existing BCO-DMO ontology, developed in collaboration with Rensselaer Polytechnic Institute's Tetherless World Constellation, makes strategic use of pre-existing ontologies and will be used to drive semantically-enabled faceted search capabilities planned for the site. At this point, the use of semantic technologies included in the Drupal 7 core is anticipated. Using a public domain CMS as opposed to proprietary middleware, and taking advantage of the many features of Drupal 7 that are designed to support semantically-enabled interfaces will help prepare the BCO-DMO and other science data repositories for interoperability between systems that serve ecosystem research data.

The Database Query Support Processor (QSP)

NASA Technical Reports Server (NTRS)

1993-01-01

The number and diversity of databases available to users continues to increase dramatically. Currently, the trend is towards decentralized, client server architectures that (on the surface) are less expensive to acquire, operate, and maintain than information architectures based on centralized, monolithic mainframes. The database query support processor (QSP) effort evaluates the performance of a network level, heterogeneous database access capability. Air Force Material Command's Rome Laboratory has developed an approach, based on ANSI standard X3.138 - 1988, 'The Information Resource Dictionary System (IRDS)' to seamless access to heterogeneous databases based on extensions to data dictionary technology. To successfully query a decentralized information system, users must know what data are available from which source, or have the knowledge and system privileges necessary to find out this information. Privacy and security considerations prohibit free and open access to every information system in every network. Even in completely open systems, time required to locate relevant data (in systems of any appreciable size) would be better spent analyzing the data, assuming the original question was not forgotten. Extensions to data dictionary technology have the potential to more fully automate the search and retrieval for relevant data in a decentralized environment. Substantial amounts of time and money could be saved by not having to teach users what data resides in which systems and how to access each of those systems. Information describing data and how to get it could be removed from the application and placed in a dedicated repository where it belongs. The result simplified applications that are less brittle and less expensive to build and maintain. Software technology providing the required functionality is off the shelf. The key difficulty is in defining the metadata required to support the process. The database query support processor effort will provide quantitative data on the amount of effort required to implement an extended data dictionary at the network level, add new systems, adapt to changing user needs, and provide sound estimates on operations and maintenance costs and savings.

TCW: Transcriptome Computational Workbench

PubMed Central

Soderlund, Carol; Nelson, William; Willer, Mark; Gang, David R.

2013-01-01

Background The analysis of transcriptome data involves many steps and various programs, along with organization of large amounts of data and results. Without a methodical approach for storage, analysis and query, the resulting ad hoc analysis can lead to human error, loss of data and results, inefficient use of time, and lack of verifiability, repeatability, and extensibility. Methodology The Transcriptome Computational Workbench (TCW) provides Java graphical interfaces for methodical analysis for both single and comparative transcriptome data without the use of a reference genome (e.g. for non-model organisms). The singleTCW interface steps the user through importing transcript sequences (e.g. Illumina) or assembling long sequences (e.g. Sanger, 454, transcripts), annotating the sequences, and performing differential expression analysis using published statistical programs in R. The data, metadata, and results are stored in a MySQL database. The multiTCW interface builds a comparison database by importing sequence and annotation from one or more single TCW databases, executes the ESTscan program to translate the sequences into proteins, and then incorporates one or more clusterings, where the clustering options are to execute the orthoMCL program, compute transitive closure, or import clusters. Both singleTCW and multiTCW allow extensive query and display of the results, where singleTCW displays the alignment of annotation hits to transcript sequences, and multiTCW displays multiple transcript alignments with MUSCLE or pairwise alignments. The query programs can be executed on the desktop for fastest analysis, or from the web for sharing the results. Conclusion It is now affordable to buy a multi-processor machine, and easy to install Java and MySQL. By simply downloading the TCW, the user can interactively analyze, query and view their data. The TCW allows in-depth data mining of the results, which can lead to a better understanding of the transcriptome. TCW is freely available from www.agcol.arizona.edu/software/tcw. PMID:23874959

TCW: transcriptome computational workbench.

PubMed

Soderlund, Carol; Nelson, William; Willer, Mark; Gang, David R

2013-01-01

The analysis of transcriptome data involves many steps and various programs, along with organization of large amounts of data and results. Without a methodical approach for storage, analysis and query, the resulting ad hoc analysis can lead to human error, loss of data and results, inefficient use of time, and lack of verifiability, repeatability, and extensibility. The Transcriptome Computational Workbench (TCW) provides Java graphical interfaces for methodical analysis for both single and comparative transcriptome data without the use of a reference genome (e.g. for non-model organisms). The singleTCW interface steps the user through importing transcript sequences (e.g. Illumina) or assembling long sequences (e.g. Sanger, 454, transcripts), annotating the sequences, and performing differential expression analysis using published statistical programs in R. The data, metadata, and results are stored in a MySQL database. The multiTCW interface builds a comparison database by importing sequence and annotation from one or more single TCW databases, executes the ESTscan program to translate the sequences into proteins, and then incorporates one or more clusterings, where the clustering options are to execute the orthoMCL program, compute transitive closure, or import clusters. Both singleTCW and multiTCW allow extensive query and display of the results, where singleTCW displays the alignment of annotation hits to transcript sequences, and multiTCW displays multiple transcript alignments with MUSCLE or pairwise alignments. The query programs can be executed on the desktop for fastest analysis, or from the web for sharing the results. It is now affordable to buy a multi-processor machine, and easy to install Java and MySQL. By simply downloading the TCW, the user can interactively analyze, query and view their data. The TCW allows in-depth data mining of the results, which can lead to a better understanding of the transcriptome. TCW is freely available from www.agcol.arizona.edu/software/tcw.

Automatic meta-data collection of STP observation data

NASA Astrophysics Data System (ADS)

Ishikura, S.; Kimura, E.; Murata, K.; Kubo, T.; Shinohara, I.

2006-12-01

For the geo-science and the STP (Solar-Terrestrial Physics) studies, various observations have been done by satellites and ground-based observatories up to now. These data are saved and managed at many organizations, but no common procedure and rule to provide and/or share these data files. Researchers have felt difficulty in searching and analyzing such different types of data distributed over the Internet. To support such cross-over analyses of observation data, we have developed the STARS (Solar-Terrestrial data Analysis and Reference System). The STARS consists of client application (STARS-app), the meta-database (STARS- DB), the portal Web service (STARS-WS) and the download agent Web service (STARS DLAgent-WS). The STARS-DB includes directory information, access permission, protocol information to retrieve data files, hierarchy information of mission/team/data and user information. Users of the STARS are able to download observation data files without knowing locations of the files by using the STARS-DB. We have implemented the Portal-WS to retrieve meta-data from the meta-database. One reason we use the Web service is to overcome a variety of firewall restrictions which is getting stricter in recent years. Now it is difficult for the STARS client application to access to the STARS-DB by sending SQL query to obtain meta- data from the STARS-DB. Using the Web service, we succeeded in placing the STARS-DB behind the Portal- WS and prevent from exposing it on the Internet. The STARS accesses to the Portal-WS by sending the SOAP (Simple Object Access Protocol) request over HTTP. Meta-data is received as a SOAP Response. The STARS DLAgent-WS provides clients with data files downloaded from data sites. The data files are provided with a variety of protocols (e.g., FTP, HTTP, FTPS and SFTP). These protocols are individually selected at each site. The clients send a SOAP request with download request messages and receive observation data files as a SOAP Response with DIME-Attachment. By introducing the DLAgent-WS, we overcame the problem that the data management policies of each data site are independent. Another important issue to be overcome is how to collect the meta-data of observation data files. So far, STARS-DB managers have added new records to the meta-database and updated them manually. We have had a lot of troubles to maintain the meta-database because observation data are generated every day and the quantity of data files increases explosively. For that purpose, we have attempted to automate collection of the meta-data. In this research, we adopted the RSS 1.0 (RDF Site Summary) as a format to exchange meta-data in the STP fields. The RSS is an RDF vocabulary that provides a multipurpose extensible meta-data description and is suitable for syndication of meta-data. Most of the data in the present study are described in the CDF (Common Data Format), which is a self- describing data format. We have converted meta-information extracted from the CDF data files into RSS files. The program to generate the RSS files is executed on data site server once a day and the RSS files provide information of new data files. The RSS files are collected by RSS collection server once a day and the meta- data are stored in the STARS-DB.

The Chandra Source Catalog: Storage and Interfaces

NASA Astrophysics Data System (ADS)

van Stone, David; Harbo, Peter N.; Tibbetts, Michael S.; Zografou, Panagoula; Evans, Ian N.; Primini, Francis A.; Glotfelty, Kenny J.; Anderson, Craig S.; Bonaventura, Nina R.; Chen, Judy C.; Davis, John E.; Doe, Stephen M.; Evans, Janet D.; Fabbiano, Giuseppina; Galle, Elizabeth C.; Gibbs, Danny G., II; Grier, John D.; Hain, Roger; Hall, Diane M.; He, Xiang Qun (Helen); Houck, John C.; Karovska, Margarita; Kashyap, Vinay L.; Lauer, Jennifer; McCollough, Michael L.; McDowell, Jonathan C.; Miller, Joseph B.; Mitschang, Arik W.; Morgan, Douglas L.; Mossman, Amy E.; Nichols, Joy S.; Nowak, Michael A.; Plummer, David A.; Refsdal, Brian L.; Rots, Arnold H.; Siemiginowska, Aneta L.; Sundheim, Beth A.; Winkelman, Sherry L.

2009-09-01

The Chandra Source Catalog (CSC) is part of the Chandra Data Archive (CDA) at the Chandra X-ray Center. The catalog contains source properties and associated data objects such as images, spectra, and lightcurves. The source properties are stored in relational databases and the data objects are stored in files with their metadata stored in databases. The CDA supports different versions of the catalog: multiple fixed release versions and a live database version. There are several interfaces to the catalog: CSCview, a graphical interface for building and submitting queries and for retrieving data objects; a command-line interface for property and source searches using ADQL; and VO-compliant services discoverable though the VO registry. This poster describes the structure of the catalog and provides an overview of the interfaces.

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.

A data and information system for processing, archival, and distribution of data for global change research

NASA Technical Reports Server (NTRS)

Graves, Sara J.

1994-01-01

Work on this project was focused on information management techniques for Marshall Space Flight Center's EOSDIS Version 0 Distributed Active Archive Center (DAAC). The centerpiece of this effort has been participation in EOSDIS catalog interoperability research, the result of which is a distributed Information Management System (IMS) allowing the user to query the inventories of all the DAAC's from a single user interface. UAH has provided the MSFC DAAC database server for the distributed IMS, and has contributed to definition and development of the browse image display capabilities in the system's user interface. Another important area of research has been in generating value-based metadata through data mining. In addition, information management applications for local inventory and archive management, and for tracking data orders were provided.

cyvcf2: fast, flexible variant analysis with Python.

PubMed

Pedersen, Brent S; Quinlan, Aaron R

2017-06-15

Variant call format (VCF) files document the genetic variation observed after DNA sequencing, alignment and variant calling of a sample cohort. Given the complexity of the VCF format as well as the diverse variant annotations and genotype metadata, there is a need for fast, flexible methods enabling intuitive analysis of the variant data within VCF and BCF files. We introduce cyvcf2 , a Python library and software package for fast parsing and querying of VCF and BCF files and illustrate its speed, simplicity and utility. bpederse@gmail.com or aaronquinlan@gmail.com. cyvcf2 is available from https://github.com/brentp/cyvcf2 under the MIT license and from common python package managers. Detailed documentation is available at http://brentp.github.io/cyvcf2/. © The Author 2017. Published by Oxford University Press.

Bridging the gap between Hydrologic and Atmospheric communities through a standard based framework

NASA Astrophysics Data System (ADS)

Boldrini, E.; Salas, F.; Maidment, D. R.; Mazzetti, P.; Santoro, M.; Nativi, S.; Domenico, B.

2012-04-01

Data interoperability in the study of Earth sciences is essential to performing interdisciplinary multi-scale multi-dimensional analyses (e.g. hydrologic impacts of global warming, regional urbanization, global population growth etc.). This research aims to bridge the existing gap between hydrologic and atmospheric communities both at semantic and technological levels. Within the context of hydrology, scientists are usually concerned with data organized as time series: a time series can be seen as a variable measured at a particular point in space over a period of time (e.g. the stream flow values as periodically measured by a buoy sensor in a river); atmospheric scientists instead usually organize their data as coverages: a coverage can be seen as a multidimensional data array (e.g. satellite images acquired through time). These differences make non-trivial the set up of a common framework to perform data discovery and access. A set of web services specifications and implementations is already in place in both the scientific communities to allow data discovery and access in the different domains. The CUAHSI-Hydrologic Information System (HIS) service stack lists different services types and implementations: - a metacatalog (implemented as a CSW) used to discover metadata services by distributing the query to a set of catalogs - time series catalogs (implemented as CSW) used to discover datasets published by the feature services - feature services (implemented as WFS) containing features with data access link - sensor observation services (implemented as SOS) enabling access to the stream of acquisitions Within the Unidata framework, there lies a similar service stack for atmospheric data: - the broker service (implemented as a CSW) distributes a user query to a set of heterogeneous services (i.e. catalogs services, but also inventory and access services) - the catalog service (implemented as a CSW) is able to harvest the available metadata offered by THREDDS services, and executes complex queries against the available metadata. - inventory service (implemented as a THREDDS) being able to hierarchically organize and publish a local collection of multi-dimensional arrays (e.g. NetCDF, GRIB files), as well as publish auxiliary standard services to realize the actual data access and visualization (e.g. WCS, OPeNDAP, WMS). The approach followed in this research is to build on top of the existing standards and implementations, by setting up a standard-aware interoperable framework, able to deal with the existing heterogeneity in an organic way. As a methodology, interoperability tests against real services were performed; existing problems were thus highlighted and possibly solved. The use of flexible tools, able to deal in a smart way with heterogeneity has proven to be successful, in particular experiments were carried on with both GI-cat broker and ESRI GeoPortal frameworks. GI-cat discovery broker was proven successful at implementing the CSW interface, as well as federating heterogeneous resources, such as THREDDS and WCS services published by Unidata, HydroServer, WFS and SOS services published by CUAHSI. Experiments with ESRI GeoPortal were also successful: the GeoPortal was used to deploy a web interface able to distribute searches amongst catalog implementations from both the hydrologic and the atmospheric communities, including HydroServers and GI-cat, combining results from both the domains in a seamless way.

Clustered Numerical Data Analysis Using Markov Lie Monoid Based Networks

NASA Astrophysics Data System (ADS)

Johnson, Joseph

2016-03-01

We have designed and build an optimal numerical standardization algorithm that links numerical values with their associated units, error level, and defining metadata thus supporting automated data exchange and new levels of artificial intelligence (AI). The software manages all dimensional and error analysis and computational tracing. Tables of entities verses properties of these generalized numbers (called ``metanumbers'') support a transformation of each table into a network among the entities and another network among their properties where the network connection matrix is based upon a proximity metric between the two items. We previously proved that every network is isomorphic to the Lie algebra that generates continuous Markov transformations. We have also shown that the eigenvectors of these Markov matrices provide an agnostic clustering of the underlying patterns. We will present this methodology and show how our new work on conversion of scientific numerical data through this process can reveal underlying information clusters ordered by the eigenvalues. We will also show how the linking of clusters from different tables can be used to form a ``supernet'' of all numerical information supporting new initiatives in AI.

The NASA Navigator Program Ground Based Archives at the Michelson Science Center: Supporting the Search for Habitable Planets

NASA Astrophysics Data System (ADS)

Berriman, G. B.; Ciardi, D. R.; Good, J. C.; Laity, A. C.; Zhang, A.

2006-07-01

At ADASS XIV, we described how the W. M. Keck Observatory Archive (KOA) re-uses and extends the component based architecture of the NASA/IPAC Infrared Science Archive (IRSA) to ingest and serve level 0 observations made with HIRES, the High Resolution Echelle Spectrometer. Since August 18, the KOA has ingested 325 GB of data from 135 nights of observations. The architecture exploits a service layer between the mass storage layer and the user interface. This service layer consists of standalone utilities called through a simple executive that perform generic query and retrieval functions, such as query generation, database table sub-setting, and return page generation etc. It has been extended to implement proprietary access to data through deployment of query management middleware developed for the National Virtual Observatory. The MSC archives have recently extended this design to query and retrieve complex data sets describing the properties of potential target stars for the Terrestrial Planet Finder (TPF) missions. The archives can now support knowledge based retrieval, as well as data retrieval. This paper describes how extensions to the IRSA architecture, which is applicable across all wavelengths and astronomical datatypes, supports the design and development of the MSC NP archives at modest cost.

Experimental Evaluation of Concepts for Miqsture; An Online Interactive Language for Tactical Intelligence Processing

DTIC Science & Technology

1979-12-10

Review Collection Plan File. L... _.. Table 20 (Item 18) Items 76 17, and’ 78 compared three different METHODS for recording the outcomes of a task...3-1 3.2 Background ........ n. .... .............. ...... 3-1 3.3 Method Summary...aspects of descriptions of selected tasks from Army tactical Intelli- gence processing. The results provided indications of what query methods have

CINERGI: Community Inventory of EarthCube Resources for Geoscience Interoperability

NASA Astrophysics Data System (ADS)

Zaslavsky, Ilya; Bermudez, Luis; Grethe, Jeffrey; Gupta, Amarnath; Hsu, Leslie; Lehnert, Kerstin; Malik, Tanu; Richard, Stephen; Valentine, David; Whitenack, Thomas

2014-05-01

Organizing geoscience data resources to support cross-disciplinary data discovery, interpretation, analysis and integration is challenging because of different information models, semantic frameworks, metadata profiles, catalogs, and services used in different geoscience domains, not to mention different research paradigms and methodologies. The central goal of CINERGI, a new project supported by the US National Science Foundation through its EarthCube Building Blocks program, is to create a methodology and assemble a large inventory of high-quality information resources capable of supporting data discovery needs of researchers in a wide range of geoscience domains. The key characteristics of the inventory are: 1) collaboration with and integration of metadata resources from a number of large data facilities; 2) reliance on international metadata and catalog service standards; 3) assessment of resource "interoperability-readiness"; 4) ability to cross-link and navigate data resources, projects, models, researcher directories, publications, usage information, etc.; 5) efficient inclusion of "long-tail" data, which are not appearing in existing domain repositories; 6) data registration at feature level where appropriate, in addition to common dataset-level registration, and 7) integration with parallel EarthCube efforts, in particular focused on EarthCube governance, information brokering, service-oriented architecture design and management of semantic information. We discuss challenges associated with accomplishing CINERGI goals, including defining the inventory scope; managing different granularity levels of resource registration; interaction with search systems of domain repositories; explicating domain semantics; metadata brokering, harvesting and pruning; managing provenance of the harvested metadata; and cross-linking resources based on the linked open data (LOD) approaches. At the higher level of the inventory, we register domain-wide resources such as domain catalogs, vocabularies, information models, data service specifications, identifier systems, and assess their conformance with international standards (such as those adopted by ISO and OGC, and used by INSPIRE) or de facto community standards using, in part, automatic validation techniques. The main level in CINERGI leverages a metadata aggregation platform (currently Geoportal Server) to organize harvested resources from multiple collections and contributed by community members during EarthCube end-user domain workshops or suggested online. The latter mechanism uses the SciCrunch toolkit originally developed within the Neuroscience Information Framework (NIF) project and now being extended to other communities. The inventory is designed to support requests such as "Find resources with theme X in geographic area S", "Find datasets with subject Y using query concept expansion", "Find geographic regions having data of type Z", "Find datasets that contain property P". With the added LOD support, additional types of requests, such as "Find example implementations of specification X", "Find researchers who have worked in Domain X, dataset Y, location L", "Find resources annotated by person X", will be supported. Project's website (http://workspace.earthcube.org/cinergi) provides access to the initial resource inventory, a gallery of EarthCube researchers, collections of geoscience models, metadata entry forms, and other software modules and inventories being integrated into the CINERGI system. Support from the US National Science Foundation under award NSF ICER-1343816 is gratefully acknowledged.

Providing interoperability of eHealth communities through peer-to-peer networks.

PubMed

Kilic, Ozgur; Dogac, Asuman; Eichelberg, Marco

2010-05-01

Providing an interoperability infrastructure for Electronic Healthcare Records (EHRs) is on the agenda of many national and regional eHealth initiatives. Two important integration profiles have been specified for this purpose, namely, the "Integrating the Healthcare Enterprise (IHE) Cross-enterprise Document Sharing (XDS)" and the "IHE Cross Community Access (XCA)." IHE XDS describes how to share EHRs in a community of healthcare enterprises and IHE XCA describes how EHRs are shared across communities. However, the current version of the IHE XCA integration profile does not address some of the important challenges of cross-community exchange environments. The first challenge is scalability. If every community that joins the network needs to connect to every other community, i.e., a pure peer-to-peer network, this solution will not scale. Furthermore, each community may use a different coding vocabulary for the same metadata attribute, in which case, the target community cannot interpret the query involving such an attribute. Yet another important challenge is that each community may (and typically will) have a different patient identifier domain. Querying for the patient identifiers in the target community using patient demographic data may create patient privacy concerns. In this paper, we address each of these challenges and show how they can be handled effectively in a superpeer-based peer-to-peer architecture.

Spiders and Camels and Sybase! Oh, My!

NASA Astrophysics Data System (ADS)

Barg, Irene; Ferro, Anthony J.; Stobie, Elizabeth

The Hubble Space Telescope NICMOS Guaranteed Time Observers (GTOs) requested a means of sharing point spread function (PSF) observations. Because of the specifics of the instrument, these PSFs are very useful in the analysis of observations and can vary with the conditions on the telescope. The GTOs are geographically diverse, so a centralized processing solution would not work. The individual PSF observations were reduced by different people, at different institutions, using different reduction software. These varied observations had to be combined into a single database and linked to other information as well. The NICMOS software group at the University of Arizona developed a solution based on a World Wide Web (WWW) interface, using Perl/CGI forms to query the submitter about the PSF data to be entered. After some semi-automated sanity checks, using the FTOOLS package, the metadata are then entered into a Sybase relational database system. A user of the system can then query the database, again through a WWW interface, to locate and retrieve PSFs which may match their observations, as well as determine other information regarding the telescope conditions at the time of the observations (e.g., the breathing parameter). This presentation discusses some of the driving forces in the design, problems encountered, and the choices made. The tools used, including Sybase, Perl, FTOOLS, and WWW elements are also discussed.

Real-time high-level video understanding using data warehouse

NASA Astrophysics Data System (ADS)

Lienard, Bruno; Desurmont, Xavier; Barrie, Bertrand; Delaigle, Jean-Francois

2006-02-01

High-level Video content analysis such as video-surveillance is often limited by computational aspects of automatic image understanding, i.e. it requires huge computing resources for reasoning processes like categorization and huge amount of data to represent knowledge of objects, scenarios and other models. This article explains how to design and develop a "near real-time adaptive image datamart", used, as a decisional support system for vision algorithms, and then as a mass storage system. Using RDF specification as storing format of vision algorithms meta-data, we can optimise the data warehouse concepts for video analysis, add some processes able to adapt the current model and pre-process data to speed-up queries. In this way, when new data is sent from a sensor to the data warehouse for long term storage, using remote procedure call embedded in object-oriented interfaces to simplified queries, they are processed and in memory data-model is updated. After some processing, possible interpretations of this data can be returned back to the sensor. To demonstrate this new approach, we will present typical scenarios applied to this architecture such as people tracking and events detection in a multi-camera network. Finally we will show how this system becomes a high-semantic data container for external data-mining.

Web Content Management Systems: An Analysis of Forensic Investigatory Challenges.

PubMed

Horsman, Graeme

2018-02-26

With an increase in the creation and maintenance of personal websites, web content management systems are now frequently utilized. Such systems offer a low cost and simple solution for those seeking to develop an online presence, and subsequently, a platform from which reported defamatory content, abuse, and copyright infringement has been witnessed. This article provides an introductory forensic analysis of the three current most popular web content management systems available, WordPress, Drupal, and Joomla! Test platforms have been created, and their site structures have been examined to provide guidance for forensic practitioners facing investigations of this type. Result's document available metadata for establishing site ownership, user interactions, and stored content following analysis of artifacts including Wordpress's wp_users, and wp_comments tables, Drupal's "watchdog" records, and Joomla!'s _users, and _content tables. Finally, investigatory limitations documenting the difficulties of investigating WCMS usage are noted, and analysis recommendations are offered. © 2018 American Academy of Forensic Sciences.

A dynamic clinical dental relational database.

PubMed

Taylor, D; Naguib, R N G; Boulton, S

2004-09-01

The traditional approach to relational database design is based on the logical organization of data into a number of related normalized tables. One assumption is that the nature and structure of the data is known at the design stage. In the case of designing a relational database to store historical dental epidemiological data from individual clinical surveys, the structure of the data is not known until the data is presented for inclusion into the database. This paper addresses the issues concerned with the theoretical design of a clinical dynamic database capable of adapting the internal table structure to accommodate clinical survey data, and presents a prototype database application capable of processing, displaying, and querying the dental data.

Petroleum system modeling of the western Canada sedimentary basin - isopach grid files

USGS Publications Warehouse

Higley, Debra K.; Henry, Mitchell E.; Roberts, Laura N.R.

2005-01-01

This publication contains zmap-format grid files of isopach intervals that represent strata associated with Devonian to Holocene petroleum systems of the Western Canada Sedimentary Basin (WCSB) of Alberta, British Columbia, and Saskatchewan, Canada. Also included is one grid file that represents elevations relative to sea level of the top of the Lower Cretaceous Mannville Group. Vertical and lateral scales are in meters. The age range represented by the stratigraphic intervals comprising the grid files is 373 million years ago (Ma) to present day. File names, age ranges, formation intervals, and primary petroleum system elements are listed in table 1. Metadata associated with this publication includes information on the study area and the zmap-format files. The digital files listed in table 1 were compiled as part of the Petroleum Processes Research Project being conducted by the Central Energy Resources Team of the U.S. Geological Survey, which focuses on modeling petroleum generation, 3 migration, and accumulation through time for petroleum systems of the WCSB. Primary purposes of the WCSB study are to Construct the 1-D/2-D/3-D petroleum system models of the WCSB. Actual boundaries of the study area are documented within the metadata; excluded are northern Alberta and eastern Saskatchewan, but fringing areas of the United States are included.Publish results of the research and the grid files generated for use in the 3-D model of the WCSB.Evaluate the use of petroleum system modeling in assessing undiscovered oil and gas resources for geologic provinces across the World.

A Compilation of Global Bio-Optical in Situ Data for Ocean-Colour Satellite Applications

NASA Technical Reports Server (NTRS)

Valente, Andre; Sathyendranath, Shubha; Brotus, Vanda; Groom, Steve; Grant, Michael; Taberner, Malcolm; Antoine, David; Arnone, Robert; Balch, William M.; Barker, Kathryn;

A self-updating road map of The Cancer Genome Atlas.

PubMed

Robbins, David E; Grüneberg, Alexander; Deus, Helena F; Tanik, Murat M; Almeida, Jonas S

2013-05-15

Since 2011, The Cancer Genome Atlas' (TCGA) files have been accessible through HTTP from a public site, creating entirely new possibilities for cancer informatics by enhancing data discovery and retrieval. Significantly, these enhancements enable the reporting of analysis results that can be fully traced to and reproduced using their source data. However, to realize this possibility, a continually updated road map of files in the TCGA is required. Creation of such a road map represents a significant data modeling challenge, due to the size and fluidity of this resource: each of the 33 cancer types is instantiated in only partially overlapping sets of analytical platforms, while the number of data files available doubles approximately every 7 months. We developed an engine to index and annotate the TCGA files, relying exclusively on third-generation web technologies (Web 3.0). Specifically, this engine uses JavaScript in conjunction with the World Wide Web Consortium's (W3C) Resource Description Framework (RDF), and SPARQL, the query language for RDF, to capture metadata of files in the TCGA open-access HTTP directory. The resulting index may be queried using SPARQL, and enables file-level provenance annotations as well as discovery of arbitrary subsets of files, based on their metadata, using web standard languages. In turn, these abilities enhance the reproducibility and distribution of novel results delivered as elements of a web-based computational ecosystem. The development of the TCGA Roadmap engine was found to provide specific clues about how biomedical big data initiatives should be exposed as public resources for exploratory analysis, data mining and reproducible research. These specific design elements align with the concept of knowledge reengineering and represent a sharp departure from top-down approaches in grid initiatives such as CaBIG. They also present a much more interoperable and reproducible alternative to the still pervasive use of data portals. A prepared dashboard, including links to source code and a SPARQL endpoint, is available at http://bit.ly/TCGARoadmap. A video tutorial is available at http://bit.ly/TCGARoadmapTutorial. robbinsd@uab.edu.

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.

A self-updating road map of The Cancer Genome Atlas

PubMed Central

Robbins, David E.; Grüneberg, Alexander; Deus, Helena F.; Tanik, Murat M.; Almeida, Jonas S.

2013-01-01

Motivation: Since 2011, The Cancer Genome Atlas’ (TCGA) files have been accessible through HTTP from a public site, creating entirely new possibilities for cancer informatics by enhancing data discovery and retrieval. Significantly, these enhancements enable the reporting of analysis results that can be fully traced to and reproduced using their source data. However, to realize this possibility, a continually updated road map of files in the TCGA is required. Creation of such a road map represents a significant data modeling challenge, due to the size and fluidity of this resource: each of the 33 cancer types is instantiated in only partially overlapping sets of analytical platforms, while the number of data files available doubles approximately every 7 months. Results: We developed an engine to index and annotate the TCGA files, relying exclusively on third-generation web technologies (Web 3.0). Specifically, this engine uses JavaScript in conjunction with the World Wide Web Consortium’s (W3C) Resource Description Framework (RDF), and SPARQL, the query language for RDF, to capture metadata of files in the TCGA open-access HTTP directory. The resulting index may be queried using SPARQL, and enables file-level provenance annotations as well as discovery of arbitrary subsets of files, based on their metadata, using web standard languages. In turn, these abilities enhance the reproducibility and distribution of novel results delivered as elements of a web-based computational ecosystem. The development of the TCGA Roadmap engine was found to provide specific clues about how biomedical big data initiatives should be exposed as public resources for exploratory analysis, data mining and reproducible research. These specific design elements align with the concept of knowledge reengineering and represent a sharp departure from top-down approaches in grid initiatives such as CaBIG. They also present a much more interoperable and reproducible alternative to the still pervasive use of data portals. Availability: A prepared dashboard, including links to source code and a SPARQL endpoint, is available at http://bit.ly/TCGARoadmap. A video tutorial is available at http://bit.ly/TCGARoadmapTutorial. Contact: robbinsd@uab.edu PMID:23595662

Fast in-database cross-matching of high-cadence, high-density source lists with an up-to-date sky model

NASA Astrophysics Data System (ADS)

Scheers, B.; Bloemen, S.; Mühleisen, H.; Schellart, P.; van Elteren, A.; Kersten, M.; Groot, P. J.

2018-04-01

Coming high-cadence wide-field optical telescopes will image hundreds of thousands of sources per minute. Besides inspecting the near real-time data streams for transient and variability events, the accumulated data archive is a wealthy laboratory for making complementary scientific discoveries. The goal of this work is to optimise column-oriented database techniques to enable the construction of a full-source and light-curve database for large-scale surveys, that is accessible by the astronomical community. We adopted LOFAR's Transients Pipeline as the baseline and modified it to enable the processing of optical images that have much higher source densities. The pipeline adds new source lists to the archive database, while cross-matching them with the known cataloguedsources in order to build a full light-curve archive. We investigated several techniques of indexing and partitioning the largest tables, allowing for faster positional source look-ups in the cross matching algorithms. We monitored all query run times in long-term pipeline runs where we processed a subset of IPHAS data that have image source density peaks over 170,000 per field of view (500,000 deg-2). Our analysis demonstrates that horizontal table partitions of declination widths of one-degree control the query run times. Usage of an index strategy where the partitions are densely sorted according to source declination yields another improvement. Most queries run in sublinear time and a few (< 20%) run in linear time, because of dependencies on input source-list and result-set size. We observed that for this logical database partitioning schema the limiting cadence the pipeline achieved with processing IPHAS data is 25 s.

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.

Data management routines for reproducible research using the G-Node Python Client library

PubMed Central

Sobolev, Andrey; Stoewer, Adrian; Pereira, Michael; Kellner, Christian J.; Garbers, Christian; Rautenberg, Philipp L.; Wachtler, Thomas

2014-01-01

Structured, efficient, and secure storage of experimental data and associated meta-information constitutes one of the most pressing technical challenges in modern neuroscience, and does so particularly in electrophysiology. The German INCF Node aims to provide open-source solutions for this domain that support the scientific data management and analysis workflow, and thus facilitate future data access and reproducible research. G-Node provides a data management system, accessible through an application interface, that is based on a combination of standardized data representation and flexible data annotation to account for the variety of experimental paradigms in electrophysiology. The G-Node Python Library exposes these services to the Python environment, enabling researchers to organize and access their experimental data using their familiar tools while gaining the advantages that a centralized storage entails. The library provides powerful query features, including data slicing and selection by metadata, as well as fine-grained permission control for collaboration and data sharing. Here we demonstrate key actions in working with experimental neuroscience data, such as building a metadata structure, organizing recorded data in datasets, annotating data, or selecting data regions of interest, that can be automated to large degree using the library. Compliant with existing de-facto standards, the G-Node Python Library is compatible with many Python tools in the field of neurophysiology and thus enables seamless integration of data organization into the scientific data workflow. PMID:24634654

Publishing and Editing of Semantically-Enabled Scientific Metadata Across Multiple Web Platforms: Challenges and Experiences

NASA Astrophysics Data System (ADS)

Patton, E. W.; West, P.; Greer, R.; Jin, B.

2011-12-01

Following on work presented at the 2010 AGU Fall Meeting, we present a number of real-world collections of semantically-enabled scientific metadata ingested into the Tetherless World RDF2HTML system as structured data and presented and edited using that system. Two separate datasets from two different domains (oceanography and solar sciences) are made available using existing web standards and services, e.g. encoded using ontologies represented with the Web Ontology Language (OWL) and stored in a SPARQL endpoint for querying. These datasets are deployed for use in three different web environments, i.e. Drupal, MediaWiki, and a custom web portal written in Java, to highlight the cross-platform nature of the data presentation. Stylesheets used to transform concepts in each domain as well as shared terms into HTML will be presented to show the power of using common ontologies to publish data and support reuse of existing terminologies. In addition, a single domain dataset is shared between two separate portal instances to demonstrate the ability for this system to offer distributed access and modification of content across the Internet. Lastly, we will highlight challenges that arose in the software engineering process, outline the design choices we made in solving those issues, and discuss how future improvements to this and other systems will enable the evolution of distributed, decentralized collaborations for scientific data sharing across multiple research groups.

OC ToGo: bed site image integration into OpenClinica with mobile devices

NASA Astrophysics Data System (ADS)

Haak, Daniel; Gehlen, Johan; Jonas, Stephan; Deserno, Thomas M.

2014-03-01

Imaging and image-based measurements nowadays play an essential role in controlled clinical trials, but electronic data capture (EDC) systems insufficiently support integration of captured images by mobile devices (e.g. smartphones and tablets). The web application OpenClinica has established as one of the world's leading EDC systems and is used to collect, manage and store data of clinical trials in electronic case report forms (eCRFs). In this paper, we present a mobile application for instantaneous integration of images into OpenClinica directly during examination on patient's bed site. The communication between the Android application and OpenClinica is based on the simple object access protocol (SOAP) and representational state transfer (REST) web services for metadata, and secure file transfer protocol (SFTP) for image transfer, respectively. OpenClinica's web services are used to query context information (e.g. existing studies, events and subjects) and to import data into the eCRF, as well as export of eCRF metadata and structural information. A stable image transfer is ensured and progress information (e.g. remaining time) visualized to the user. The workflow is demonstrated for a European multi-center registry, where patients with calciphylaxis disease are included. Our approach improves the EDC workflow, saves time, and reduces costs. Furthermore, data privacy is enhanced, since storage of private health data on the imaging devices becomes obsolete.

Data management routines for reproducible research using the G-Node Python Client library.

PubMed

Sobolev, Andrey; Stoewer, Adrian; Pereira, Michael; Kellner, Christian J; Garbers, Christian; Rautenberg, Philipp L; Wachtler, Thomas

2014-01-01

Structured, efficient, and secure storage of experimental data and associated meta-information constitutes one of the most pressing technical challenges in modern neuroscience, and does so particularly in electrophysiology. The German INCF Node aims to provide open-source solutions for this domain that support the scientific data management and analysis workflow, and thus facilitate future data access and reproducible research. G-Node provides a data management system, accessible through an application interface, that is based on a combination of standardized data representation and flexible data annotation to account for the variety of experimental paradigms in electrophysiology. The G-Node Python Library exposes these services to the Python environment, enabling researchers to organize and access their experimental data using their familiar tools while gaining the advantages that a centralized storage entails. The library provides powerful query features, including data slicing and selection by metadata, as well as fine-grained permission control for collaboration and data sharing. Here we demonstrate key actions in working with experimental neuroscience data, such as building a metadata structure, organizing recorded data in datasets, annotating data, or selecting data regions of interest, that can be automated to large degree using the library. Compliant with existing de-facto standards, the G-Node Python Library is compatible with many Python tools in the field of neurophysiology and thus enables seamless integration of data organization into the scientific data workflow.

NASA's Global Change Master Directory: Discover and Access Earth Science Data Sets, Related Data Services, and Climate Diagnostics

NASA Technical Reports Server (NTRS)

Aleman, Alicia; Olsen, Lola; Ritz, Scott; Morahan, Michael; Cepero, Laurel; Stevens, Tyler

2011-01-01

NASA's Global Change Master Directory provides the scientific community with the ability to discover, access, and use Earth science data, data-related services, and climate diagnostics worldwide. The GCMD offers descriptions of Earth science data sets using the Directory Interchange Format (DIF) metadata standard; Earth science related data services are described using the Service Entry Resource Format (SERF); and climate visualizations are described using the Climate Diagnostic (CD) standard. The DIF, SERF and CD standards each capture data attributes used to determine whether a data set, service, or climate visualization is relevant to a user's needs. Metadata fields include: title, summary, science keywords, service keywords, data center, data set citation, personnel, instrument, platform, quality, related URL, temporal and spatial coverage, data resolution and distribution information. In addition, nine valuable sets of controlled vocabularies have been developed to assist users in normalizing the search for data descriptions. An update to the GCMD's search functionality is planned to further capitalize on the controlled vocabularies during database queries. By implementing a dynamic keyword "tree", users will have the ability to search for data sets by combining keywords in new ways. This will allow users to conduct more relevant and efficient database searches to support the free exchange and re-use of Earth science data. http://gcmd.nasa.gov/

A new relational database structure and online interface for the HITRAN database

NASA Astrophysics Data System (ADS)

Hill, Christian; Gordon, Iouli E.; Rothman, Laurence S.; Tennyson, Jonathan

2013-11-01

A new format for the HITRAN database is proposed. By storing the line-transition data in a number of linked tables described by a relational database schema, it is possible to overcome the limitations of the existing format, which have become increasingly apparent over the last few years as new and more varied data are being used by radiative-transfer models. Although the database in the new format can be searched using the well-established Structured Query Language (SQL), a web service, HITRANonline, has been deployed to allow users to make most common queries of the database using a graphical user interface in a web page. The advantages of the relational form of the database to ensuring data integrity and consistency are explored, and the compatibility of the online interface with the emerging standards of the Virtual Atomic and Molecular Data Centre (VAMDC) project is discussed. In particular, the ability to access HITRAN data using a standard query language from other websites, command line tools and from within computer programs is described.

An automated process for generating archival data files from MATLAB figures

NASA Astrophysics Data System (ADS)

Wallace, G. M.; Greenwald, M.; Stillerman, J.

2016-10-01

A new directive from the White House Office of Science and Technology Policy requires that all publications supported by federal funding agencies (e.g. Department of Energy Office of Science, National Science Foundation) include machine-readable datasets for figures and tables. An automated script was developed at the PSFC to make this process easier for authors using the MATLAB plotting environment to create figures. All relevant data (x, y, z, errorbars) and metadata (line style, color, symbol shape, labels) are contained within the MATLAB .fig file created when saving a figure. The export_fig script extracts data and metadata from a .fig file and exports it into an HDF5 data file with no additional user input required. Support is included for a number of plot types including 2-D and 3-D line, contour, and surface plots, quiver plots, bar graphs, and histograms. This work supported by US Department of Energy cooperative agreement DE-FC02-99ER54512 using the Alcator C-Mod tokamak, a DOE Office of Science user facility.

STBase: one million species trees for comparative biology.

PubMed

McMahon, Michelle M; Deepak, Akshay; Fernández-Baca, David; Boss, Darren; Sanderson, Michael J

2015-01-01

Comprehensively sampled phylogenetic trees provide the most compelling foundations for strong inferences in comparative evolutionary biology. Mismatches are common, however, between the taxa for which comparative data are available and the taxa sampled by published phylogenetic analyses. Moreover, many published phylogenies are gene trees, which cannot always be adapted immediately for species level comparisons because of discordance, gene duplication, and other confounding biological processes. A new database, STBase, lets comparative biologists quickly retrieve species level phylogenetic hypotheses in response to a query list of species names. The database consists of 1 million single- and multi-locus data sets, each with a confidence set of 1000 putative species trees, computed from GenBank sequence data for 413,000 eukaryotic taxa. Two bodies of theoretical work are leveraged to aid in the assembly of multi-locus concatenated data sets for species tree construction. First, multiply labeled gene trees are pruned to conflict-free singly-labeled species-level trees that can be combined between loci. Second, impacts of missing data in multi-locus data sets are ameliorated by assembling only decisive data sets. Data sets overlapping with the user's query are ranked using a scheme that depends on user-provided weights for tree quality and for taxonomic overlap of the tree with the query. Retrieval times are independent of the size of the database, typically a few seconds. Tree quality is assessed by a real-time evaluation of bootstrap support on just the overlapping subtree. Associated sequence alignments, tree files and metadata can be downloaded for subsequent analysis. STBase provides a tool for comparative biologists interested in exploiting the most relevant sequence data available for the taxa of interest. It may also serve as a prototype for future species tree oriented databases and as a resource for assembly of larger species phylogenies from precomputed trees.

RIMS: An Integrated Mapping and Analysis System with Applications to Earth Sciences and Hydrology

NASA Astrophysics Data System (ADS)

Proussevitch, A. A.; Glidden, S.; Shiklomanov, A. I.; Lammers, R. B.

2011-12-01

A web-based information and computational system for analysis of spatially distributed Earth system, climate, and hydrologic data have been developed. The System allows visualization, data exploration, querying, manipulation and arbitrary calculations with any loaded gridded or vector polygon dataset. The system's acronym, RIMS, stands for its core functionality as a Rapid Integrated Mapping System. The system can be deployed for a Global scale projects as well as for regional hydrology and climatology studies. In particular, the Water Systems Analysis Group of the University of New Hampshire developed the global and regional (Northern Eurasia, pan-Arctic) versions of the system with different map projections and specific data. The system has demonstrated its potential for applications in other fields of Earth sciences and education. The key Web server/client components of the framework include (a) a visualization engine built on Open Source libraries (GDAL, PROJ.4, etc.) that are utilized in a MapServer; (b) multi-level data querying tools built on XML server-client communication protocols that allow downloading map data on-the-fly to a client web browser; and (c) data manipulation and grid cell level calculation tools that mimic desktop GIS software functionality via a web interface. Server side data management of the system is designed around a simple database of dataset metadata facilitating mounting of new data to the system and maintaining existing data in an easy manner. RIMS contains "built-in" river network data that allows for query of upstream areas on-demand which can be used for spatial data aggregation and analysis of sub-basin areas. RIMS is an ongoing effort and currently being used to serve a number of websites hosting a suite of hydrologic, environmental and other GIS data.

toxoMine: an integrated omics data warehouse for Toxoplasma gondii systems biology research

PubMed Central

Rhee, David B.; Croken, Matthew McKnight; Shieh, Kevin R.; Sullivan, Julie; Micklem, Gos; Kim, Kami; Golden, Aaron

2015-01-01

Toxoplasma gondii (T. gondii) is an obligate intracellular parasite that must monitor for changes in the host environment and respond accordingly; however, it is still not fully known which genetic or epigenetic factors are involved in regulating virulence traits of T. gondii. There are on-going efforts to elucidate the mechanisms regulating the stage transition process via the application of high-throughput epigenomics, genomics and proteomics techniques. Given the range of experimental conditions and the typical yield from such high-throughput techniques, a new challenge arises: how to effectively collect, organize and disseminate the generated data for subsequent data analysis. Here, we describe toxoMine, which provides a powerful interface to support sophisticated integrative exploration of high-throughput experimental data and metadata, providing researchers with a more tractable means toward understanding how genetic and/or epigenetic factors play a coordinated role in determining pathogenicity of T. gondii. As a data warehouse, toxoMine allows integration of high-throughput data sets with public T. gondii data. toxoMine is also able to execute complex queries involving multiple data sets with straightforward user interaction. Furthermore, toxoMine allows users to define their own parameters during the search process that gives users near-limitless search and query capabilities. The interoperability feature also allows users to query and examine data available in other InterMine systems, which would effectively augment the search scope beyond what is available to toxoMine. toxoMine complements the major community database ToxoDB by providing a data warehouse that enables more extensive integrative studies for T. gondii. Given all these factors, we believe it will become an indispensable resource to the greater infectious disease research community. Database URL: http://toxomine.org PMID:26130662

The parser generator as a general purpose tool

NASA Technical Reports Server (NTRS)

Noonan, R. E.; Collins, W. R.

1985-01-01

The parser generator has proven to be an extremely useful, general purpose tool. It can be used effectively by programmers having only a knowledge of grammars and no training at all in the theory of formal parsing. Some of the application areas for which a table-driven parser can be used include interactive, query languages, menu systems, translators, and programming support tools. Each of these is illustrated by an example grammar.

Putting the 1991 census sample of anonymised records on your Unix workstation.

PubMed

Turton, I; Openshaw, S

1995-03-01

"The authors describe the development of a customised computer software package for easing the analysis of the U.K. 1991 Sample of Anonymised Records. The resulting USAR [Unix Sample of Anonymised Records] package is designed to be portable within the Unix environment. It offers a number of features such as interactive table design, intelligent data interpretation, and fuzzy query. An example of SAR analysis is provided." excerpt

G-Hash: Towards Fast Kernel-based Similarity Search in Large Graph Databases.

PubMed

Wang, Xiaohong; Smalter, Aaron; Huan, Jun; Lushington, Gerald H

2009-01-01

Structured data including sets, sequences, trees and graphs, pose significant challenges to fundamental aspects of data management such as efficient storage, indexing, and similarity search. With the fast accumulation of graph databases, similarity search in graph databases has emerged as an important research topic. Graph similarity search has applications in a wide range of domains including cheminformatics, bioinformatics, sensor network management, social network management, and XML documents, among others.Most of the current graph indexing methods focus on subgraph query processing, i.e. determining the set of database graphs that contains the query graph and hence do not directly support similarity search. In data mining and machine learning, various graph kernel functions have been designed to capture the intrinsic similarity of graphs. Though successful in constructing accurate predictive and classification models for supervised learning, graph kernel functions have (i) high computational complexity and (ii) non-trivial difficulty to be indexed in a graph database.Our objective is to bridge graph kernel function and similarity search in graph databases by proposing (i) a novel kernel-based similarity measurement and (ii) an efficient indexing structure for graph data management. Our method of similarity measurement builds upon local features extracted from each node and their neighboring nodes in graphs. A hash table is utilized to support efficient storage and fast search of the extracted local features. Using the hash table, a graph kernel function is defined to capture the intrinsic similarity of graphs and for fast similarity query processing. We have implemented our method, which we have named G-hash, and have demonstrated its utility on large chemical graph databases. Our results show that the G-hash method achieves state-of-the-art performance for k-nearest neighbor (k-NN) classification. Most importantly, the new similarity measurement and the index structure is scalable to large database with smaller indexing size, faster indexing construction time, and faster query processing time as compared to state-of-the-art indexing methods such as C-tree, gIndex, and GraphGrep.

Linked Metadata - lightweight semantics for data integration (Invited)

NASA Astrophysics Data System (ADS)

Hendler, J. A.

2013-12-01

The "Linked Open Data" cloud (http://linkeddata.org) is currently used to show how the linking of datasets, supported by SPARQL endpoints, is creating a growing set of linked data assets. This linked data space has been growing rapidly, and the last version collected is estimated to have had over 35 billion 'triples.' As impressive as this may sound, there is an inherent flaw in the way the linked data story is conceived. The idea is that all of the data is represented in a linked format (generally RDF) and applications will essentially query this cloud and provide mashup capabilities between the various kinds of data that are found. The view of linking in the cloud is fairly simple -links are provided by either shared URIs or by URIs that are asserted to be owl:sameAs. This view of the linking, which primarily focuses on shared objects and subjects in RDF's subject-predicate-object representation, misses a critical aspect of Semantic Web technology. Given triples such as * A:person1 foaf:knows A:person2 * B:person3 foaf:knows B:person4 * C:person5 foaf:name 'John Doe' this view would not consider them linked (barring other assertions) even though they share a common vocabulary. In fact, we get significant clues that there are commonalities in these data items from the shared namespaces and predicates, even if the traditional 'graph' view of RDF doesn't appear to join on these. Thus, it is the linking of the data descriptions, whether as metadata or other vocabularies, that provides the linking in these cases. This observation is crucial to scientific data integration where the size of the datasets, or even the individual relationships within them, can be quite large. (Note that this is not restricted to scientific data - search engines, social networks, and massive multiuser games also create huge amounts of data.) To convert all the triples into RDF and provide individual links is often unnecessary, and is both time and space intensive. Those looking to do on the fly integration may prefer to do more traditional data queries and then convert and link the 'views' returned at retrieval time, providing another means of using the linked data infrastructure without having to convert whole datasets to triples to provide linking. Web companies have been taking advantage of 'lightweight' semantic metadata for search quality and optimization (cf. schema.org), linking networks within and without web sites (cf. Facebook's Open Graph Protocol), and in doing various kinds of advertisement and user modeling across datasets. Scientific metadata, on the other hand, has traditionally been geared at being largescale and highly descriptive, and scientific ontologies have been aimed at high expressivity, essentially providing complex reasoning services rather than the less expressive vocabularies needed for data discovery and simple mappings that can allow humans (or more complex systems) when full scale integration is needed. Although this work is just the beginning for providing integration, as the community creates more and more datasets, discovery of these data resources on the Web becomes a crucial starting place. Simple descriptors, that can be combined with textual fields and/or common community vocabularies, can be a great starting place on bringing scientific data into the Web of Data that is growing in other communities. References: [1] Pouchard, Line C., et al. "A Linked Science investigation: enhancing climate change data discovery with semantic technologies." Earth science informatics 6.3 (2013): 175-185.

WOVOdat Design Document: The Schema, Table Descriptions, and Create Table Statements for the Database of Worldwide Volcanic Unrest (WOVOdat Version 1.0)

USGS Publications Warehouse

Venezky, Dina Y.; Newhall, Christopher G.

2007-01-01

WOVOdat Overview During periods of volcanic unrest, the ability to forecast near future activity has been a primary concern for human populations living near volcanoes. Our ability to forecast future activity and mitigate hazards is based on knowledge of previous activity at the volcano exhibiting unrest and knowledge of previous activity at similar volcanoes. A small set of experts with past experience are often involved in forecasting. We need to both preserve the knowledge the experts use and continue to investigate volcanic data to make better forecasts. Advances in instrumentation, networking, and data storage technologies have greatly increased our ability to collect volcanic data and share observations with our colleagues. The wealth of data creates numerous opportunities for gaining a better understanding of magmatic conditions and processes, if the data can be easily accessed for comparison. To allow for comparison of volcanic unrest data, we are creating a central database called WOVOdat. WOVOdat will contain a subset of time-series and geo-referenced data from each WOVO observatory in common and easily accessible formats. WOVOdat is being created for volcano experts in charge of forecasting volcanic activity, scientists investigating volcanic processes, and the public. The types of queries each of these groups might ask range from, 'What volcanoes were active in November of 2002?' and 'What are the relationships between tectonic earthquakes and volcanic processes?' to complex analyses of volcanic unrest to determine what future activity might occur. A new structure for storing and accessing our data was needed to examine processes across a wide range of volcanologic conditions. WOVOdat provides this new structure using relationships to connect the data parameters such that searches can be created for analogs of unrest. The subset of data that will fill WOVOdat will continue to be collected by the observatories, who will remain the primary archives of raw and detailed data on individual episodes of unrest. MySQL, an Open Source database, was chosen as the WOVOdat database for its integration with common web languages. The question of where the data will be stored and how the disparate data sets will be integrated will not be discussed in detail here. The focus of this document is to explain the data types, formats, and table organization chosen for WOVOdat 1.0. It was written for database administrators, data loaders, query writers, and anyone who monitors volcanoes. We begin with an overview of several challenges faced and solutions used in creating the WOVOdat schema. Specifics are then given for the parameters and table organization. After each table organization section, basic create table statements are included for viewing the database field formats. In the next stage of the project, scripts will be needed for data conversion, entry, and cleansing. Views will also need to be created once the data have been loaded and the basic queries are better known. Many questions and opportunities remain. We look forward to the growth and continual improvement in efficiency of the system. We hope WOVOdat will improve our understanding of magmatic systems and help mitigate future volcanic hazards.

EarthServer: a Summary of Achievements in Technology, Services, and Standards

NASA Astrophysics Data System (ADS)

Baumann, Peter

2015-04-01

Big Data in the Earth sciences, the Tera- to Exabyte archives, mostly are made up from coverage data, according to ISO and OGC defined as the digital representation of some space-time varying phenomenon. Common examples include 1-D sensor timeseries, 2-D remote sensing imagery, 3D x/y/t image timese ries and x/y/z geology data, and 4-D x/y/z/t atmosphere and ocean data. Analytics on such data requires on-demand processing of sometimes significant complexity, such as getting the Fourier transform of satellite images. As network bandwidth limits prohibit transfer of such Big Data it is indispensable to devise protocols allowing clients to task flexible and fast processing on the server. The transatlantic EarthServer initiative, running from 2011 through 2014, has united 11 partners to establish Big Earth Data Analytics. A key ingredient has been flexibility for users to ask whatever they want, not impeded and complicated by system internals. The EarthServer answer to this is to use high-level, standards-based query languages which unify data and metadata search in a simple, yet powerful way. A second key ingredient is scalability. Without any doubt, scalability ultimately can only be achieved through parallelization. In the past, parallelizing cod e has been done at compile time and usually with manual intervention. The EarthServer approach is to perform a samentic-based dynamic distribution of queries fragments based on networks optimization and further criteria. The EarthServer platform is comprised by rasdaman, the pioneer and leading Array DBMS built for any-size multi-dimensional raster data being extended with support for irregular grids and general meshes; in-situ retrieval (evaluation of database queries on existing archive structures, avoiding data import and, hence, duplication); the aforementioned distributed query processing. Additionally, Web clients for multi-dimensional data visualization are being established. Client/server interfaces are strictly based on OGC and W3C standards, in particular the Web Coverage Processing Service (WCPS) which defines a high-level coverage query language. Reviewers have attested EarthServer that "With no doubt the project has been shaping the Big Earth Data landscape through the standardization activities within OGC, ISO and beyond". We present the project approach, its outcomes and impact on standardization and Big Data technology, and vistas for the future.

Portal to the GALEX Data Archive

NASA Astrophysics Data System (ADS)

Smith, M. A.; Conti, A.; Shiao, B.; Volpicelli, C. A.

2004-05-01

In early February MAST began its hosting of the GALEX public "Early Release Observations" images (40,000 objects) and spectra (1000 objects). MAST will host a much larger "first release," the GALEX DR1, in October, 2004. In this poster we describe features of our on-line website at http://galex.stsci.edu for researchers interested in downloading and browsing GALEX UV image and spectral data. The site, is based on MS .NET technology and user queries are entered for classes of objects or sky regions on a "MAST-like" query forms or with detailed queries written in SQL. In the latter case examples are provided to tailor a query to a user's specifications. The site provides novel features, such as tooltips that return keyword definitions, "active images" that return object classification and coordinate information in a 2.5 arcmin radius around the selected object, self-documentation of terms and tables, and of course a tutorial for new navigators. The GALEX database employs a Hierarchial Triangular Mesh system for rapid data discovery, neighbor searches, and cross correlations with other catalogs. Our "GMAX" tool allows a coplotting of object positions for objects observed by GALEX and other US-NVO compliant mission websites such as Sloan, 2MASS, FIRST.... As a member of the new Skynode network, GALEX has reported its web services to the US-NVO registry. This permits users to generate queries from other sites to cross-correlate, compare, and plot GALEX data using US-NVO protocols. Future plans for limited on-line data analysis and footprint services are described.

The Footprint Database and Web Services of the Herschel Space Observatory

NASA Astrophysics Data System (ADS)

Dobos, László; Varga-Verebélyi, Erika; Verdugo, Eva; Teyssier, David; Exter, Katrina; Valtchanov, Ivan; Budavári, Tamás; Kiss, Csaba

2016-10-01

Data from the Herschel Space Observatory is freely available to the public but no uniformly processed catalogue of the observations has been published so far. To date, the Herschel Science Archive does not contain the exact sky coverage (footprint) of individual observations and supports search for measurements based on bounding circles only. Drawing on previous experience in implementing footprint databases, we built the Herschel Footprint Database and Web Services for the Herschel Space Observatory to provide efficient search capabilities for typical astronomical queries. The database was designed with the following main goals in mind: (a) provide a unified data model for meta-data of all instruments and observational modes, (b) quickly find observations covering a selected object and its neighbourhood, (c) quickly find every observation in a larger area of the sky, (d) allow for finding solar system objects crossing observation fields. As a first step, we developed a unified data model of observations of all three Herschel instruments for all pointing and instrument modes. Then, using telescope pointing information and observational meta-data, we compiled a database of footprints. As opposed to methods using pixellation of the sphere, we represent sky coverage in an exact geometric form allowing for precise area calculations. For easier handling of Herschel observation footprints with rather complex shapes, two algorithms were implemented to reduce the outline. Furthermore, a new visualisation tool to plot footprints with various spherical projections was developed. Indexing of the footprints using Hierarchical Triangular Mesh makes it possible to quickly find observations based on sky coverage, time and meta-data. The database is accessible via a web site http://herschel.vo.elte.hu and also as a set of REST web service functions, which makes it readily usable from programming environments such as Python or IDL. The web service allows downloading footprint data in various formats including Virtual Observatory standards.

Building a Digital Library for Multibeam Data, Images and Documents

NASA Astrophysics Data System (ADS)

Miller, S. P.; Staudigel, H.; Koppers, A.; Johnson, C.; Cande, S.; Sandwell, D.; Peckman, U.; Becker, J. J.; Helly, J.; Zaslavsky, I.; Schottlaender, B. E.; Starr, S.; Montoya, G.

2001-12-01

The Scripps Institution of Oceanography, the UCSD Libraries and the San Diego Supercomputing Center have joined forces to establish a digital library for accessing a wide range of multibeam and marine geophysical data, to a community that ranges from the MGG researcher to K-12 outreach clients. This digital library collection will include 233 multibeam cruises with grids, plots, photographs, station data, technical reports, planning documents and publications, drawn from the holdings of the Geological Data Center and the SIO Archives. Inquiries will be made through an Ocean Exploration Console, reminiscent of a cockpit display where a multitude of data may be displayed individually or in two or three-dimensional projections. These displays will provide access to cruise data as well as global databases such as Global Topography, crustal age, and sediment thickness, thus meeting the day-to-day needs of researchers as well as educators, students, and the public. The prototype contains a few selected expeditions, and a review of the initial approach will be solicited from the user community during the poster session. The search process can be focused by a variety of constraints: geospatial (lat-lon box), temporal (e.g., since 1996), keyword (e.g., cruise, place name, PI, etc.), or expert-level (e.g., K-6 or researcher). The Storage Resource Broker (SRB) software from the SDSC manages the evolving collection as a series of distributed but related archives in various media, from shipboard data through processing and final archiving. The latest version of MB-System provides for the systematic creation of standard metadata, and for the harvesting of metadata from multibeam files. Automated scripts will be used to load the metadata catalog to enable queries with an Oracle database management system. These new efforts to bridge the gap between libraries and data archives are supported by the NSF Information Technology and National Science Digital Library (NSDL) programs, augmented by UC funds, and closely coordinated with Digital Library for Earth System Education (DLESE) activities.

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.

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

OPUS - Outer Planets Unified Search with Enhanced Surface Geometry Parameters - Not Just for Rings

NASA Astrophysics Data System (ADS)

Gordon, Mitchell; Showalter, Mark Robert; Ballard, Lisa; Tiscareno, Matthew S.; Heather, Neil

2016-10-01

In recent years, with the massive influx of data into the PDS from a wide array of missions and instruments, finding the precise data you need has been an ongoing challenge. For remote sensing data obtained from Jupiter to Pluto, that challenge is being addressed by the Outer Planets Unified Search, more commonly known as OPUS.OPUS is a powerful search tool available at the PDS Ring-Moon Systems Node (RMS) - formerly the PDS Rings Node. While OPUS was originally designed with ring data in mind, its capabilities have been extended to include all of the targets within an instrument's field of view. OPUS provides preview images of search results, and produces a zip file for easy download of selected products, including a table of user specified metadata. For Cassini ISS and Voyager ISS we have generated and include calibrated versions of every image.Currently OPUS supports data returned by Cassini ISS, UVIS, VIMS, and CIRS (Saturn data through June 2010), New Horizons Jupiter LORRI, Galileo SSI, Voyager ISS and IRIS, and Hubble (ACS, WFC3 and WFPC2).At the RMS Node, we have developed and incorporated into OPUS detailed geometric metadata, based on the most recent SPICE kernels, for all of the bodies in the Cassini Saturn observations. This extensive set of geometric metadata is unique to the RMS Node and enables search constraints such as latitudes and longitudes (Saturn, Titan, and icy satellites), viewing and illumination geometry (phase, incidence and emission angles), and distances and resolution.Our near term plans include adding the full set of Cassini CIRS Saturn data (with enhanced geometry), New Horizons MVIC Jupiter encounter images, New Horizons LORRI and MVIC Pluto data, HST STIS observations, and Cassini and Voyager ring occultations. We also plan to develop enhanced geometric metadata for the New Horizons LORRI and MVIC instruments for both the Jupiter and the Pluto encounters.OPUS: http://pds-rings.seti.org/search/

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.

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.

Definition of a CDI metadata profile and its ISO 19139 based encoding

NASA Astrophysics Data System (ADS)

Boldrini, Enrico; de Korte, Arjen; Santoro, Mattia; Schaap, Dick M. A.; Nativi, Stefano; Manzella, Giuseppe

2010-05-01

The Common Data Index (CDI) is the middleware service adopted by SeaDataNet for discovery and query. The primary goal of the EU funded project SeaDataNet is to develop a system which provides transparent access to marine data sets and data products from 36 countries in and around Europe. The European context of SeaDataNet requires that the developed system complies with European Directive INSPIRE. In order to assure the required conformity a GI-cat based solution is proposed. GI-cat is a broker service able to mediate from different metadata sources and publish them through a consistent and unified interface. In this case GI-cat is used as a front end to the SeaDataNet portal publishing the original data, based on CDI v.1 XML schema, through an ISO 19139 application profile catalog interface (OGC CSW AP ISO). The choice of ISO 19139 is supported and driven by INSPIRE Implementing Rules, that have been used as a reference through the whole development process. A mapping from the CDI data model to the ISO 19139 was hence to be implemented in GI-cat and a first draft quickly developed, as both CDI v.1 and ISO 19139 happen to be XML implementations based on the same abstract data model (standard ISO 19115 - metadata about geographic information). This first draft mapping pointed out the CDI metadata model differences with respect to ISO 19115, as it was not possible to accommodate all the information contained in CDI v.1 into ISO 19139. Moreover some modifications were needed in order to reach INSPIRE compliance. The consequent work consisted in the definition of the CDI metadata model as a profile of ISO 19115. This included checking of all the metadata elements present in CDI and their cardinality. A comparison was made with respect to ISO 19115 and possible extensions were individuated. ISO 19139 was then chosen as a natural XML implementation of this new CDI metadata profile. The mapping and the profile definition processes were iteratively refined leading up to a complete mapping from the CDI data model to ISO 19139. Several issues were faced during the definition process. Among these: dynamic lists and vocabularies used by SeaDataNet could not be easily accommodated in ISO 19139, time resolution information from CDI v.1 was also difficult to accommodate, ambiguities both in the ISO 19139 specification and in the INSPIRE regulations (e.g. regarding to the bounding polygon, the language and the role of the responsible party). Another outcome of this process is the set up of conventions regarding the protocol formats to be used for a useful machine to machine data access. Changes to the original ISO 19139 schema were at the maximum extent avoided because of practical reasons within SeaDataNet: additional constraint required by the profile have been defined and will be checked by the use of Schematron or other validation mechanisms. The achieved mapping was finally ready to be integrated in GI-cat by implementation of a new accessor component for CDI. These type of components play the role of data model mediators within GI-cat framework. The new defined profile and its implementation will also be used within SeaDataNet as a replacement of the current data model implementation (CDI v.1).

A compilation of global bio-optical in situ data for ocean-colour satellite applications

NASA Astrophysics Data System (ADS)

Valente, André; Sathyendranath, Shubha; Brotas, Vanda; Groom, Steve; Grant, Michael; Taberner, Malcolm; Antoine, David; Arnone, Robert; Balch, William M.; Barker, Kathryn; Barlow, Ray; Bélanger, Simon; Berthon, Jean-François; Beşiktepe, Şükrü; Brando, Vittorio; Canuti, Elisabetta; Chavez, Francisco; Claustre, Hervé; Crout, Richard; Frouin, Robert; García-Soto, Carlos; Gibb, Stuart W.; Gould, Richard; Hooker, Stanford; Kahru, Mati; Klein, Holger; Kratzer, Susanne; Loisel, Hubert; McKee, David; Mitchell, Brian G.; Moisan, Tiffany; Muller-Karger, Frank; O'Dowd, Leonie; Ondrusek, Michael; Poulton, Alex J.; Repecaud, Michel; Smyth, Timothy; Sosik, Heidi M.; Twardowski, Michael; Voss, Kenneth; Werdell, Jeremy; Wernand, Marcel; Zibordi, Giuseppe

2016-06-01

A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite-data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GeP&CO), span between 1997 and 2012, and have a global distribution. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties and spectral diffuse attenuation coefficients. The data were from multi-project archives acquired via the open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were preserved throughout the work and made available in the final table. Using all the data in a validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. By making available the metadata, it is also possible to analyse each set of data separately. The compiled data are available at doi:10.1594/PANGAEA.854832 (Valente et al., 2015).

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

An interoperability experiment for sharing hydrological rating tables

NASA Astrophysics Data System (ADS)

Lemon, D.; Taylor, P.; Sheahan, P.

2013-12-01

The increasing demand on freshwater resources is requiring authorities to produce more accurate and timely estimates of their available water. Calculation of continuous time-series of river discharge and storage volumes generally requires rating tables. These approximate relationships between two phenomena, such as river level and discharge, and allow us to produce continuous estimates of a phenomenon that may be impractical or impossible to measure directly. Standardised information models or access mechanisms for rating tables are required to support sharing and exchange of water flow data. An Interoperability Experiment (IE) is underway to test an information model that describes rating tables, the observations made to build these ratings, and river cross-section data. The IE is an initiative of the joint World Meteorological Organisation/Open Geospatial Consortium's Hydrology Domain Working Group (HydroDWG) and the model will be published as WaterML2.0 part 2. Interoperability Experiments (IEs) are low overhead, multiple member projects that are run under the OGC's interoperability program to test existing and emerging standards. The HydroDWG has previously run IEs to test early versions of OGC WaterML2.0 part 1 - timeseries. This IE is focussing on two key exchange scenarios: Sharing rating tables and gauging observations between water agencies. Through the use of standard OGC web services, rating tables and associated data will be made available from water agencies. The (Australian) Bureau of Meteorology will retrieve rating tables on-demand from water authorities, allowing the Bureau to run conversions of data within their own systems. Exposing rating tables and gaugings for online analysis and educational purposes. A web client will be developed to enable exploration and visualization of rating tables, gaugings and related metadata for monitoring points. The client gives a quick view into available rating tables, their periods of applicability and the standard deviation of observations against the relationship. An example of this client running can be seen at the link provided. The result of the IE will form the basis for the standardisation of WaterML2.0 part 2. The use of the standard will lead to increased transparency and accessibility of rating tables, while also improving general understanding of this important hydrological concept.

DASMiner: discovering and integrating data from DAS sources

PubMed Central

2009-01-01

Background DAS is a widely adopted protocol for providing syntactic interoperability among biological databases. The popularity of DAS is due to a simplified and elegant mechanism for data exchange that consists of sources exposing their RESTful interfaces for data access. As a growing number of DAS services are available for molecular biology resources, there is an incentive to explore this protocol in order to advance data discovery and integration among these resources. Results We developed DASMiner, a Matlab toolkit for querying DAS data sources that enables creation of integrated biological models using the information available in DAS-compliant repositories. DASMiner is composed by a browser application and an API that work together to facilitate gathering of data from different DAS sources, which can be used for creating enriched datasets from multiple sources. The browser is used to formulate queries and navigate data contained in DAS sources. Users can execute queries against these sources in an intuitive fashion, without the need of knowing the specific DAS syntax for the particular source. Using the source's metadata provided by the DAS Registry, the browser's layout adapts to expose only the set of commands and coordinate systems supported by the specific source. For this reason, the browser can interrogate any DAS source, independently of the type of data being served. The API component of DASMiner may be used for programmatic access of DAS sources by programs in Matlab. Once the desired data is found during navigation, the query is exported in the format of an API call to be used within any Matlab application. We illustrate the use of DASMiner by creating integrative models of histone modification maps and protein-protein interaction networks. These enriched datasets were built by retrieving and integrating distributed genomic and proteomic DAS sources using the API. Conclusion The support of the DAS protocol allows that hundreds of molecular biology databases to be treated as a federated, online collection of resources. DASMiner enables full exploration of these resources, and can be used to deploy applications and create integrated views of biological systems using the information deposited in DAS repositories. PMID:19919683

Use of Statistical Estimators as Virtual Observatory Search ParametersEnabling Access to Solar and Planetary Resources through the Virtual Observatory

NASA Astrophysics Data System (ADS)

Merka, J.; Dolan, C. F.

2015-12-01

Finding and retrieving space physics data is often a complicated taskeven for publicly available data sets: Thousands of relativelysmall and many large data sets are stored in various formats and, inthe better case, accompanied by at least some documentation. VirtualHeliospheric and Magnetospheric Observatories (VHO and VMO) help researches by creating a single point of uniformdiscovery, access, and use of heliospheric (VHO) and magnetospheric(VMO) data.The VMO and VHO functionality relies on metadata expressed using theSPASE data model. This data model is developed by the SPASE WorkingGroup which is currently the only international group supporting globaldata management for Solar and Space Physics. The two Virtual Observatories(VxOs) have initiated and lead a development of a SPASE-related standardnamed SPASE Query Language for provided a standard way of submittingqueries and receiving results.The VMO and VHO use SPASE and SPASEQL for searches based on various criteria such as, for example, spatial location, time of observation, measurement type, parameter values, etc. The parameter values are represented by their statisticalestimators calculated typically over 10-minute intervals: mean, median, standard deviation, minimum, and maximum. The use of statistical estimatorsenables science driven data queries that simplify and shorten the effort tofind where and/or how often the sought phenomenon is observed, as we will present.

Development of XML Schema for Broadband Digital Seismograms and Data Center Portal

NASA Astrophysics Data System (ADS)

Takeuchi, N.; Tsuboi, S.; Ishihara, Y.; Nagao, H.; Yamagishi, Y.; Watanabe, T.; Yanaka, H.; Yamaji, H.

2008-12-01

There are a number of data centers around the globe, where the digital broadband seismograms are opened to researchers. Those centers use their own user interfaces and there are no standard to access and retrieve seismograms from different data centers using unified interface. One of the emergent technologies to realize unified user interface for different data centers is the concept of WebService and WebService portal. Here we have developed a prototype of data center portal for digital broadband seismograms. This WebService portal uses WSDL (Web Services Description Language) to accommodate differences among the different data centers. By using the WSDL, alteration and addition of data center user interfaces can be easily managed. This portal, called NINJA Portal, assumes three WebServices: (1) database Query service, (2) Seismic event data request service, and (3) Seismic continuous data request service. Current system supports both station search of database Query service and seismic continuous data request service. Data centers supported by this NINJA portal will be OHP data center in ERI and Pacific21 data center in IFREE/JAMSTEC in the beginning. We have developed metadata standard for seismological data based on QuakeML for parametric data, which has been developed by ETH Zurich, and XML-SEED for waveform data, which was developed by IFREE/JAMSTEC. The prototype of NINJA portal is now released through IFREE web page (http://www.jamstec.go.jp/pacific21/).

Font adaptive word indexing of modern printed documents.

PubMed

Marinai, Simone; Marino, Emanuele; Soda, Giovanni

2006-08-01

We propose an approach for the word-level indexing of modern printed documents which are difficult to recognize using current OCR engines. By means of word-level indexing, it is possible to retrieve the position of words in a document, enabling queries involving proximity of terms. Web search engines implement this kind of indexing, allowing users to retrieve Web pages on the basis of their textual content. Nowadays, digital libraries hold collections of digitized documents that can be retrieved either by browsing the document images or relying on appropriate metadata assembled by domain experts. Word indexing tools would therefore increase the access to these collections. The proposed system is designed to index homogeneous document collections by automatically adapting to different languages and font styles without relying on OCR engines for character recognition. The approach is based on three main ideas: the use of Self Organizing Maps (SOM) to perform unsupervised character clustering, the definition of one suitable vector-based word representation whose size depends on the word aspect-ratio, and the run-time alignment of the query word with indexed words to deal with broken and touching characters. The most appropriate applications are for processing modern printed documents (17th to 19th centuries) where current OCR engines are less accurate. Our experimental analysis addresses six data sets containing documents ranging from books of the 17th century to contemporary journals.

A relational database in neurosurgery.

PubMed

Sicurello, F; Marchetti, M R; Cazzaniga, P

1995-01-01

This paper describes teh automatic procedure for a clinical record management in a Neurosurgery ward. The automated record allows the storage, querying and effective management of clinical data. This is useful during the patient stay and also for data processing and analysis aiming at clinical research and statistical studies. The clinical record is problem-oriented. It contains a minimum data set regarding every patient and a data set which is defined by a classification nomenclature (using an inner protocol). The main parts of the clinical record are the following tables: PERSONAL DATA: contains the fields relating to personal and admission data of the patient. The compilation of some fields is compulsory because they serve as input for the automated discharge letter. This table is used as an identifier for patient retrieval. composed of five different tables according to the kind of data. They are: familiar anamnesis, physiological anamnesis, past and next pathology anamnesis, and trauma anamnesis. GENERAL OBJECTIVITY: contains the general physical information of a patient. The field hold default values, which quickens the compilation and assures the recording of normal values. NEUROLOGICAL EXAMINATION: contains information about the neurological status of the patient. Also in this table, ther are default values in the fields. COMA: contains standardized ata and classifications. The multiple choices are automated and driven and belong to homogeneous classes. SURGICAL OPERATIONS: the information recording is made defining the general kind of operation and then defining the peculiar kind of operation. INSTRUMENTAL EXAMINATIONS: some examination results are recorded in a free structure, while other ones (TAC, etc.) follow codified structure. In order to identify a pathology by means of TAC, it is enough to record three values corresponding to three variables. THis classification fully describes a lot of neurosurgical pathologies. DISCHARGE: contains conclusions, therapies, result, and hospital course. Medical language is closer to the natural one and presents some abiguities. In order to solve this problem, a classification nomenclature was used for diagnosis definition. DISCHARGE LETTER: the document given to the patient when he is discharged. It extracts data from the previously described modules and contains standard headings. The information stored int he database is structured (e.g., diagnosis, name, surname, etc.) and access to this data takes place when the user wants to search the database, using particular queries where the identifying data of a patient is put as conditions for the research (SELECT age, name WHERE diagnosis="TRAUMA"). Logical operators and relational algebra of the relational DBMS allows more complex queries ((diagnosis="TRAUMA" AND age="19") OR sex="M"). The queries are deterministic, because data management uses a classification nomenclature. Data retrieval takes place through a matching, and the DBMS answers directly to the queries. The information retrieval speed depends upon the kind of system that is used; in our case retrieval time is low because the accesses to disk are few even for big databases. In medicine, clinical records can have a hierarchical structure and/or a relational one. Nevertheless, the hierarchical model presents a disadvantage: it is not very flexible because it is linked to a pre-defined structure; as a matter of fact, the definition of path is established in the beginning and not during the execution. Thus, a better representation of the system at a logical level requries a relational DBMS which exploits the relationships between entities in a vertical and horizontal way. That is why the developers adopted a mixed strategy which exploits the advantages of both models and which is provided by M Technology with SQL language (M/SQL). For the future, it is important to have at one's disposal multimedia technologies, which integrate different kinds of information (alp

A method to implement fine-grained access control for personal health records through standard relational database queries.

PubMed

Sujansky, Walter V; Faus, Sam A; Stone, Ethan; Brennan, Patricia Flatley

2010-10-01

Online personal health records (PHRs) enable patients to access, manage, and share certain of their own health information electronically. This capability creates the need for precise access-controls mechanisms that restrict the sharing of data to that intended by the patient. The authors describe the design and implementation of an access-control mechanism for PHR repositories that is modeled on the eXtensible Access Control Markup Language (XACML) standard, but intended to reduce the cognitive and computational complexity of XACML. The authors implemented the mechanism entirely in a relational database system using ANSI-standard SQL statements. Based on a set of access-control rules encoded as relational table rows, the mechanism determines via a single SQL query whether a user who accesses patient data from a specific application is authorized to perform a requested operation on a specified data object. Testing of this query on a moderately large database has demonstrated execution times consistently below 100ms. The authors include the details of the implementation, including algorithms, examples, and a test database as Supplementary materials. Copyright © 2010 Elsevier Inc. All rights reserved.

HbVar: A relational database of human hemoglobin variants and thalassemia mutations at the globin gene server.

PubMed

Hardison, Ross C; Chui, David H K; Giardine, Belinda; Riemer, Cathy; Patrinos, George P; Anagnou, Nicholas; Miller, Webb; Wajcman, Henri

2002-03-01

We have constructed a relational database of hemoglobin variants and thalassemia mutations, called HbVar, which can be accessed on the web at http://globin.cse.psu.edu. Extensive information is recorded for each variant and mutation, including a description of the variant and associated pathology, hematology, electrophoretic mobility, methods of isolation, stability information, ethnic occurrence, structure studies, functional studies, and references. The initial information was derived from books by Dr. Titus Huisman and colleagues [Huisman et al., 1996, 1997, 1998]. The current database is updated regularly with the addition of new data and corrections to previous data. Queries can be formulated based on fields in the database. Tables of common categories of variants, such as all those involving the alpha1-globin gene (HBA1) or all those that result in high oxygen affinity, are maintained by automated queries on the database. Users can formulate more precise queries, such as identifying "all beta-globin variants associated with instability and found in Scottish populations." This new database should be useful for clinical diagnosis as well as in fundamental studies of hemoglobin biochemistry, globin gene regulation, and human sequence variation at these loci. Copyright 2002 Wiley-Liss, Inc.

Magnetic Fields for All: The GPIPS Community Web-Access Portal

NASA Astrophysics Data System (ADS)

Carveth, Carol; Clemens, D. P.; Pinnick, A.; Pavel, M.; Jameson, K.; Taylor, B.

2007-12-01

The new GPIPS website portal provides community users with an intuitive and powerful interface to query the data products of the Galactic Plane Infrared Polarization Survey. The website, which was built using PHP for the front end and MySQL for the database back end, allows users to issue queries based on galactic or equatorial coordinates, GPIPS-specific identifiers, polarization information, magnitude information, and several other attributes. The returns are presented in HTML tables, with the added option of either downloading or being emailed an ASCII file including the same or more information from the database. Other functionalities of the website include providing details of the status of the Survey (which fields have been observed or are planned to be observed), techniques involved in data collection and analysis, and descriptions of the database contents and names. For this initial launch of the website, users may access the GPIPS polarization point source catalog and the deep coadd photometric point source catalog. Future planned developments include a graphics-based method for querying the database, as well as tools to combine neighboring GPIPS images into larger image files for both polarimetry and photometry. This work is partially supported by NSF grant AST-0607500.

Relational Database for the Geology of the Northern Rocky Mountains - Idaho, Montana, and Washington

USGS Publications Warehouse

Causey, J. Douglas; Zientek, Michael L.; Bookstrom, Arthur A.; Frost, Thomas P.; Evans, Karl V.; Wilson, Anna B.; Van Gosen, Bradley S.; Boleneus, David E.; Pitts, Rebecca A.

2008-01-01

A relational database was created to prepare and organize geologic map-unit and lithologic descriptions for input into a spatial database for the geology of the northern Rocky Mountains, a compilation of forty-three geologic maps for parts of Idaho, Montana, and Washington in U.S. Geological Survey Open File Report 2005-1235. Not all of the information was transferred to and incorporated in the spatial database due to physical file limitations. This report releases that part of the relational database that was completed for that earlier product. In addition to descriptive geologic information for the northern Rocky Mountains region, the relational database contains a substantial bibliography of geologic literature for the area. The relational database nrgeo.mdb (linked below) is available in Microsoft Access version 2000, a proprietary database program. The relational database contains data tables and other tables used to define terms, relationships between the data tables, and hierarchical relationships in the data; forms used to enter data; and queries used to extract data.

Design and implementation of the NPOI database and website

NASA Astrophysics Data System (ADS)

Newman, K.; Jorgensen, A. M.; Landavazo, M.; Sun, B.; Hutter, D. J.; Armstrong, J. T.; Mozurkewich, David; Elias, N.; van Belle, G. T.; Schmitt, H. R.; Baines, E. K.

2014-07-01

The Navy Precision Optical Interferometer (NPOI) has been recording astronomical observations for nearly two decades, at this point with hundreds of thousands of individual observations recorded to date for a total data volume of many terabytes. To make maximum use of the NPOI data it is necessary to organize them in an easily searchable manner and be able to extract essential diagnostic information from the data to allow users to quickly gauge data quality and suitability for a specific science investigation. This sets the motivation for creating a comprehensive database of observation metadata as well as, at least, reduced data products. The NPOI database is implemented in MySQL using standard database tools and interfaces. The use of standard database tools allows us to focus on top-level database and interface implementation and take advantage of standard features such as backup, remote access, mirroring, and complex queries which would otherwise be time-consuming to implement. A website was created in order to give scientists a user friendly interface for searching the database. It allows the user to select various metadata to search for and also allows them to decide how and what results are displayed. This streamlines the searches, making it easier and quicker for scientists to find the information they are looking for. The website has multiple browser and device support. In this paper we present the design of the NPOI database and website, and give examples of its use.

The ATLAS TAGS database distribution and management - Operational challenges of a multi-terabyte distributed database

NASA Astrophysics Data System (ADS)

Viegas, F.; Malon, D.; Cranshaw, J.; Dimitrov, G.; Nowak, M.; Nairz, A.; Goossens, L.; Gallas, E.; Gamboa, C.; Wong, A.; Vinek, E.

2010-04-01

The TAG files store summary event quantities that allow a quick selection of interesting events. This data will be produced at a nominal rate of 200 Hz, and is uploaded into a relational database for access from websites and other tools. The estimated database volume is 6TB per year, making it the largest application running on the ATLAS relational databases, at CERN and at other voluntary sites. The sheer volume and high rate of production makes this application a challenge to data and resource management, in many aspects. This paper will focus on the operational challenges of this system. These include: uploading the data from files to the CERN's and remote sites' databases; distributing the TAG metadata that is essential to guide the user through event selection; controlling resource usage of the database, from the user query load to the strategy of cleaning and archiving of old TAG data.

Web based tools for visualizing imaging data and development of XNATView, a zero footprint image viewer

PubMed Central

Gutman, David A.; Dunn, William D.; Cobb, Jake; Stoner, Richard M.; Kalpathy-Cramer, Jayashree; Erickson, Bradley

2014-01-01

Advances in web technologies now allow direct visualization of imaging data sets without necessitating the download of large file sets or the installation of software. This allows centralization of file storage and facilitates image review and analysis. XNATView is a light framework recently developed in our lab to visualize DICOM images stored in The Extensible Neuroimaging Archive Toolkit (XNAT). It consists of a PyXNAT-based framework to wrap around the REST application programming interface (API) and query the data in XNAT. XNATView was developed to simplify quality assurance, help organize imaging data, and facilitate data sharing for intra- and inter-laboratory collaborations. Its zero-footprint design allows the user to connect to XNAT from a web browser, navigate through projects, experiments, and subjects, and view DICOM images with accompanying metadata all within a single viewing instance. PMID:24904399

LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing.

PubMed

Stephens, Kari A; Lin, Ching-Ping; Baldwin, Laura-Mae; Echo-Hawk, Abigail; Keppel, Gina A; Buchwald, Dedra; Whitener, Ron J; Korngiebel, Diane M; Berg, Alfred O; Black, Robert A; Tarczy-Hornoch, Peter

2012-01-01

The University of Washington Institute of Translational Health Sciences is engaged in a project, LC Data QUEST, building data sharing capacity in primary care practices serving rural and tribal populations in the Washington, Wyoming, Alaska, Montana, Idaho region to build research infrastructure. We report on the iterative process of developing the technical architecture for semantically aligning electronic health data in primary care settings across our pilot sites and tools that will facilitate linkages between the research and practice communities. Our architecture emphasizes sustainable technical solutions for addressing data extraction, alignment, quality, and metadata management. The architecture provides immediate benefits to participating partners via a clinical decision support tool and data querying functionality to support local quality improvement efforts. The FInDiT tool catalogues type, quantity, and quality of the data that are available across the LC Data QUEST data sharing architecture. These tools facilitate the bi-directional process of translational research.

A Polyglot Approach to Bioinformatics Data Integration: A Phylogenetic Analysis of HIV-1

PubMed Central

Reisman, Steven; Hatzopoulos, Thomas; Läufer, Konstantin; Thiruvathukal, George K.; Putonti, Catherine

2016-01-01

As sequencing technologies continue to drop in price and increase in throughput, new challenges emerge for the management and accessibility of genomic sequence data. We have developed a pipeline for facilitating the storage, retrieval, and subsequent analysis of molecular data, integrating both sequence and metadata. Taking a polyglot approach involving multiple languages, libraries, and persistence mechanisms, sequence data can be aggregated from publicly available and local repositories. Data are exposed in the form of a RESTful web service, formatted for easy querying, and retrieved for downstream analyses. As a proof of concept, we have developed a resource for annotated HIV-1 sequences. Phylogenetic analyses were conducted for >6,000 HIV-1 sequences revealing spatial and temporal factors influence the evolution of the individual genes uniquely. Nevertheless, signatures of origin can be extrapolated even despite increased globalization. The approach developed here can easily be customized for any species of interest. PMID:26819543

Content-Based Discovery for Web Map Service using Support Vector Machine and User Relevance Feedback

PubMed Central

Cheng, Xiaoqiang; Qi, Kunlun; Zheng, Jie; You, Lan; Wu, Huayi

2016-01-01

Many discovery methods for geographic information services have been proposed. There are approaches for finding and matching geographic information services, methods for constructing geographic information service classification schemes, and automatic geographic information discovery. Overall, the efficiency of the geographic information discovery keeps improving., There are however, still two problems in Web Map Service (WMS) discovery that must be solved. Mismatches between the graphic contents of a WMS and the semantic descriptions in the metadata make discovery difficult for human users. End-users and computers comprehend WMSs differently creating semantic gaps in human-computer interactions. To address these problems, we propose an improved query process for WMSs based on the graphic contents of WMS layers, combining Support Vector Machine (SVM) and user relevance feedback. Our experiments demonstrate that the proposed method can improve the accuracy and efficiency of WMS discovery. PMID:27861505

Visual interface for space and terrestrial analysis

NASA Technical Reports Server (NTRS)

Dombrowski, Edmund G.; Williams, Jason R.; George, Arthur A.; Heckathorn, Harry M.; Snyder, William A.

1995-01-01

The management of large geophysical and celestial data bases is now, more than ever, the most critical path to timely data analysis. With today's large volume data sets from multiple satellite missions, analysts face the task of defining useful data bases from which data and metadata (information about data) can be extracted readily in a meaningful way. Visualization, following an object-oriented design, is a fundamental method of organizing and handling data. Humans, by nature, easily accept pictorial representations of data. Therefore graphically oriented user interfaces are appealing, as long as they remain simple to produce and use. The Visual Interface for Space and Terrestrial Analysis (VISTA) system, currently under development at the Naval Research Laboratory's Backgrounds Data Center (BDC), has been designed with these goals in mind. Its graphical user interface (GUI) allows the user to perform queries, visualization, and analysis of atmospheric and celestial backgrounds data.

Content-Based Discovery for Web Map Service using Support Vector Machine and User Relevance Feedback.

PubMed

Hu, Kai; Gui, Zhipeng; Cheng, Xiaoqiang; Qi, Kunlun; Zheng, Jie; You, Lan; Wu, Huayi

2016-01-01

Many discovery methods for geographic information services have been proposed. There are approaches for finding and matching geographic information services, methods for constructing geographic information service classification schemes, and automatic geographic information discovery. Overall, the efficiency of the geographic information discovery keeps improving., There are however, still two problems in Web Map Service (WMS) discovery that must be solved. Mismatches between the graphic contents of a WMS and the semantic descriptions in the metadata make discovery difficult for human users. End-users and computers comprehend WMSs differently creating semantic gaps in human-computer interactions. To address these problems, we propose an improved query process for WMSs based on the graphic contents of WMS layers, combining Support Vector Machine (SVM) and user relevance feedback. Our experiments demonstrate that the proposed method can improve the accuracy and efficiency of WMS discovery.

Uniform Data Access Using GXD

NASA Technical Reports Server (NTRS)

Vanderbilt, Peter

1999-01-01

This paper gives an overview of GXD, a framework facilitating publication and use of data from diverse data sources. GXD defines an object-oriented data model designed to represent a wide range of things including data, its metadata, resources and query results. GXD also defines a data transport language. a dialect of XML, for representing instances of the data model. This language allows for a wide range of data source implementations by supporting both the direct incorporation of data and the specification of data by various rules. The GXD software library, proto-typed in Java, includes client and server runtimes. The server runtime facilitates the generation of entities containing data encoded in the GXD transport language. The GXD client runtime interprets these entities (potentially from many data sources) to create an illusion of a globally interconnected data space, one that is independent of data source location and implementation.

LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing

PubMed Central

Stephens, Kari A.; Lin, Ching-Ping; Baldwin, Laura-Mae; Echo-Hawk, Abigail; Keppel, Gina A.; Buchwald, Dedra; Whitener, Ron J.; Korngiebel, Diane M.; Berg, Alfred O.; Black, Robert A.; Tarczy-Hornoch, Peter

2012-01-01

The University of Washington Institute of Translational Health Sciences is engaged in a project, LC Data QUEST, building data sharing capacity in primary care practices serving rural and tribal populations in the Washington, Wyoming, Alaska, Montana, Idaho region to build research infrastructure. We report on the iterative process of developing the technical architecture for semantically aligning electronic health data in primary care settings across our pilot sites and tools that will facilitate linkages between the research and practice communities. Our architecture emphasizes sustainable technical solutions for addressing data extraction, alignment, quality, and metadata management. The architecture provides immediate benefits to participating partners via a clinical decision support tool and data querying functionality to support local quality improvement efforts. The FInDiT tool catalogues type, quantity, and quality of the data that are available across the LC Data QUEST data sharing architecture. These tools facilitate the bi-directional process of translational research. PMID:22779052

The Starchive: An open access, open source archive of nearby and young stars and their planets

NASA Astrophysics Data System (ADS)

Tanner, Angelle; Gelino, Chris; Elfeki, Mario

2015-12-01

Historically, astronomers have utilized a piecemeal set of archives such as SIMBAD, the Washington Double Star Catalog, various exoplanet encyclopedias and electronic tables from the literature to cobble together stellar and exo-planetary parameters in the absence of corresponding images and spectra. As the search for planets around young stars through direct imaging, transits and infrared/optical radial velocity surveys blossoms, there is a void in the available set of to create comprehensive lists of the stellar parameters of nearby stars especially for important parameters such as metallicity and stellar activity indicators. For direct imaging surveys, we need better resources for downloading existing high contrast images to help confirm new discoveries and find ideal target stars. Once we have discovered new planets, we need a uniform database of stellar and planetary parameters from which to look for correlations to better understand the formation and evolution of these systems. As a solution to these issues, we are developing the Starchive - an open access stellar archive in the spirit of the open exoplanet catalog, the Kepler Community Follow-up Program and many others. The archive will allow users to download various datasets, upload new images, spectra and metadata and will contain multiple plotting tools to use in presentations and data interpretations. While we will highly regulate and constantly validate the data being placed into our archive the open nature of its design is intended to allow the database to be expanded efficiently and have a level of versatility which is necessary in today's fast moving, big data community. Finally, the front-end scripts will be placed on github and users will be encouraged to contribute new plotting tools. Here, I will introduce the community to the content and expected capabilities of the archive and query the audience for community feedback.

High dimensional biological data retrieval optimization with NoSQL technology.

PubMed

Wang, Shicai; Pandis, Ioannis; Wu, Chao; He, Sijin; Johnson, David; Emam, Ibrahim; Guitton, Florian; Guo, Yike

2014-01-01

High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data model as a basis for migrating tranSMART's implementation to a more scalable solution for Big Data.

High dimensional biological data retrieval optimization with NoSQL technology

PubMed Central

2014-01-01

Background High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. Results In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. Conclusions The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data model as a basis for migrating tranSMART's implementation to a more scalable solution for Big Data. PMID:25435347

Development and Utility of Automatic Language Processing Technologies. Volume 2

DTIC Science & Technology

2014-04-01

speech for each word using the existing Treetagger program. 3. Stem the word using the revised RevP stemmer, “RussianStemmer2013. java ” (see Section...KBaselineParaphrases2013. java ,” with the paraphrase table and a LM built from the TED training data. Information from the LM was called using the new utility query_interp...GATE/ Java Annotation Patterns Engine (JAPE) interface and on transliteration of Chinese named entities. Available Linguistic Data Consortium (LDC

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

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

Bartoletti, T.

SPI/U3.1 consists of five tools used to assess and report the security posture of computers running the UNIX operating system. The tools are: Access Control Test: A rule-based system which identifies sequential dependencies in UNIX access controls. Binary Inspector Tool: Evaluates the release status of system binaries by comparing a crypto-checksum to provide table entries. Change Detection Tool: Maintains and applies a snapshot of critical system files and attributes for purposes of change detection. Configuration Query Language: Accepts CQL-based scripts (provided) to evaluate queries over the status of system files, configuration of services and many other elements of UNIX systemmore » security. Password Security Inspector: Tests for weak or aged passwords. The tools are packaged with a forms-based user interface providing on-line context-sensistive help, job scheduling, parameter management and output report management utilities. Tools may be run independent of the UI.« less

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

Bartoletti, Tony

SPI/U3.2 consists of five tools used to assess and report the security posture of computers running the UNIX operating system. The tools are: Access Control Test: A rule-based system which identifies sequential dependencies in UNIX access controls. Binary Authentication Tool: Evaluates the release status of system binaries by comparing a crypto-checksum to provide table entries. Change Detection Tool: Maintains and applies a snapshot of critical system files and attributes for purposes of change detection. Configuration Query Language: Accepts CQL-based scripts (provided) to evaluate queries over the status of system files, configuration of services and many other elements of UNIX systemmore » security. Password Security Inspector: Tests for weak or aged passwords. The tools are packaged with a forms-based user interface providing on-line context-sensistive help, job scheduling, parameter management and output report management utilities. Tools may be run independent of the UI.« less

Intelligent search in Big Data

NASA Astrophysics Data System (ADS)

Birialtsev, E.; Bukharaev, N.; Gusenkov, A.

2017-10-01

An approach to data integration, aimed on the ontology-based intelligent search in Big Data, is considered in the case when information objects are represented in the form of relational databases (RDB), structurally marked by their schemes. The source of information for constructing an ontology and, later on, the organization of the search are texts in natural language, treated as semi-structured data. For the RDBs, these are comments on the names of tables and their attributes. Formal definition of RDBs integration model in terms of ontologies is given. Within framework of the model universal RDB representation ontology, oil production subject domain ontology and linguistic thesaurus of subject domain language are built. Technique of automatic SQL queries generation for subject domain specialists is proposed. On the base of it, information system for TATNEFT oil-producing company RDBs was implemented. Exploitation of the system showed good relevance with majority of queries.

SPI/U3.2. Security Profile Inspector for UNIX Systems

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

Bartoletti, A.

1994-08-01

SPI/U3.2 consists of five tools used to assess and report the security posture of computers running the UNIX operating system. The tools are: Access Control Test: A rule-based system which identifies sequential dependencies in UNIX access controls. Binary Authentication Tool: Evaluates the release status of system binaries by comparing a crypto-checksum to provide table entries. Change Detection Tool: Maintains and applies a snapshot of critical system files and attributes for purposes of change detection. Configuration Query Language: Accepts CQL-based scripts (provided) to evaluate queries over the status of system files, configuration of services and many other elements of UNIX systemmore » security. Password Security Inspector: Tests for weak or aged passwords. The tools are packaged with a forms-based user interface providing on-line context-sensistive help, job scheduling, parameter management and output report management utilities. Tools may be run independent of the UI.« less

High-Bandwidth Tactical-Network Data Analysis in a High-Performance-Computing (HPC) Environment: Device Status Data

DTIC Science & Technology

2015-09-01

Figures iv List of Tables iv 1. Introduction 1 2. Device Status Data 1 2.1 SNMP 1 2.2 NMS 1 2.3 ICMP Ping 2 3. Data Collection 2 4. Hydra ...Configuration 3 4.1 Status Codes 4 4.2 Request Time 5 4.3 Hydra BLOb Metadata 6 5. Data Processing 6 5.1 Hydra Data Processing Framework 6 5.1.1...Basic Components 6 5.1.2 Map Component 7 5.1.3 Postmap Methods 8 5.1.4 Data Flow 9 5.1.5 Distributed Processing Considerations 9 5.2 Specific Hydra

A clinical data repository enhances hospital infection control.

PubMed Central

Samore, M.; Lichtenberg, D.; Saubermann, L.; Kawachi, C.; Carmeli, Y.

1997-01-01

We describe the benefits of a relational database of hospital clinical data (Clinical Data Repository; CDR) for an infection control program. The CDR consists of > 40 Sybase tables, and is directly accessible for ad hoc queries by members of the infection control unit who have been granted privileges for access by the Information Systems Department. The data elements and functional requirements most useful for surveillance of nosocomial infections, antibiotic use, and resistant organisms are characterized. Specific applications of the CDR are presented, including the use of automated definitions of nosocomial infection, graphical monitoring of resistant organisms with quality control limits, and prospective detection of inappropriate antibiotic use. Hospital surveillance and quality improvement activities are significantly benefited by the availability of a querable set of tables containing diverse clinical data. PMID:9357588

Use of Graph Database for the Integration of Heterogeneous Biological Data.

PubMed

Yoon, Byoung-Ha; Kim, Seon-Kyu; Kim, Seon-Young

2017-03-01

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.

Use of Graph Database for the Integration of Heterogeneous Biological Data

PubMed Central

Yoon, Byoung-Ha; Kim, Seon-Kyu

2017-01-01

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data. PMID:28416946

[Establishment of a comprehensive database for laryngeal cancer related genes and the miRNAs].

PubMed

Li, Mengjiao; E, Qimin; Liu, Jialin; Huang, Tingting; Liang, Chuanyu

2015-09-01

By collecting and analyzing the laryngeal cancer related genes and the miRNAs, to build a comprehensive laryngeal cancer-related gene database, which differs from the current biological information database with complex and clumsy structure and focuses on the theme of gene and miRNA, and it could make the research and teaching more convenient and efficient. Based on the B/S architecture, using Apache as a Web server, MySQL as coding language of database design and PHP as coding language of web design, a comprehensive database for laryngeal cancer-related genes was established, providing with the gene tables, protein tables, miRNA tables and clinical information tables of the patients with laryngeal cancer. The established database containsed 207 laryngeal cancer related genes, 243 proteins, 26 miRNAs, and their particular information such as mutations, methylations, diversified expressions, and the empirical references of laryngeal cancer relevant molecules. The database could be accessed and operated via the Internet, by which browsing and retrieval of the information were performed. The database were maintained and updated regularly. The database for laryngeal cancer related genes is resource-integrated and user-friendly, providing a genetic information query tool for the study of laryngeal cancer.

A Magnetic Petrology Database for Satellite Magnetic Anomaly Interpretations

NASA Astrophysics Data System (ADS)

Nazarova, K.; Wasilewski, P.; Didenko, A.; Genshaft, Y.; Pashkevich, I.

2002-05-01

A Magnetic Petrology Database (MPDB) is now being compiled at NASA/Goddard Space Flight Center in cooperation with Russian and Ukrainian Institutions. The purpose of this database is to provide the geomagnetic community with a comprehensive and user-friendly method of accessing magnetic petrology data via Internet for more realistic interpretation of satellite magnetic anomalies. Magnetic Petrology Data had been accumulated in NASA/Goddard Space Flight Center, United Institute of Physics of the Earth (Russia) and Institute of Geophysics (Ukraine) over several decades and now consists of many thousands of records of data in our archives. The MPDB was, and continues to be in big demand especially since recent launching in near Earth orbit of the mini-constellation of three satellites - Oersted (in 1999), Champ (in 2000), and SAC-C (in 2000) which will provide lithospheric magnetic maps with better spatial and amplitude resolution (about 1 nT). The MPDB is focused on lower crustal and upper mantle rocks and will include data on mantle xenoliths, serpentinized ultramafic rocks, granulites, iron quartzites and rocks from Archean-Proterozoic metamorphic sequences from all around the world. A substantial amount of data is coming from the area of unique Kursk Magnetic Anomaly and Kola Deep Borehole (which recovered 12 km of continental crust). A prototype MPDB can be found on the Geodynamics Branch web server of Goddard Space Flight Center at http://core2.gsfc.nasa.gov/terr_mag/magnpetr.html. The MPDB employs a searchable relational design and consists of 7 interrelated tables. The schema of database is shown at http://core2.gsfc.nasa.gov/terr_mag/doc.html. MySQL database server was utilized to implement MPDB. The SQL (Structured Query Language) is used to query the database. To present the results of queries on WEB and for WEB programming we utilized PHP scripting language and CGI scripts. The prototype MPDB is designed to search database by major satellite magnetic anomaly, tectonic structure, geographical location, rock type, magnetic properties, chemistry and reference, see http://core2.gsfc.nasa.gov/terr_mag/query1.html. The output of database is HTML structured table, text file, and downloadable file. This database will be very useful for studies of lithospheric satellite magnetic anomalies on the Earth and other terrestrial planets.

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,…

Metadata Dictionary Database: A Proposed Tool for Academic Library Metadata Management

ERIC Educational Resources Information Center

Southwick, Silvia B.; Lampert, Cory

2011-01-01

This article proposes a metadata dictionary (MDD) be used as a tool for metadata management. The MDD is a repository of critical data necessary for managing metadata to create "shareable" digital collections. An operational definition of metadata management is provided. The authors explore activities involved in metadata management in…

The Chandra Source Catalog 2.0: Interfaces

NASA Astrophysics Data System (ADS)

D'Abrusco, Raffaele; Zografou, Panagoula; Tibbetts, Michael; Allen, Christopher E.; Anderson, Craig S.; Budynkiewicz, Jamie A.; Burke, Douglas; Chen, Judy C.; Civano, Francesca Maria; Doe, Stephen M.; Evans, Ian N.; Evans, Janet D.; Fabbiano, Giuseppina; Gibbs, Danny G., II; Glotfelty, Kenny J.; Graessle, Dale E.; Grier, John D.; Hain, Roger; Hall, Diane M.; Harbo, Peter N.; Houck, John C.; Lauer, Jennifer L.; Laurino, Omar; Lee, Nicholas P.; Martínez-Galarza, Rafael; McCollough, Michael L.; McDowell, Jonathan C.; Miller, Joseph; McLaughlin, Warren; Morgan, Douglas L.; Mossman, Amy E.; Nguyen, Dan T.; Nichols, Joy S.; Nowak, Michael A.; Paxson, Charles; Plummer, David A.; Primini, Francis Anthony; Rots, Arnold H.; Siemiginowska, Aneta; Sundheim, Beth A.; Van Stone, David W.

2018-01-01

Easy-to-use, powerful public interfaces to access the wealth of information contained in any modern, complex astronomical catalog are fundamental to encourage its usage. In this poster,I present the public interfaces of the second Chandra Source Catalog (CSC2). CSC2 is the most comprehensive catalog of X-ray sources detected by Chandra, thanks to the inclusion of Chandra observations public through the end of 2014 and to methodological advancements. CSC2 provides measured properties for a large number of sources that sample the X-ray sky at fainter levels than the previous versions of the CSC, thanks to the stacking of single overlapping observations within 1’ before source detection. Sources from stacks are then crossmatched, if multiple stacks cover the same area of the sky, to create a list of unique, optimal CSC2 sources. The properties of sources detected in each single stack and each single observation are also measured. The layered structure of the CSC2 catalog is mirrored in the organization of the CSC2 database, consisting of three tables containing all properties for the unique stacked sources (“Master Source”), single stack sources (“Stack Source”) and sources in any single observation (“Observation Source”). These tables contain estimates of the position, flags, extent, significances, fluxes, spectral properties and variability (and associated errors) for all classes of sources. The CSC2 also includes source region and full-field data products for all master sources, stack sources and observation sources: images, photon event lists, light curves and spectra.CSCview, the main interface to the CSC2 source properties and data products, is a GUI tool that allows to build queries based on the values of all properties contained in CSC2 tables, query the catalog, inspect the returned table of source properties, browse and download the associated data products. I will also introduce the suite of command-line interfaces to CSC2 that can be used in alternative to CSCview, and will present the concept for an additional planned cone-search web-based interface.This work has been supported by NASA under contract NAS 8-03060 to the Smithsonian Astrophysical Observatory for operation of the Chandra X-ray Center.

Fast and Accurate Metadata Authoring Using Ontology-Based Recommendations.

PubMed

Martínez-Romero, Marcos; O'Connor, Martin J; Shankar, Ravi D; Panahiazar, Maryam; Willrett, Debra; Egyedi, Attila L; Gevaert, Olivier; Graybeal, John; Musen, Mark A

2017-01-01

In biomedicine, high-quality metadata are crucial for finding experimental datasets, for understanding how experiments were performed, and for reproducing those experiments. Despite the recent focus on metadata, the quality of metadata available in public repositories continues to be extremely poor. A key difficulty is that the typical metadata acquisition process is time-consuming and error prone, with weak or nonexistent support for linking metadata to ontologies. There is a pressing need for methods and tools to speed up the metadata acquisition process and to increase the quality of metadata that are entered. In this paper, we describe a methodology and set of associated tools that we developed to address this challenge. A core component of this approach is a value recommendation framework that uses analysis of previously entered metadata and ontology-based metadata specifications to help users rapidly and accurately enter their metadata. We performed an initial evaluation of this approach using metadata from a public metadata repository.

Fast and Accurate Metadata Authoring Using Ontology-Based Recommendations

PubMed Central

Martínez-Romero, Marcos; O’Connor, Martin J.; Shankar, Ravi D.; Panahiazar, Maryam; Willrett, Debra; Egyedi, Attila L.; Gevaert, Olivier; Graybeal, John; Musen, Mark A.

2017-01-01

In biomedicine, high-quality metadata are crucial for finding experimental datasets, for understanding how experiments were performed, and for reproducing those experiments. Despite the recent focus on metadata, the quality of metadata available in public repositories continues to be extremely poor. A key difficulty is that the typical metadata acquisition process is time-consuming and error prone, with weak or nonexistent support for linking metadata to ontologies. There is a pressing need for methods and tools to speed up the metadata acquisition process and to increase the quality of metadata that are entered. In this paper, we describe a methodology and set of associated tools that we developed to address this challenge. A core component of this approach is a value recommendation framework that uses analysis of previously entered metadata and ontology-based metadata specifications to help users rapidly and accurately enter their metadata. We performed an initial evaluation of this approach using metadata from a public metadata repository. PMID:29854196

Airborne Network Data Availability Using Peer to Peer Database Replication on a Distributed Hash Table

DTIC Science & Technology

2013-03-01

DSR Dynamic Source Routing DSSS Direct -sequence spread spectrum GUID Globally Unique ID MANET Mobile Ad-hoc Network NS3 Network Simulator 3 OLSR...networking schemes for safe maneuvering and data communication. Imagine needing to maintain an operational picture of an overall environment using a...as simple as O(n) where every node is sequentially queried to O log(n), or O(1). These schemes will be discussed with each individual DHT. Four of the

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.

Simplified Metadata Curation via the Metadata Management Tool

NASA Astrophysics Data System (ADS)

Shum, D.; Pilone, D.

2015-12-01

The Metadata Management Tool (MMT) is the newest capability developed as part of NASA Earth Observing System Data and Information System's (EOSDIS) efforts to simplify metadata creation and improve metadata quality. The MMT was developed via an agile methodology, taking into account inputs from GCMD's science coordinators and other end-users. In its initial release, the MMT uses the Unified Metadata Model for Collections (UMM-C) to allow metadata providers to easily create and update collection records in the ISO-19115 format. Through a simplified UI experience, metadata curators can create and edit collections without full knowledge of the NASA Best Practices implementation of ISO-19115 format, while still generating compliant metadata. More experienced users are also able to access raw metadata to build more complex records as needed. In future releases, the MMT will build upon recent work done in the community to assess metadata quality and compliance with a variety of standards through application of metadata rubrics. The tool will provide users with clear guidance as to how to easily change their metadata in order to improve their quality and compliance. Through these features, the MMT allows data providers to create and maintain compliant and high quality metadata in a short amount of time.

Enriched Video Semantic Metadata: Authorization, Integration, and Presentation.

ERIC Educational Resources Information Center

Mu, Xiangming; Marchionini, Gary

2003-01-01

Presents an enriched video metadata framework including video authorization using the Video Annotation and Summarization Tool (VAST)-a video metadata authorization system that integrates both semantic and visual metadata-- metadata integration, and user level applications. Results demonstrated that the enriched metadata were seamlessly…

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

Automated Data Submission for the Data Center

NASA Astrophysics Data System (ADS)

Wright, D.; Beaty, T.; Wei, Y.; Shanafield, H.; Santhana Vannan, S. K.

2014-12-01

Data centers struggle with difficulties related to data submission. Data are acquired through many avenues by many people. Many data submission activities involve intensive manual processes. During the submission process, data end up on varied storage devices. The situation can easily become chaotic. Collecting information on the status of pending data sets is arduous. For data providers, the submission process can be inconsistent and confusing. Scientists generally provide data from previous projects, and archival can be a low priority. Incomplete or poor documentation accompanies many data sets. However, complicated questionnaires deter busy data providers. At the ORNL DAAC, we have semi-automated the data set submission process to create a uniform data product and provide a consistent data provider experience. The formalized workflow makes archival faster for the data center and data set submission easier for data providers. Software modules create a flexible, reusable submission package. Formalized data set submission provides several benefits to the data center. A single data upload area provides one point of entry and ensures data are stored in a consistent location. A central dashboard records pending data set submissions in a single table and simplifies reporting. Flexible role management allows team members to readily coordinate and increases efficiency. Data products and metadata become uniform and easily maintained. As data and metadata standards change, modules can be modified or re-written without affecting workflow. While each data center has unique challenges, the data ingestion process is generally the same: get data from the provider, scientist, or project and capture metadata pertinent to that data. The ORNL DAAC data set submission workflow and software modules can be reused entirely or in part by other data centers looking for a data set submission solution. These data set submission modules will be available on NASA's Earthdata Code Collaborative and by request.

NERIES: Seismic Data Gateways and User Composed Datasets Metadata Management

NASA Astrophysics Data System (ADS)

Spinuso, Alessandro; Trani, Luca; Kamb, Linus; Frobert, Laurent

2010-05-01

One of the NERIES EC project main objectives is to establish and improve the networking of seismic waveform data exchange and access among four main data centers in Europe: INGV, GFZ, ORFEUS and IPGP. Besides the implementation of the data backbone, several investigations and developments have been conducted in order to offer to the users the data available from this network, either programmatically or interactively. One of the challenges is to understand how to enable users` activities such as discovering, aggregating, describing and sharing datasets to obtain a decrease in the replication of similar data queries towards the network, exempting the data centers to guess and create useful pre-packed products. We`ve started to transfer this task more and more towards the users community, where the users` composed data products could be extensively re-used. The main link to the data is represented by a centralized webservice (SeismoLink) acting like a single access point to the whole data network. Users can download either waveform data or seismic station inventories directly from their own software routines by connecting to this webservice, which routes the request to the data centers. The provenance of the data is maintained and transferred to the users in the form of URIs, that identify the dataset and implicitly refer to the data provider. SeismoLink, combined with other webservices (eg EMSC-QuakeML earthquakes catalog service), is used from a community gateway such as the NERIES web portal (http://www.seismicportal.eu). Here the user interacts with a map based portlet which allows the dynamic composition of a data product, binding seismic event`s parameters with a set of seismic stations. The requested data is collected by the back-end processes of the portal, preserved and offered to the user in a personal data cart, where metadata can be generated interactively on-demand. The metadata, expressed in RDF, can also be remotely ingested. They offer rating, provenance and user annotation properties. Once generated they are included into a proprietary taxonomy, used by the overall architecture of the web portal. The metadata are made available through a SPARQL endpoint, thus allowing the datasets to be aggregated and shared among users in a meaningful way, enabling at the same time the development of third party visualization tools beyond the portal infrastructure. The SEE-GRID-SCI and the JISC-funded RapidSeis projects investigate the usage of this framework to enable the waveform data processing over the Grid.

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.

Current Development at the Southern California Earthquake Data Center (SCEDC)

NASA Astrophysics Data System (ADS)

Appel, V. L.; Clayton, R. W.

2005-12-01

Over the past year, the SCEDC completed or is near completion of three featured projects: Station Information System (SIS) Development: The SIS will provide users with an interface into complete and accurate station metadata for all current and historic data at the SCEDC. The goal of this project is to develop a system that can interact with a single database source to enter, update and retrieve station metadata easily and efficiently. The system will provide accurate station/channel information for active stations to the SCSN real-time processing system, as will as station/channel information for stations that have parametric data at the SCEDC i.e., for users retrieving data via STP. Additionally, the SIS will supply information required to generate dataless SEED and COSMOS V0 volumes and allow stations to be added to the system with a minimum, but incomplete set of information using predefined defaults that can be easily updated as more information becomes available. Finally, the system will facilitate statewide metadata exchange for both real-time processing and provide a common approach to CISN historic station metadata. Moment Tensor Solutions: The SCEDC is currently archiving and delivering Moment Magnitudes and Moment Tensor Solutions (MTS) produced by the SCSN in real-time and post-processing solutions for events spanning back to 1999. The automatic MTS runs on all local events with magnitudes > 3.0, and all regional events > 3.5. The distributed solution automatically creates links from all USGS Simpson Maps to a text e-mail summary solution, creates a .gif image of the solution, and updates the moment tensor database tables at the SCEDC. Searchable Scanned Waveforms Site: The Caltech Seismological Lab has made available 12,223 scanned images of pre-digital analog recordings of major earthquakes recorded in Southern California between 1962 and 1992 at http://www.data.scec.org/research/scans/. The SCEDC has developed a searchable web interface that allows users to search the available files, select multiple files for download and then retrieve a zipped file containing the results. Scanned images of paper records for M>3.5 southern California earthquakes and several significant teleseisms are available for download via the SCEDC through this search tool.

Parsing GML data based on integrative GML syntactic and semantic schemas database

NASA Astrophysics Data System (ADS)

Miao, Lizhi; Zhang, Shuliang; Lu, Guonian; Gao, Xiaoli; Jiao, Donglai; Gan, Jiayan

2007-06-01

This paper proposes a new method to parse various application schemas of Geography Markup Language (GML) for understanding syntax and semantic of their element and type in order to implement uniform interpretation of the same GML instance data among diverse users. The proposed method generates an Integrative GML Syntactic and Semantic Schemas Database (IGSSSDB) from GML3.1 core schemas and corresponding application schema. This paper parses GML data based on IGSSSDB, which is composed of syntactic and semantic information, nesting information and mapping rules of GML core schemas and application schemas. Three kinds of relational tables are designed for storing information from schemas when constructing IGSSSDB. Those are info tables for schemas included and namespace imported in application schemas, tables for information related to schemas and catalog tables of core schemas. In relational tables, we propose to use homologous regular expression to describe model of elements and complex types in schemas, which can ensure model complete and readable. Based on IGSSSDB, we design and develop many APIs to implement GML data parsing, and can process syntactic and semantic information of GML data from diverse fields and users. At the latter part of this paper, test study is implemented to show that the proposed method is feasible and appropriate for parsing GML data. Also, it founds a good basis for future GML data studies such as storage, index and query etc.

Computer systems and methods for the query and visualization of multidimensional databases

DOEpatents

Stolte, Chris; Tang, Diane L; Hanrahan, Patrick

2014-04-29

In response to a user request, a computer generates a graphical user interface on a computer display. A schema information region of the graphical user interface includes multiple operand names, each operand name associated with one or more fields of a multi-dimensional database. A data visualization region of the graphical user interface includes multiple shelves. Upon detecting a user selection of the operand names and a user request to associate each user-selected operand name with a respective shelf in the data visualization region, the computer generates a visual table in the data visualization region in accordance with the associations between the operand names and the corresponding shelves. The visual table includes a plurality of panes, each pane having at least one axis defined based on data for the fields associated with a respective operand name.

Computer systems and methods for the query and visualization of multidimensional databases

DOEpatents

Stolte, Chris [Palo Alto, CA; Tang, Diane L [Palo Alto, CA; Hanrahan, Patrick [Portola Valley, CA

2011-02-01

In response to a user request, a computer generates a graphical user interface on a computer display. A schema information region of the graphical user interface includes multiple operand names, each operand name associated with one or more fields of a multi-dimensional database. A data visualization region of the graphical user interface includes multiple shelves. Upon detecting a user selection of the operand names and a user request to associate each user-selected operand name with a respective shelf in the data visualization region, the computer generates a visual table in the data visualization region in accordance with the associations between the operand names and the corresponding shelves. The visual table includes a plurality of panes, each pane having at least one axis defined based on data for the fields associated with a respective operand name.

Computer systems and methods for the query and visualization of multidimensional databases

DOEpatents

Stolte, Chris [Palo Alto, CA; Tang, Diane L [Palo Alto, CA; Hanrahan, Patrick [Portola Valley, CA

2012-03-20

In response to a user request, a computer generates a graphical user interface on a computer display. A schema information region of the graphical user interface includes multiple operand names, each operand name associated with one or more fields of a multi-dimensional database. A data visualization region of the graphical user interface includes multiple shelves. Upon detecting a user selection of the operand names and a user request to associate each user-selected operand name with a respective shelf in the data visualization region, the computer generates a visual table in the data visualization region in accordance with the associations between the operand names and the corresponding shelves. The visual table includes a plurality of panes, each pane having at least one axis defined based on data for the fields associated with a respective operand name.

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

STBase: One Million Species Trees for Comparative Biology

PubMed Central

McMahon, Michelle M.; Deepak, Akshay; Fernández-Baca, David; Boss, Darren; Sanderson, Michael J.

2015-01-01

Comprehensively sampled phylogenetic trees provide the most compelling foundations for strong inferences in comparative evolutionary biology. Mismatches are common, however, between the taxa for which comparative data are available and the taxa sampled by published phylogenetic analyses. Moreover, many published phylogenies are gene trees, which cannot always be adapted immediately for species level comparisons because of discordance, gene duplication, and other confounding biological processes. A new database, STBase, lets comparative biologists quickly retrieve species level phylogenetic hypotheses in response to a query list of species names. The database consists of 1 million single- and multi-locus data sets, each with a confidence set of 1000 putative species trees, computed from GenBank sequence data for 413,000 eukaryotic taxa. Two bodies of theoretical work are leveraged to aid in the assembly of multi-locus concatenated data sets for species tree construction. First, multiply labeled gene trees are pruned to conflict-free singly-labeled species-level trees that can be combined between loci. Second, impacts of missing data in multi-locus data sets are ameliorated by assembling only decisive data sets. Data sets overlapping with the user’s query are ranked using a scheme that depends on user-provided weights for tree quality and for taxonomic overlap of the tree with the query. Retrieval times are independent of the size of the database, typically a few seconds. Tree quality is assessed by a real-time evaluation of bootstrap support on just the overlapping subtree. Associated sequence alignments, tree files and metadata can be downloaded for subsequent analysis. STBase provides a tool for comparative biologists interested in exploiting the most relevant sequence data available for the taxa of interest. It may also serve as a prototype for future species tree oriented databases and as a resource for assembly of larger species phylogenies from precomputed trees. PMID:25679219

Conservation-Oriented Hbim. The Bimexplorer Web Tool

NASA Astrophysics Data System (ADS)

Quattrini, R.; Pierdicca, R.; Morbidoni, C.; Malinverni, E. S.

2017-05-01

The application of (H)BIM within the domain of Architectural Historical Heritage has huge potential that can be even exploited within the restoration domain. The work presents a novel approach to solve the widespread interoperability issue related to the data enrichment in BIM environment, by developing and testing a web tool based on a specific workflow experienced choosing as the case study a Romanic church in Portonovo, Ancona, Italy. Following the need to make the data, organized in a BIM environment, usable for the different actors involved in the restoration phase, we have created a pipeline that take advantage of BIM existing platforms and semantic-web technologies, enabling the end user to query a repository composed of semantically structured data. The pipeline of work consists in four major steps: i) modelling an ontology with the main information needs for the domain of interest, providing a data structure that can be leveraged to inform the data-enrichment phase and, later, to meaningfully query the data; ii) data enrichment, by creating a set of shared parameters reflecting the properties in our domain ontology; iii) structuring data in a machine-readable format (through a data conversion) to represent the domain (ontology) and analyse data of specific buildings respectively; iv) development of a demonstrative data exploration web application based on the faceted browsing paradigm and allowing to exploit both structured metadata and 3D visualization. The application can be configured by a domain expert to reflect a given domain ontology, and used by an operator to query and explore the data in a more efficient and reliable way. With the proposed solution the analysis of data can be reused together with the 3D model, providing the end-user with a non proprietary tool; in this way, the planned maintenance or the restoration project became more collaborative and interactive, optimizing the whole process of HBIM data collection.

A geodata warehouse: Using denormalisation techniques as a tool for delivering spatially enabled integrated geological information to geologists

NASA Astrophysics Data System (ADS)

Kingdon, Andrew; Nayembil, Martin L.; Richardson, Anne E.; Smith, A. Graham

2016-11-01

New requirements to understand geological properties in three dimensions have led to the development of PropBase, a data structure and delivery tools to deliver this. At the BGS, relational database management systems (RDBMS) has facilitated effective data management using normalised subject-based database designs with business rules in a centralised, vocabulary controlled, architecture. These have delivered effective data storage in a secure environment. However, isolated subject-oriented designs prevented efficient cross-domain querying of datasets. Additionally, the tools provided often did not enable effective data discovery as they struggled to resolve the complex underlying normalised structures providing poor data access speeds. Users developed bespoke access tools to structures they did not fully understand sometimes delivering them incorrect results. Therefore, BGS has developed PropBase, a generic denormalised data structure within an RDBMS to store property data, to facilitate rapid and standardised data discovery and access, incorporating 2D and 3D physical and chemical property data, with associated metadata. This includes scripts to populate and synchronise the layer with its data sources through structured input and transcription standards. A core component of the architecture includes, an optimised query object, to deliver geoscience information from a structure equivalent to a data warehouse. This enables optimised query performance to deliver data in multiple standardised formats using a web discovery tool. Semantic interoperability is enforced through vocabularies combined from all data sources facilitating searching of related terms. PropBase holds 28.1 million spatially enabled property data points from 10 source databases incorporating over 50 property data types with a vocabulary set that includes 557 property terms. By enabling property data searches across multiple databases PropBase has facilitated new scientific research, previously considered impractical. PropBase is easily extended to incorporate 4D data (time series) and is providing a baseline for new "big data" monitoring projects.

Ingredients for an Integrated Dinner: Parsley, Sage, Rosemary and Thyme

NASA Astrophysics Data System (ADS)

Baumann, Peter

2013-04-01

In 1966, Simon and Garfunkel combined the English traditional "Scarborough Fair" with a counter melody. This is one of the manifold techniques of the Kontrapunktik described by Bach around 1745 in "The Art of the Fugue": combining completely different and seemingly independent melodies (or motifs) into a coherent piece of music, pleasant for the audience. This achievement, transposed into Computer Science, could be of great benefit for geo services as we look at the currently disparate situation: On the one hand, we have metadata - traditionally, they are understood as being small in volume, but rich in content and semantics, and flexibly queryable through the rich body of technologies established over several decades of database research, centering around query languages like SQL. On the other hand, we have data themselves, such as remote sensing and other measured and observed data sets - they are considered difficult to interpret, semantic-poor, and only for clumsy download, as they are the main constituent of what we today call Big Data. The traditional advantages of databases, such as information integration, query flexibility, and scalability seem to be unavailable. These are the melodies that require a kontrapunctic harmonization, leading to a Holy Grail where different information categories enjoy individually tailored support, while an overall integrating framework allows seamless and convenient access and processing by the user. Most of the data categories to be integrated are well known in fact: ontologies, geospatial meshes, spatiotemporal arrays, and free text constitute major ingredients in this orchestration. For many of them, isolated solutions have been presented, and for some of them (like ontologies and text) integration has been achieved already; a complete harmonic integration, though, is still lacking as of today. In our talk, we detail our vision on such integration through query models and languages which merge established concepts and novel paradigms in a harmonic way. We present the EarthServer initiative which has set out to demonstrate flexible ad-hoc processing and filtering on massive Earth data sets.

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 Demonstrator for the European Plate Observing System (EPOS)

NASA Astrophysics Data System (ADS)

Hoffmann, T. L.; Euteneuer, F.; Ulbricht, D.; Lauterjung, J.; Bailo, D.; Jeffery, K. G.

2014-12-01

An important outcome of the 4-year Preparatory Phase of the ESFRI project European Plate Observing System (EPOS) was the development and first implementation of the EPOS Demonstrator by the project's ICT Working Group 7. The Demonstrator implements the vertical integration of the three-layer architectural scheme for EPOS, connecting the Integrated Core Services (ICS), Thematic Core Services (TCS) and the National Research Infrastructures (NRI). The demonstrator provides a single GUI with central key discovery and query functionalities, based on already existing services by the seismic, geologic and geodetic communities. More specifically the seismic services of the Demonstrator utilize webservices and APIs for data and discovery of raw seismic data (FDSN webservices by the EIDA Network), events (Geoportal by EMSC) and analytical data products (e.g., hazard maps by EFEHR via OGC WMS). For geologic services, the EPOS Demonstrator accesses OneGeology Europe which serves the community with geologic maps and point information via OGC webservices. The Demonstrator also provides access to raw geodetic data via a newly developed universal tool called GSAC. The Demonstrator itself resembles the future Integrated Core Service (ICS) and provides direct access to the end user. Its core functionality lies in a metadata catalogue, which serves as the central information hub and stores information about all RIs, related persons, projects, financial background and technical access information. The database schema of the catalogue is based on CERIF, which has been slightly adapted. Currently, the portal provides basic query functions as well as cross domain search. [www.epos.cineca.it

iReceptor: A platform for querying and analyzing antibody/B-cell and T-cell receptor repertoire data across federated repositories.

PubMed

Corrie, Brian D; Marthandan, Nishanth; Zimonja, Bojan; Jaglale, Jerome; Zhou, Yang; Barr, Emily; Knoetze, Nicole; Breden, Frances M W; Christley, Scott; Scott, Jamie K; Cowell, Lindsay G; Breden, Felix

2018-07-01

Next-generation sequencing allows the characterization of the adaptive immune receptor repertoire (AIRR) in exquisite detail. These large-scale AIRR-seq data sets have rapidly become critical to vaccine development, understanding the immune response in autoimmune and infectious disease, and monitoring novel therapeutics against cancer. However, at present there is no easy way to compare these AIRR-seq data sets across studies and institutions. The ability to combine and compare information for different disease conditions will greatly enhance the value of AIRR-seq data for improving biomedical research and patient care. The iReceptor Data Integration Platform (gateway.ireceptor.org) provides one implementation of the AIRR Data Commons envisioned by the AIRR Community (airr-community.org), an initiative that is developing protocols to facilitate sharing and comparing AIRR-seq data. The iReceptor Scientific Gateway links distributed (federated) AIRR-seq repositories, allowing sequence searches or metadata queries across multiple studies at multiple institutions, returning sets of sequences fulfilling specific criteria. We present a review of the development of iReceptor, and how it fits in with the general trend toward sharing genomic and health data, and the development of standards for describing and reporting AIRR-seq data. Researchers interested in integrating their repositories of AIRR-seq data into the iReceptor Platform are invited to contact support@ireceptor.org. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

BAID: The Barrow Area Information Database - an interactive web mapping portal and cyberinfrastructure for scientific activities in the vicinity of Barrow, Alaska

NASA Astrophysics Data System (ADS)

Cody, R. P.; Kassin, A.; Gaylord, A. G.; Tweedie, C. E.

2013-12-01

In 2013, the Barrow Area Information Database (BAID, www.baid.utep.edu) project resumed field operations in Barrow, AK. The Barrow area of northern Alaska is one of the most intensely researched locations in the Arctic. BAID is a cyberinfrastructure (CI) that details much of the historic and extant research undertaken within in the Barrow region in a suite of interactive web-based mapping and information portals (geobrowsers). The BAID user community and target audience for BAID is diverse and includes research scientists, science logisticians, land managers, educators, students, and the general public. BAID contains information on more than 11,000 Barrow area research sites that extend back to the 1940's and more than 640 remote sensing images and geospatial datasets. In a web-based setting, users can zoom, pan, query, measure distance, and save or print maps and query results. Data are described with metadata that meet Federal Geographic Data Committee standards and are archived at the University Corporation for Atmospheric Research Earth Observing Laboratory (EOL) where non-proprietary BAID data can be freely downloaded. Highlights for the 2013 season include the addition of more than 2000 additional research sites, providing differential global position system (dGPS) support to visiting scientists, surveying over 80 miles of coastline to document rates of erosion, training of local GIS personal, deployment of a wireless sensor network, and substantial upgrades to the BAID website and web mapping applications.

Common Data Model for Neuroscience Data and Data Model Exchange

PubMed Central

Gardner, Daniel; Knuth, Kevin H.; Abato, Michael; Erde, Steven M.; White, Thomas; DeBellis, Robert; Gardner, Esther P.

2001-01-01

Objective: Generalizing the data models underlying two prototype neurophysiology databases, the authors describe and propose the Common Data Model (CDM) as a framework for federating a broad spectrum of disparate neuroscience information resources. Design: Each component of the CDM derives from one of five superclasses—data, site, method, model, and reference—or from relations defined between them. A hierarchic attribute-value scheme for metadata enables interoperability with variable tree depth to serve specific intra- or broad inter-domain queries. To mediate data exchange between disparate systems, the authors propose a set of XML-derived schema for describing not only data sets but data models. These include biophysical description markup language (BDML), which mediates interoperability between data resources by providing a meta-description for the CDM. Results: The set of superclasses potentially spans data needs of contemporary neuroscience. Data elements abstracted from neurophysiology time series and histogram data represent data sets that differ in dimension and concordance. Site elements transcend neurons to describe subcellular compartments, circuits, regions, or slices; non-neuroanatomic sites include sequences to patients. Methods and models are highly domain-dependent. Conclusions: True federation of data resources requires explicit public description, in a metalanguage, of the contents, query methods, data formats, and data models of each data resource. Any data model that can be derived from the defined superclasses is potentially conformant and interoperability can be enabled by recognition of BDML-described compatibilities. Such metadescriptions can buffer technologic changes. PMID:11141510

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.

VisFlow - Web-based Visualization Framework for Tabular Data with a Subset Flow Model.

PubMed

Yu, Bowen; Silva, Claudio T

2017-01-01

Data flow systems allow the user to design a flow diagram that specifies the relations between system components which process, filter or visually present the data. Visualization systems may benefit from user-defined data flows as an analysis typically consists of rendering multiple plots on demand and performing different types of interactive queries across coordinated views. In this paper, we propose VisFlow, a web-based visualization framework for tabular data that employs a specific type of data flow model called the subset flow model. VisFlow focuses on interactive queries within the data flow, overcoming the limitation of interactivity from past computational data flow systems. In particular, VisFlow applies embedded visualizations and supports interactive selections, brushing and linking within a visualization-oriented data flow. The model requires all data transmitted by the flow to be a data item subset (i.e. groups of table rows) of some original input table, so that rendering properties can be assigned to the subset unambiguously for tracking and comparison. VisFlow features the analysis flexibility of a flow diagram, and at the same time reduces the diagram complexity and improves usability. We demonstrate the capability of VisFlow on two case studies with domain experts on real-world datasets showing that VisFlow is capable of accomplishing a considerable set of visualization and analysis tasks. The VisFlow system is available as open source on GitHub.

Semantic Integration for Marine Science Interoperability Using Web Technologies

NASA Astrophysics Data System (ADS)

Rueda, C.; Bermudez, L.; Graybeal, J.; Isenor, A. W.

2008-12-01

The Marine Metadata Interoperability Project, MMI (http://marinemetadata.org) promotes the exchange, integration, and use of marine data through enhanced data publishing, discovery, documentation, and accessibility. A key effort is the definition of an Architectural Framework and Operational Concept for Semantic Interoperability (http://marinemetadata.org/sfc), which is complemented with the development of tools that realize critical use cases in semantic interoperability. In this presentation, we describe a set of such Semantic Web tools that allow performing important interoperability tasks, ranging from the creation of controlled vocabularies and the mapping of terms across multiple ontologies, to the online registration, storage, and search services needed to work with the ontologies (http://mmisw.org). This set of services uses Web standards and technologies, including Resource Description Framework (RDF), Web Ontology language (OWL), Web services, and toolkits for Rich Internet Application development. We will describe the following components: MMI Ontology Registry: The MMI Ontology Registry and Repository provides registry and storage services for ontologies. Entries in the registry are associated with projects defined by the registered users. Also, sophisticated search functions, for example according to metadata items and vocabulary terms, are provided. Client applications can submit search requests using the WC3 SPARQL Query Language for RDF. Voc2RDF: This component converts an ASCII comma-delimited set of terms and definitions into an RDF file. Voc2RDF facilitates the creation of controlled vocabularies by using a simple form-based user interface. Created vocabularies and their descriptive metadata can be submitted to the MMI Ontology Registry for versioning and community access. VINE: The Vocabulary Integration Environment component allows the user to map vocabulary terms across multiple ontologies. Various relationships can be established, for example exactMatch, narrowerThan, and subClassOf. VINE can compute inferred mappings based on the given associations. Attributes about each mapping, like comments and a confidence level, can also be included. VINE also supports registering and storing resulting mapping files in the Ontology Registry. The presentation will describe the application of semantic technologies in general, and our planned applications in particular, to solve data management problems in the marine and environmental sciences.

Similarity analysis of spectra obtained via reflectance spectrometry in legal medicine.

PubMed

Belenki, Liudmila; Sterzik, Vera; Bohnert, Michael

2014-02-01

In the present study, a series of reflectance spectra of postmortem lividity, pallor, and putrefaction-affected skin for 195 investigated cases in the course of cooling down the corpse has been collected. The reflectance spectrometric measurements were stored together with their respective metadata in a MySQL database. The latter has been managed via a scientific information repository. We propose similarity measures and a criterion of similarity that capture similar spectra recorded at corpse skin. We systematically clustered reflectance spectra from the database as well as their metadata, such as case number, age, sex, skin temperature, duration of cooling, and postmortem time, with respect to the given criterion of similarity. Altogether, more than 500 reflectance spectra have been pairwisely compared. The measures that have been used to compare a pair of reflectance curve samples include the Euclidean distance between curves and the Euclidean distance between derivatives of the functions represented by the reflectance curves at the same wavelengths in the spectral range of visible light between 380 and 750 nm. For each case, using the recorded reflectance curves and the similarity criterion, the postmortem time interval during which a characteristic change in the shape of reflectance spectrum takes place is estimated. The latter is carried out via a software package composed of Java, Python, and MatLab scripts that query the MySQL database. We show that in legal medicine, matching and clustering of reflectance curves obtained by means of reflectance spectrometry with respect to a given criterion of similarity can be used to estimate the postmortem interval.

TransAtlasDB: an integrated database connecting expression data, metadata and variants

PubMed Central

Adetunji, Modupeore O; Lamont, Susan J; Schmidt, Carl J

2018-01-01

Abstract High-throughput transcriptome sequencing (RNAseq) is the universally applied method for target-free transcript identification and gene expression quantification, generating huge amounts of data. The constraint of accessing such data and interpreting results can be a major impediment in postulating suitable hypothesis, thus an innovative storage solution that addresses these limitations, such as hard disk storage requirements, efficiency and reproducibility are paramount. By offering a uniform data storage and retrieval mechanism, various data can be compared and easily investigated. We present a sophisticated system, TransAtlasDB, which incorporates a hybrid architecture of both relational and NoSQL databases for fast and efficient data storage, processing and querying of large datasets from transcript expression analysis with corresponding metadata, as well as gene-associated variants (such as SNPs) and their predicted gene effects. TransAtlasDB provides the data model of accurate storage of the large amount of data derived from RNAseq analysis and also methods of interacting with the database, either via the command-line data management workflows, written in Perl, with useful functionalities that simplifies the complexity of data storage and possibly manipulation of the massive amounts of data generated from RNAseq analysis or through the web interface. The database application is currently modeled to handle analyses data from agricultural species, and will be expanded to include more species groups. Overall TransAtlasDB aims to serve as an accessible repository for the large complex results data files derived from RNAseq gene expression profiling and variant analysis. Database URL: https://modupeore.github.io/TransAtlasDB/ PMID:29688361

One Click to the Cosmos: The AstroPix Image Archive

NASA Astrophysics Data System (ADS)

Hurt, Robert L.; Llamas, J.; Squires, G. K.; Brinkworth, C.; X-ray Center, Chandra; ESO/ESA; Science Center, Spitzer; STScI

2013-01-01

Imagine a single website that acts as a portal to the entire wealth of public imagery spanning the world's observatories. This is the goal of the AstroPix project (astropix.ipac.caltech.edu), and you can use it today! Although still in a beta development state, this past year has seen the inclusion of thousands of images spanning some of the most prominent observatories in the world, including Chandra, ESO, Galex, Herschel, Hubble, Spitzer, and WISE, with more on the way. The archive is unique as it is built around the Astronomical Visualization Metadata (AVM) standard, which captures the rich contextual information for each image. This ranges from titles and descriptions, to color representations and observation details, to sky coordinates. AVM enables AstroPix imagery to be used in a variety of unique ways that benefit formal and informal education as well as astronomers and the general public. Visitors to Astropix can search the database using simple free-text queries, or use a structured search (similar to "Smart Playlists" found in iTunes, for example). We are also developing public application programming interfaces (APIs) to allow third party software and websites to access the growing content for a variety of uses (planetarium software, museum kiosks, mobile apps, and creative web interfaces, to name a few). Contributing image assets to AstroPix is as easy as tagging the images with the relevant metadata and including the web links to the images in a simple RSS feed. We will cover some of the latest information about tools to contribute images to AstroPix and ways to use the site.

Evaluating and Evolving Metadata in Multiple Dialects

NASA Astrophysics Data System (ADS)

Kozimor, J.; Habermann, T.; Powers, L. A.; Gordon, S.

2016-12-01

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. This situation has led to the development of metadata repositories that can ingest and output metadata in multiple dialects. As an operational example, the NASA Common Metadata Repository (CMR) includes three different metadata dialects (DIF, ECHO, and ISO 19115-2). These systems raise a new question for metadata providers: if I have a choice of metadata dialects, which should I use and how do I make that decision? We have developed a collection of metadata evaluation tools that can be used to evaluate metadata records in many dialects for completeness with respect to recommendations from many organizations and communities. We have applied these tools to over 8000 collection and granule metadata records in four different dialects. This large collection of identical content in multiple dialects enables us to address questions about metadata and dialect evolution and to answer those questions quantitatively. We will describe those tools and results from evaluating the NASA CMR metadata collection.

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+.

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.

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).

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.

A data colocation grid framework for big data medical image processing: backend design

NASA Astrophysics Data System (ADS)

Bao, Shunxing; Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J.; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A.

2018-03-01

When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework's performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop and HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative small. The source code and interfaces have been made publicly available.

A Data Colocation Grid Framework for Big Data Medical Image Processing: Backend Design.

PubMed

Bao, Shunxing; Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A

2018-03-01

When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework's performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop & HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative small. The source code and interfaces have been made publicly available.

A Data Colocation Grid Framework for Big Data Medical Image Processing: Backend Design

PubMed Central

Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J.; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A.

2018-01-01

When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework’s performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop & HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative small. The source code and interfaces have been made publicly available. PMID:29887668

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.

Efficient Execution Methods of Pivoting for Bulk Extraction of Entity-Attribute-Value-Modeled Data

PubMed Central

Luo, Gang; Frey, Lewis J.

2017-01-01

Entity-attribute-value (EAV) tables are widely used to store data in electronic medical records and clinical study data management systems. Before they can be used by various analytical (e.g., data mining and machine learning) programs, EAV-modeled data usually must be transformed into conventional relational table format through pivot operations. This time-consuming and resource-intensive process is often performed repeatedly on a regular basis, e.g., to provide a daily refresh of the content in a clinical data warehouse. Thus, it would be beneficial to make pivot operations as efficient as possible. In this paper, we present three techniques for improving the efficiency of pivot operations: 1) filtering out EAV tuples related to unneeded clinical parameters early on; 2) supporting pivoting across multiple EAV tables; and 3) conducting multi-query optimization. We demonstrate the effectiveness of our techniques through implementation. We show that our optimized execution method of pivoting using these techniques significantly outperforms the current basic execution method of pivoting. Our techniques can be used to build a data extraction tool to simplify the specification of and improve the efficiency of extracting data from the EAV tables in electronic medical records and clinical study data management systems. PMID:25608318

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.

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.

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.

searchSCF: Using MongoDB to Enable Richer Searches of Locally Hosted Science Data Repositories

NASA Astrophysics Data System (ADS)

Knosp, B.

2016-12-01

Science teams today are in the unusual position of almost having too much data available to them. Modern sensors and models are capable of outputting terabytes of data per day, which can make it difficult to find specific subsets of data. The sheer size of files can also make it time consuming to retrieve this big data from national data archive centers. Thus, many science teams choose to store what data they can on their local systems, but they are not always equipped with tools to help them intelligently organize and search their data. In its local data repository, the Aura Microwave Limb Sounder (MLS) science team at NASA's Jet Propulsion Laboratory has collected over 300TB of atmospheric science data from 71 missions/models that aid in validation, algorithm development, and research activities. When the project began, the team developed a MySQL database to aid in data queries, but this database was only designed to keep track of MLS and a few ancillary data sets, leving much of the data uncatalogued. The team has also seen database query time rise over the life of the mission. Even though the MLS science team's data holdings are not the size of a national data center's, team members still need tools to help them discover and utilize the data that they have on-hand. Over the past year, members of the science team have been looking for solutions to (1) store information on all the data sets they have collected in a single database, (2) store more metadata about each data file, (3) develop queries that can find relationships among these disparate data types, and (4) plug any new functions developed around this database into existing analysis, visualization, and web tools, transparently to users. In this presentation, I will discuss the searchSCF package that is currently under development. This package includes a NoSQL database management system (MongoDB) and a set of Python tools that both ingests data into the database and supports user queries. I will also highlight case studies of how this system could be used by the MLS science team, and how it could be implemented by other science teams with local data repositories.

BAID: The Barrow Area Information Database - An Interactive Web Mapping Portal and Cyberinfrastructure Showcasing Scientific Activities in the Vicinity of Barrow, Arctic Alaska.

NASA Astrophysics Data System (ADS)

Escarzaga, S. M.; Cody, R. P.; Kassin, A.; Barba, M.; Gaylord, A. G.; Manley, W. F.; Mazza Ramsay, F. D.; Vargas, S. A., Jr.; Tarin, G.; Laney, C. M.; Villarreal, S.; Aiken, Q.; Collins, J. A.; Green, E.; Nelson, L.; Tweedie, C. E.

2015-12-01

The Barrow area of northern Alaska is one of the most intensely researched locations in the Arctic and the Barrow Area Information Database (BAID, www.barrowmapped.org) tracks and facilitates a gamut of research, management, and educational activities in the area. BAID is a cyberinfrastructure (CI) that details much of the historic and extant research undertaken within in the Barrow region in a suite of interactive web-based mapping and information portals (geobrowsers). The BAID user community and target audience for BAID is diverse and includes research scientists, science logisticians, land managers, educators, students, and the general public. BAID contains information on more than 12,000 Barrow area research sites that extend back to the 1940's and more than 640 remote sensing images and geospatial datasets. In a web-based setting, users can zoom, pan, query, measure distance, save or print maps and query results, and filter or view information by space, time, and/or other tags. Additionally, data are described with metadata that meet Federal Geographic Data Committee standards. Recent advances include the addition of more than 2000 new research sites, the addition of a query builder user interface allowing rich and complex queries, and provision of differential global position system (dGPS) and high-resolution aerial imagery support to visiting scientists. Recent field surveys include over 80 miles of coastline to document rates of erosion and the collection of high-resolution sonar data for bathymetric mapping of Elson Lagoon and near shore region of the Chukchi Sea. A network of five climate stations has been deployed across the peninsula to serve as a wireless net for the research community and to deliver near real time climatic data to the user community. Local GIS personal have also been trained to better make use of scientific data for local decision making. Links to Barrow area datasets are housed at national data archives and substantial upgrades have been made to the BAID website and web mapping applications to include the public release of a new multi-temporal Imagery Viewer that allow users to interact with and compare imagery of the Barrow area from 1949 to present.

Intelligent Data Granulation on Load: Improving Infobright's Knowledge Grid

NASA Astrophysics Data System (ADS)

Ślęzak, Dominik; Kowalski, Marcin

One of the major aspects of Infobright's relational database technology is automatic decomposition of each of data tables onto Rough Rows, each consisting of 64K of original rows. Rough Rows are automatically annotated by Knowledge Nodes that represent compact information about the rows' values. Query performance depends on the quality of Knowledge Nodes, i.e., their efficiency in minimizing the access to the compressed portions of data stored on disk, according to the specific query optimization procedures. We show how to implement the mechanism of organizing the incoming data into such Rough Rows that maximize the quality of the corresponding Knowledge Nodes. Given clear business-driven requirements, the implemented mechanism needs to be fully integrated with the data load process, causing no decrease in the data load speed. The performance gain resulting from better data organization is illustrated by some tests over our benchmark data. The differences between the proposed mechanism and some well-known procedures of database clustering or partitioning are discussed. The paper is a continuation of our patent application [22].

RANDOMNESS of Numbers DEFINITION(QUERY:WHAT? V HOW?) ONLY Via MAXWELL-BOLTZMANN CLASSICAL-Statistics(MBCS) Hot-Plasma VS. Digits-Clumping Log-Law NON-Randomness Inversion ONLY BOSE-EINSTEIN QUANTUM-Statistics(BEQS) .

NASA Astrophysics Data System (ADS)

Siegel, Z.; Siegel, Edward Carl-Ludwig

2011-03-01

RANDOMNESS of Numbers cognitive-semantics DEFINITION VIA Cognition QUERY: WHAT???, NOT HOW?) VS. computer-``science" mindLESS number-crunching (Harrel-Sipser-...) algorithmics Goldreich "PSEUDO-randomness"[Not.AMS(02)] mea-culpa is ONLY via MAXWELL-BOLTZMANN CLASSICAL-STATISTICS(NOT FDQS!!!) "hot-plasma" REPULSION VERSUS Newcomb(1881)-Weyl(1914;1916)-Benford(1938) "NeWBe" logarithmic-law digit-CLUMPING/ CLUSTERING NON-Randomness simple Siegel[AMS Joint.Mtg.(02)-Abs. # 973-60-124] algebraic-inversion to THE QUANTUM and ONLY BEQS preferentially SEQUENTIALLY lower-DIGITS CLUMPING/CLUSTERING with d = 0 BEC, is ONLY VIA Siegel-Baez FUZZYICS=CATEGORYICS (SON OF TRIZ)/"Category-Semantics"(C-S), latter intersection/union of Lawvere(1964)-Siegel(1964)] category-theory (matrix: MORPHISMS V FUNCTORS) "+" cognitive-semantics'' (matrix: ANTONYMS V SYNONYMS) yields Siegel-Baez FUZZYICS=CATEGORYICS/C-S tabular list-format matrix truth-table analytics: MBCS RANDOMNESS TRUTH/EMET!!!

Using PeptideAtlas, SRMAtlas and PASSEL – Comprehensive Resources for discovery and targeted proteomics

PubMed Central

Kusebauch, Ulrike; Deutsch, Eric W.; Campbell, David S.; Sun, Zhi; Farrah, Terry; Moritz, Robert L.

2014-01-01

PeptideAtlas, SRMAtlas and PASSEL are web-accessible resources to support discovery and targeted proteomics research. PeptideAtlas is a multi-species compendium of shotgun proteomic data provided by the scientific community, SRMAtlas is a resource of high-quality, complete proteome SRM assays generated in a consistent manner for the targeted identification and quantification of proteins, and PASSEL is a repository that compiles and represents selected reaction monitoring data, all in an easy to use interface. The databases are generated from native mass spectrometry data files that are analyzed in a standardized manner including statistical validation of the results. Each resource offers search functionalities and can be queried by user defined constraints; the query results are provided in tables or are graphically displayed. PeptideAtlas, SRMAtlas and PASSEL are publicly available freely via the website http://www.peptideatlas.org. In this protocol, we describe the use of these resources, we highlight how to submit, search, collate and download data. PMID:24939129

Integration of Web-based and PC-based clinical research databases.

PubMed

Brandt, C A; Sun, K; Charpentier, P; Nadkarni, P M

2004-01-01

We have created a Web-based repository or data library of information about measurement instruments used in studies of multi-factorial geriatric health conditions (the Geriatrics Research Instrument Library - GRIL) based upon existing features of two separate clinical study data management systems. GRIL allows browsing, searching, and selecting measurement instruments based upon criteria such as keywords and areas of applicability. Measurement instruments selected can be printed and/or included in an automatically generated standalone microcomputer database application, which can be downloaded by investigators for use in data collection and data management. Integration of database applications requires the creation of a common semantic model, and mapping from each system to this model. Various database schema conflicts at the table and attribute level must be identified and resolved prior to integration. Using a conflict taxonomy and a mapping schema facilitates this process. Critical conflicts at the table level that required resolution included name and relationship differences. A major benefit of integration efforts is the sharing of features and cross-fertilization of applications created for similar purposes in different operating environments. Integration of applications mandates some degree of metadata model unification.

Database architectures for Space Telescope Science Institute

NASA Astrophysics Data System (ADS)

Lubow, Stephen

1993-08-01

At STScI nearly all large applications require database support. A general purpose architecture has been developed and is in use that relies upon an extended client-server paradigm. Processing is in general distributed across three processes, each of which generally resides on its own processor. Database queries are evaluated on one such process, called the DBMS server. The DBMS server software is provided by a database vendor. The application issues database queries and is called the application client. This client uses a set of generic DBMS application programming calls through our STDB/NET programming interface. Intermediate between the application client and the DBMS server is the STDB/NET server. This server accepts generic query requests from the application and converts them into the specific requirements of the DBMS server. In addition, it accepts query results from the DBMS server and passes them back to the application. Typically the STDB/NET server is local to the DBMS server, while the application client may be remote. The STDB/NET server provides additional capabilities such as database deadlock restart and performance monitoring. This architecture is currently in use for some major STScI applications, including the ground support system. We are currently investigating means of providing ad hoc query support to users through the above architecture. Such support is critical for providing flexible user interface capabilities. The Universal Relation advocated by Ullman, Kernighan, and others appears to be promising. In this approach, the user sees the entire database as a single table, thereby freeing the user from needing to understand the detailed schema. A software layer provides the translation between the user and detailed schema views of the database. However, many subtle issues arise in making this transformation. We are currently exploring this scheme for use in the Hubble Space Telescope user interface to the data archive system (DADS).

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.