Implementation Recommendations for MOSAIC: A Workflow Architecture for Analytic Enrichment. Analysis and Recommendations for the Implementation of a Cohesive Method for Orchestrating Analytics in a Distributed Model

DTIC Science & Technology

2011-02-01

Process Architecture Technology Analysis: Executive .............................................. 15 UIMA as Executive...44 A.4: Flow Code in UIMA ......................................................................................................... 46... UIMA ................................................................................................................................ 57 E.2

Windows Terminal Servers Orchestration

NASA Astrophysics Data System (ADS)

Bukowiec, Sebastian; Gaspar, Ricardo; Smith, Tim

2017-10-01

Windows Terminal Servers provide application gateways for various parts of the CERN accelerator complex, used by hundreds of CERN users every day. The combination of new tools such as Puppet, HAProxy and Microsoft System Center suite enable automation of provisioning workflows to provide a terminal server infrastructure that can scale up and down in an automated manner. The orchestration does not only reduce the time and effort necessary to deploy new instances, but also facilitates operations such as patching, analysis and recreation of compromised nodes as well as catering for workload peaks.

NOW: A Workflow Language for Orchestration in Nomadic Networks

NASA Astrophysics Data System (ADS)

Philips, Eline; van der Straeten, Ragnhild; Jonckers, Viviane

Existing workflow languages for nomadic or mobile ad hoc networks do not offer adequate support for dealing with the volatile connections inherent to these environments. Services residing on mobile devices are exposed to (temporary) network failures, which should be considered the rule rather than the exception. This paper proposes a nomadic workflow language built on top of an ambient-oriented programming language which supports dynamic service discovery and communication primitives resilient to network failures. Our proposed language provides high level workflow abstractions for control flow and supports rich network and service failure detection and handling through compensating actions. Moreover, we introduce a powerful variable binding mechanism which enables dynamic data flow between services in a nomadic environment. By adding this extra layer of abstraction on top of an ambient-oriented programming language, the application programmer is offered a flexible way to develop applications for nomadic networks.

An overview of the model integration process: From pre ...

EPA Pesticide Factsheets

Integration of models requires linking models which can be developed using different tools, methodologies, and assumptions. We performed a literature review with the aim of improving our understanding of model integration process, and also presenting better strategies for building integrated modeling systems. We identified five different phases to characterize integration process: pre-integration assessment, preparation of models for integration, orchestration of models during simulation, data interoperability, and testing. Commonly, there is little reuse of existing frameworks beyond the development teams and not much sharing of science components across frameworks. We believe this must change to enable researchers and assessors to form complex workflows that leverage the current environmental science available. In this paper, we characterize the model integration process and compare integration practices of different groups. We highlight key strategies, features, standards, and practices that can be employed by developers to increase reuse and interoperability of science software components and systems. The paper provides a review of the literature regarding techniques and methods employed by various modeling system developers to facilitate science software interoperability. The intent of the paper is to illustrate the wide variation in methods and the limiting effect the variation has on inter-framework reuse and interoperability. A series of recommendation

BPELPower—A BPEL execution engine for geospatial web services

NASA Astrophysics Data System (ADS)

Yu, Genong (Eugene); Zhao, Peisheng; Di, Liping; Chen, Aijun; Deng, Meixia; Bai, Yuqi

2012-10-01

The Business Process Execution Language (BPEL) has become a popular choice for orchestrating and executing workflows in the Web environment. As one special kind of scientific workflow, geospatial Web processing workflows are data-intensive, deal with complex structures in data and geographic features, and execute automatically with limited human intervention. To enable the proper execution and coordination of geospatial workflows, a specially enhanced BPEL execution engine is required. BPELPower was designed, developed, and implemented as a generic BPEL execution engine with enhancements for executing geospatial workflows. The enhancements are especially in its capabilities in handling Geography Markup Language (GML) and standard geospatial Web services, such as the Web Processing Service (WPS) and the Web Feature Service (WFS). BPELPower has been used in several demonstrations over the decade. Two scenarios were discussed in detail to demonstrate the capabilities of BPELPower. That study showed a standard-compliant, Web-based approach for properly supporting geospatial processing, with the only enhancement at the implementation level. Pattern-based evaluation and performance improvement of the engine are discussed: BPELPower directly supports 22 workflow control patterns and 17 workflow data patterns. In the future, the engine will be enhanced with high performance parallel processing and broad Web paradigms.

Architectural Principles for Orchestration of Cross-Organizational Service Delivery: Case Studies from the Netherlands

NASA Astrophysics Data System (ADS)

van Veenstra, Anne Fleur; Janssen, Marijn

One of the main challenges for e-government is to create coherent services for citizens and businesses. Realizing Integrated Service Delivery (ISD) requires government agencies to collaborate across their organizational boundaries. The coordination of processes across multiple organizations to realize ISD is called orchestration. One way of achieving orchestration is to formalize processes using architecture. In this chapter we identify architectural principles for orchestration by looking at three case studies of cross-organizational service delivery chain formation in the Netherlands. In total, six generic principles were formulated and subsequently validated in two workshops with experts. These principles are: (i) build an intelligent front office, (ii) give processes a clear starting point and end, (iii) build a central workflow application keeping track of the process, (iv) differentiate between simple and complex processes, (v) ensure that the decision-making responsibility and the overview of the process are not performed by the same process role, and (vi) create a central point where risk profiles are maintained. Further research should focus on how organizations can adapt these principles to their own situation.

Orchestration in Learning Technology Research: Evaluation of a Conceptual Framework

ERIC Educational Resources Information Center

Prieto, Luis P.; Dimitriadis, Yannis; Asensio-Pérez, Juan I.; Looi, Chee-Kit

2015-01-01

The term "orchestrating learning" is being used increasingly often, referring to the coordination activities performed while applying learning technologies to authentic settings. However, there is little consensus about how this notion should be conceptualised, and what aspects it entails. In this paper, a conceptual framework for…

An automated and integrated framework for dust storm detection based on ogc web processing services

NASA Astrophysics Data System (ADS)

Xiao, F.; Shea, G. Y. K.; Wong, M. S.; Campbell, J.

2014-11-01

Dust storms are known to have adverse effects on public health. Atmospheric dust loading is also one of the major uncertainties in global climatic modelling as it is known to have a significant impact on the radiation budget and atmospheric stability. The complexity of building scientific dust storm models is coupled with the scientific computation advancement, ongoing computing platform development, and the development of heterogeneous Earth Observation (EO) networks. It is a challenging task to develop an integrated and automated scheme for dust storm detection that combines Geo-Processing frameworks, scientific models and EO data together to enable the dust storm detection and tracking processes in a dynamic and timely manner. This study develops an automated and integrated framework for dust storm detection and tracking based on the Web Processing Services (WPS) initiated by Open Geospatial Consortium (OGC). The presented WPS framework consists of EO data retrieval components, dust storm detecting and tracking component, and service chain orchestration engine. The EO data processing component is implemented based on OPeNDAP standard. The dust storm detecting and tracking component combines three earth scientific models, which are SBDART model (for computing aerosol optical depth (AOT) of dust particles), WRF model (for simulating meteorological parameters) and HYSPLIT model (for simulating the dust storm transport processes). The service chain orchestration engine is implemented based on Business Process Execution Language for Web Service (BPEL4WS) using open-source software. The output results, including horizontal and vertical AOT distribution of dust particles as well as their transport paths, were represented using KML/XML and displayed in Google Earth. A serious dust storm, which occurred over East Asia from 26 to 28 Apr 2012, is used to test the applicability of the proposed WPS framework. Our aim here is to solve a specific instance of a complex EO data and scientific model integration problem by using a framework and scientific workflow approach together. The experimental result shows that this newly automated and integrated framework can be used to give advance near real-time warning of dust storms, for both environmental authorities and public. The methods presented in this paper might be also generalized to other types of Earth system models, leading to improved ease of use and flexibility.

The Live Access Server Scientific Product Generation Through Workflow Orchestration

NASA Astrophysics Data System (ADS)

Hankin, S.; Calahan, J.; Li, J.; Manke, A.; O'Brien, K.; Schweitzer, R.

2006-12-01

The Live Access Server (LAS) is a well-established Web-application for display and analysis of geo-science data sets. The software, which can be downloaded and installed by anyone, gives data providers an easy way to establish services for their on-line data holdings, so their users can make plots; create and download data sub-sets; compare (difference) fields; and perform simple analyses. Now at version 7.0, LAS has been in operation since 1994. The current "Armstrong" release of LAS V7 consists of three components in a tiered architecture: user interface, workflow orchestration and Web Services. The LAS user interface (UI) communicates with the LAS Product Server via an XML protocol embedded in an HTTP "get" URL. Libraries (APIs) have been developed in Java, JavaScript and perl that can readily generate this URL. As a result of this flexibility it is common to find LAS user interfaces of radically different character, tailored to the nature of specific datasets or the mindset of specific users. When a request is received by the LAS Product Server (LPS -- the workflow orchestration component), business logic converts this request into a series of Web Service requests invoked via SOAP. These "back- end" Web services perform data access and generate products (visualizations, data subsets, analyses, etc.). LPS then packages these outputs into final products (typically HTML pages) via Jakarta Velocity templates for delivery to the end user. "Fine grained" data access is performed by back-end services that may utilize JDBC for data base access; the OPeNDAP "DAPPER" protocol; or (in principle) the OGC WFS protocol. Back-end visualization services are commonly legacy science applications wrapped in Java or Python (or perl) classes and deployed as Web Services accessible via SOAP. Ferret is the default visualization application used by LAS, though other applications such as Matlab, CDAT, and GrADS can also be used. Other back-end services may include generation of Google Earth layers using KML; generation of maps via WMS or ArcIMS protocols; and data manipulation with Unix utilities.

BioVLAB-MMIA: a cloud environment for microRNA and mRNA integrated analysis (MMIA) on Amazon EC2.

PubMed

Lee, Hyungro; Yang, Youngik; Chae, Heejoon; Nam, Seungyoon; Choi, Donghoon; Tangchaisin, Patanachai; Herath, Chathura; Marru, Suresh; Nephew, Kenneth P; Kim, Sun

2012-09-01

MicroRNAs, by regulating the expression of hundreds of target genes, play critical roles in developmental biology and the etiology of numerous diseases, including cancer. As a vast amount of microRNA expression profile data are now publicly available, the integration of microRNA expression data sets with gene expression profiles is a key research problem in life science research. However, the ability to conduct genome-wide microRNA-mRNA (gene) integration currently requires sophisticated, high-end informatics tools, significant expertise in bioinformatics and computer science to carry out the complex integration analysis. In addition, increased computing infrastructure capabilities are essential in order to accommodate large data sets. In this study, we have extended the BioVLAB cloud workbench to develop an environment for the integrated analysis of microRNA and mRNA expression data, named BioVLAB-MMIA. The workbench facilitates computations on the Amazon EC2 and S3 resources orchestrated by the XBaya Workflow Suite. The advantages of BioVLAB-MMIA over the web-based MMIA system include: 1) readily expanded as new computational tools become available; 2) easily modifiable by re-configuring graphic icons in the workflow; 3) on-demand cloud computing resources can be used on an "as needed" basis; 4) distributed orchestration supports complex and long running workflows asynchronously. We believe that BioVLAB-MMIA will be an easy-to-use computing environment for researchers who plan to perform genome-wide microRNA-mRNA (gene) integrated analysis tasks.

Support for Taverna workflows in the VPH-Share cloud platform.

PubMed

Kasztelnik, Marek; Coto, Ernesto; Bubak, Marian; Malawski, Maciej; Nowakowski, Piotr; Arenas, Juan; Saglimbeni, Alfredo; Testi, Debora; Frangi, Alejandro F

2017-07-01

To address the increasing need for collaborative endeavours within the Virtual Physiological Human (VPH) community, the VPH-Share collaborative cloud platform allows researchers to expose and share sequences of complex biomedical processing tasks in the form of computational workflows. The Taverna Workflow System is a very popular tool for orchestrating complex biomedical & bioinformatics processing tasks in the VPH community. This paper describes the VPH-Share components that support the building and execution of Taverna workflows, and explains how they interact with other VPH-Share components to improve the capabilities of the VPH-Share platform. Taverna workflow support is delivered by the Atmosphere cloud management platform and the VPH-Share Taverna plugin. These components are explained in detail, along with the two main procedures that were developed to enable this seamless integration: workflow composition and execution. 1) Seamless integration of VPH-Share with other components and systems. 2) Extended range of different tools for workflows. 3) Successful integration of scientific workflows from other VPH projects. 4) Execution speed improvement for medical applications. The presented workflow integration provides VPH-Share users with a wide range of different possibilities to compose and execute workflows, such as desktop or online composition, online batch execution, multithreading, remote execution, etc. The specific advantages of each supported tool are presented, as are the roles of Atmosphere and the VPH-Share plugin within the VPH-Share project. The combination of the VPH-Share plugin and Atmosphere engenders the VPH-Share infrastructure with far more flexible, powerful and usable capabilities for the VPH-Share community. As both components can continue to evolve and improve independently, we acknowledge that further improvements are still to be developed and will be described. Copyright © 2017 Elsevier B.V. All rights reserved.

Data Provenance Hybridization Supporting Extreme-Scale Scientific WorkflowApplications

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

Elsethagen, Todd O.; Stephan, Eric G.; Raju, Bibi

As high performance computing (HPC) infrastructures continue to grow in capability and complexity, so do the applications that they serve. HPC and distributed-area computing (DAC) (e.g. grid and cloud) users are looking increasingly toward workflow solutions to orchestrate their complex application coupling, pre- and post-processing needs To gain insight and a more quantitative understanding of a workflow’s performance our method includes not only the capture of traditional provenance information, but also the capture and integration of system environment metrics helping to give context and explanation for a workflow’s execution. In this paper, we describe IPPD’s provenance management solution (ProvEn) andmore » its hybrid data store combining both of these data provenance perspectives.« less

A Framework for Modeling Workflow Execution by an Interdisciplinary Healthcare Team.

PubMed

Kezadri-Hamiaz, Mounira; Rosu, Daniela; Wilk, Szymon; Kuziemsky, Craig; Michalowski, Wojtek; Carrier, Marc

2015-01-01

The use of business workflow models in healthcare is limited because of insufficient capture of complexities associated with behavior of interdisciplinary healthcare teams that execute healthcare workflows. In this paper we present a novel framework that builds on the well-founded business workflow model formalism and related infrastructures and introduces a formal semantic layer that describes selected aspects of team dynamics and supports their real-time operationalization.

A framework for service enterprise workflow simulation with multi-agents cooperation

NASA Astrophysics Data System (ADS)

Tan, Wenan; Xu, Wei; Yang, Fujun; Xu, Lida; Jiang, Chuanqun

2013-11-01

Process dynamic modelling for service business is the key technique for Service-Oriented information systems and service business management, and the workflow model of business processes is the core part of service systems. Service business workflow simulation is the prevalent approach to be used for analysis of service business process dynamically. Generic method for service business workflow simulation is based on the discrete event queuing theory, which is lack of flexibility and scalability. In this paper, we propose a service workflow-oriented framework for the process simulation of service businesses using multi-agent cooperation to address the above issues. Social rationality of agent is introduced into the proposed framework. Adopting rationality as one social factor for decision-making strategies, a flexible scheduling for activity instances has been implemented. A system prototype has been developed to validate the proposed simulation framework through a business case study.

LASP Time Series Server (LaTiS): Overcoming Data Access Barriers via a Common Data Model in the Middle Tier (Invited)

NASA Astrophysics Data System (ADS)

Lindholm, D. M.; Wilson, A.

2010-12-01

The Laboratory for Atmospheric and Space Physics at the University of Colorado has developed an Open Source, OPeNDAP compliant, Java Servlet based, RESTful web service to serve time series data. In addition to handling OPeNDAP style requests and returning standard responses, existing modules for alternate output formats can be reused or customized. It is also simple to reuse or customize modules to directly read various native data sources and even to perform some processing on the server. The server is built around a common data model based on the Unidata Common Data Model (CDM) which merges the NetCDF, HDF, and OPeNDAP data models. The server framework features a modular architecture that supports pluggable Readers, Writers, and Filters via the common interface to the data, enabling a workflow that reads data from their native form, performs some processing on the server, and presents the results to the client in its preferred form. The service is currently being used operationally to serve time series data for the LASP Interactive Solar Irradiance Data Center (LISIRD, http://lasp.colorado.edu/lisird/) and as part of the Time Series Data Server (TSDS, http://tsds.net/). I will present the data model and how it enables reading, writing, and processing concerns to be separated into loosely coupled components. I will also share thoughts for evolving beyond the time series abstraction and providing a general purpose data service that can be orchestrated into larger workflows.

An Integrated Framework for Parameter-based Optimization of Scientific Workflows.

PubMed

Kumar, Vijay S; Sadayappan, P; Mehta, Gaurang; Vahi, Karan; Deelman, Ewa; Ratnakar, Varun; Kim, Jihie; Gil, Yolanda; Hall, Mary; Kurc, Tahsin; Saltz, Joel

2009-01-01

Data analysis processes in scientific applications can be expressed as coarse-grain workflows of complex data processing operations with data flow dependencies between them. Performance optimization of these workflows can be viewed as a search for a set of optimal values in a multi-dimensional parameter space. While some performance parameters such as grouping of workflow components and their mapping to machines do not a ect the accuracy of the output, others may dictate trading the output quality of individual components (and of the whole workflow) for performance. This paper describes an integrated framework which is capable of supporting performance optimizations along multiple dimensions of the parameter space. Using two real-world applications in the spatial data analysis domain, we present an experimental evaluation of the proposed framework.

A Mixed-Methods Research Framework for Healthcare Process Improvement.

PubMed

Bastian, Nathaniel D; Munoz, David; Ventura, Marta

2016-01-01

The healthcare system in the United States is spiraling out of control due to ever-increasing costs without significant improvements in quality, access to care, satisfaction, and efficiency. Efficient workflow is paramount to improving healthcare value while maintaining the utmost standards of patient care and provider satisfaction in high stress environments. This article provides healthcare managers and quality engineers with a practical healthcare process improvement framework to assess, measure and improve clinical workflow processes. The proposed mixed-methods research framework integrates qualitative and quantitative tools to foster the improvement of processes and workflow in a systematic way. The framework consists of three distinct phases: 1) stakeholder analysis, 2a) survey design, 2b) time-motion study, and 3) process improvement. The proposed framework is applied to the pediatric intensive care unit of the Penn State Hershey Children's Hospital. The implementation of this methodology led to identification and categorization of different workflow tasks and activities into both value-added and non-value added in an effort to provide more valuable and higher quality patient care. Based upon the lessons learned from the case study, the three-phase methodology provides a better, broader, leaner, and holistic assessment of clinical workflow. The proposed framework can be implemented in various healthcare settings to support continuous improvement efforts in which complexity is a daily element that impacts workflow. We proffer a general methodology for process improvement in a healthcare setting, providing decision makers and stakeholders with a useful framework to help their organizations improve efficiency. Published by Elsevier Inc.

A proposed clinical decision support architecture capable of supporting whole genome sequence information.

PubMed

Welch, Brandon M; Loya, Salvador Rodriguez; Eilbeck, Karen; Kawamoto, Kensaku

2014-04-04

Whole genome sequence (WGS) information may soon be widely available to help clinicians personalize the care and treatment of patients. However, considerable barriers exist, which may hinder the effective utilization of WGS information in a routine clinical care setting. Clinical decision support (CDS) offers a potential solution to overcome such barriers and to facilitate the effective use of WGS information in the clinic. However, genomic information is complex and will require significant considerations when developing CDS capabilities. As such, this manuscript lays out a conceptual framework for a CDS architecture designed to deliver WGS-guided CDS within the clinical workflow. To handle the complexity and breadth of WGS information, the proposed CDS framework leverages service-oriented capabilities and orchestrates the interaction of several independently-managed components. These independently-managed components include the genome variant knowledge base, the genome database, the CDS knowledge base, a CDS controller and the electronic health record (EHR). A key design feature is that genome data can be stored separately from the EHR. This paper describes in detail: (1) each component of the architecture; (2) the interaction of the components; and (3) how the architecture attempts to overcome the challenges associated with WGS information. We believe that service-oriented CDS capabilities will be essential to using WGS information for personalized medicine.

A Proposed Clinical Decision Support Architecture Capable of Supporting Whole Genome Sequence Information

PubMed Central

Welch, Brandon M.; Rodriguez Loya, Salvador; Eilbeck, Karen; Kawamoto, Kensaku

2014-01-01

Whole genome sequence (WGS) information may soon be widely available to help clinicians personalize the care and treatment of patients. However, considerable barriers exist, which may hinder the effective utilization of WGS information in a routine clinical care setting. Clinical decision support (CDS) offers a potential solution to overcome such barriers and to facilitate the effective use of WGS information in the clinic. However, genomic information is complex and will require significant considerations when developing CDS capabilities. As such, this manuscript lays out a conceptual framework for a CDS architecture designed to deliver WGS-guided CDS within the clinical workflow. To handle the complexity and breadth of WGS information, the proposed CDS framework leverages service-oriented capabilities and orchestrates the interaction of several independently-managed components. These independently-managed components include the genome variant knowledge base, the genome database, the CDS knowledge base, a CDS controller and the electronic health record (EHR). A key design feature is that genome data can be stored separately from the EHR. This paper describes in detail: (1) each component of the architecture; (2) the interaction of the components; and (3) how the architecture attempts to overcome the challenges associated with WGS information. We believe that service-oriented CDS capabilities will be essential to using WGS information for personalized medicine. PMID:25411644

Inferring Clinical Workflow Efficiency via Electronic Medical Record Utilization

PubMed Central

Chen, You; Xie, Wei; Gunter, Carl A; Liebovitz, David; Mehrotra, Sanjay; Zhang, He; Malin, Bradley

2015-01-01

Complexity in clinical workflows can lead to inefficiency in making diagnoses, ineffectiveness of treatment plans and uninformed management of healthcare organizations (HCOs). Traditional strategies to manage workflow complexity are based on measuring the gaps between workflows defined by HCO administrators and the actual processes followed by staff in the clinic. However, existing methods tend to neglect the influences of EMR systems on the utilization of workflows, which could be leveraged to optimize workflows facilitated through the EMR. In this paper, we introduce a framework to infer clinical workflows through the utilization of an EMR and show how such workflows roughly partition into four types according to their efficiency. Our framework infers workflows at several levels of granularity through data mining technologies. We study four months of EMR event logs from a large medical center, including 16,569 inpatient stays, and illustrate that over approximately 95% of workflows are efficient and that 80% of patients are on such workflows. At the same time, we show that the remaining 5% of workflows may be inefficient due to a variety of factors, such as complex patients. PMID:26958173

Orchestrating TRANSP Simulations for Interpretative and Predictive Tokamak Modeling with OMFIT

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

Grierson, B. A.; Yuan, X.; Gorelenkova, M.

TRANSP simulations are being used in the OMFIT work- flow manager to enable a machine independent means of experimental analysis, postdictive validation, and predictive time dependent simulations on the DIII-D, NSTX, JET and C-MOD tokamaks. The procedures for preparing the input data from plasma profile diagnostics and equilibrium reconstruction, as well as processing of the time-dependent heating and current drive sources and assumptions about the neutral recycling, vary across machines, but are streamlined by using a common workflow manager. Settings for TRANSP simulation fidelity are incorporated into the OMFIT framework, contrasting between-shot analysis, power balance, and fast-particle simulations. A previouslymore » established series of data consistency metrics are computed such as comparison of experimental vs. calculated neutron rate, equilibrium stored energy vs. total stored energy from profile and fast-ion pressure, and experimental vs. computed surface loop voltage. Discrepancies between data consistency metrics can indicate errors in input quantities such as electron density profile or Zeff, or indicate anomalous fast-particle transport. Measures to assess the sensitivity of the verification metrics to input quantities are provided by OMFIT, including scans of the input profiles and standardized post-processing visualizations. For predictive simulations, TRANSP uses GLF23 or TGLF to predict core plasma profiles, with user defined boundary conditions in the outer region of the plasma. ITPA validation metrics are provided in post-processing to assess the transport model validity. By using OMFIT to orchestrate the steps for experimental data preparation, selection of operating mode, submission, post-processing and visualization, we have streamlined and standardized the usage of TRANSP.« less

Orchestrating TRANSP Simulations for Interpretative and Predictive Tokamak Modeling with OMFIT

DOE PAGES

Grierson, B. A.; Yuan, X.; Gorelenkova, M.; ...

2018-02-21

TRANSP simulations are being used in the OMFIT work- flow manager to enable a machine independent means of experimental analysis, postdictive validation, and predictive time dependent simulations on the DIII-D, NSTX, JET and C-MOD tokamaks. The procedures for preparing the input data from plasma profile diagnostics and equilibrium reconstruction, as well as processing of the time-dependent heating and current drive sources and assumptions about the neutral recycling, vary across machines, but are streamlined by using a common workflow manager. Settings for TRANSP simulation fidelity are incorporated into the OMFIT framework, contrasting between-shot analysis, power balance, and fast-particle simulations. A previouslymore » established series of data consistency metrics are computed such as comparison of experimental vs. calculated neutron rate, equilibrium stored energy vs. total stored energy from profile and fast-ion pressure, and experimental vs. computed surface loop voltage. Discrepancies between data consistency metrics can indicate errors in input quantities such as electron density profile or Zeff, or indicate anomalous fast-particle transport. Measures to assess the sensitivity of the verification metrics to input quantities are provided by OMFIT, including scans of the input profiles and standardized post-processing visualizations. For predictive simulations, TRANSP uses GLF23 or TGLF to predict core plasma profiles, with user defined boundary conditions in the outer region of the plasma. ITPA validation metrics are provided in post-processing to assess the transport model validity. By using OMFIT to orchestrate the steps for experimental data preparation, selection of operating mode, submission, post-processing and visualization, we have streamlined and standardized the usage of TRANSP.« less

Approaches to Learning and Study Orchestrations in High School Students

ERIC Educational Resources Information Center

Cano, Francisco

2007-01-01

In the framework of the SAL (Students' approaches to learning) position, the learning experience (approaches to learning and study orchestrations) of 572 high school students was explored, examining its interrelationships with some personal and familial variables. Three major results emerged. First, links were found between family's intellectual…

Coupling between a multi-physics workflow engine and an optimization framework

NASA Astrophysics Data System (ADS)

Di Gallo, L.; Reux, C.; Imbeaux, F.; Artaud, J.-F.; Owsiak, M.; Saoutic, B.; Aiello, G.; Bernardi, P.; Ciraolo, G.; Bucalossi, J.; Duchateau, J.-L.; Fausser, C.; Galassi, D.; Hertout, P.; Jaboulay, J.-C.; Li-Puma, A.; Zani, L.

2016-03-01

A generic coupling method between a multi-physics workflow engine and an optimization framework is presented in this paper. The coupling architecture has been developed in order to preserve the integrity of the two frameworks. The objective is to provide the possibility to replace a framework, a workflow or an optimizer by another one without changing the whole coupling procedure or modifying the main content in each framework. The coupling is achieved by using a socket-based communication library for exchanging data between the two frameworks. Among a number of algorithms provided by optimization frameworks, Genetic Algorithms (GAs) have demonstrated their efficiency on single and multiple criteria optimization. Additionally to their robustness, GAs can handle non-valid data which may appear during the optimization. Consequently GAs work on most general cases. A parallelized framework has been developed to reduce the time spent for optimizations and evaluation of large samples. A test has shown a good scaling efficiency of this parallelized framework. This coupling method has been applied to the case of SYCOMORE (SYstem COde for MOdeling tokamak REactor) which is a system code developed in form of a modular workflow for designing magnetic fusion reactors. The coupling of SYCOMORE with the optimization platform URANIE enables design optimization along various figures of merit and constraints.

RABIX: AN OPEN-SOURCE WORKFLOW EXECUTOR SUPPORTING RECOMPUTABILITY AND INTEROPERABILITY OF WORKFLOW DESCRIPTIONS

PubMed Central

Ivkovic, Sinisa; Simonovic, Janko; Tijanic, Nebojsa; Davis-Dusenbery, Brandi; Kural, Deniz

2016-01-01

As biomedical data has become increasingly easy to generate in large quantities, the methods used to analyze it have proliferated rapidly. Reproducible and reusable methods are required to learn from large volumes of data reliably. To address this issue, numerous groups have developed workflow specifications or execution engines, which provide a framework with which to perform a sequence of analyses. One such specification is the Common Workflow Language, an emerging standard which provides a robust and flexible framework for describing data analysis tools and workflows. In addition, reproducibility can be furthered by executors or workflow engines which interpret the specification and enable additional features, such as error logging, file organization, optimizations1 to computation and job scheduling, and allow for easy computing on large volumes of data. To this end, we have developed the Rabix Executor a , an open-source workflow engine for the purposes of improving reproducibility through reusability and interoperability of workflow descriptions. PMID:27896971

RABIX: AN OPEN-SOURCE WORKFLOW EXECUTOR SUPPORTING RECOMPUTABILITY AND INTEROPERABILITY OF WORKFLOW DESCRIPTIONS.

PubMed

Kaushik, Gaurav; Ivkovic, Sinisa; Simonovic, Janko; Tijanic, Nebojsa; Davis-Dusenbery, Brandi; Kural, Deniz

2017-01-01

As biomedical data has become increasingly easy to generate in large quantities, the methods used to analyze it have proliferated rapidly. Reproducible and reusable methods are required to learn from large volumes of data reliably. To address this issue, numerous groups have developed workflow specifications or execution engines, which provide a framework with which to perform a sequence of analyses. One such specification is the Common Workflow Language, an emerging standard which provides a robust and flexible framework for describing data analysis tools and workflows. In addition, reproducibility can be furthered by executors or workflow engines which interpret the specification and enable additional features, such as error logging, file organization, optim1izations to computation and job scheduling, and allow for easy computing on large volumes of data. To this end, we have developed the Rabix Executor, an open-source workflow engine for the purposes of improving reproducibility through reusability and interoperability of workflow descriptions.

The Swarm Archiving Payload Data Facility, an Instance Configuration of the ESA Multi-Mission Facility

NASA Astrophysics Data System (ADS)

Pruin, B.; Martini, A.; Shanmugam, P.; Lopes, C.

2015-04-01

The Swarm mission consists of 3 satellites, each carrying an identical set of instruments. The scientific algorithms for processing are organized in 11 separate processing steps including automated product quality control. In total, the mission data consists of data products of several hundred distinct types from raw to level 2 product types and auxiliary data. The systematic production for Swarm within the ESA Archiving and Payload Data Facility (APDF) is performed up to level 2. The production up to L2 (CAT2-mature algorithm) is performed completely within the APDF. A separate systematic production chain from L1B to L2 (CAT1-evolving algorithm) is performed by an external facility (L2PS) with output files archived within the APDF as well. The APDF also performs re-processing exercises. Re-processing may start directly from the acquired data or from any other intermediate level resulting in the need for a refined product version and baseline management. Storage, dissemination and circulation functionality is configurable in the ESA generic multi-mission elements and does not require any software coding. The control of the production is more involved. While the interface towards the algorithmic entities is standardized due to the introduction of a generic IPF interface by ESA, the orchestration of the individual IPFs into the overall workflows is distinctly mission-specific and not as amenable to standardization. The ESA MMFI production management system provides extension points to integrate additional logical elements for the build-up of complex orchestrated workflows. These extension points have been used to inject the Swarm-specific production logic into the system. A noteworthy fact about the APDF is that the dissemination elements are hosted in a high bandwidth infrastructure procured as a managed service, thus affording users a considerable access bandwidth. This paper gives an overview of the Swarm APDF data flows. It describes the elements of the solution with particular focus on how the available generic multi-mission functionality of the ESA MMFI was utilized and where there was a need to implement missionspecific extensions and plug-ins. The paper concludes with some statistics on the system output during commissioning and early operational phases as well as some general considerations on the utilization of a framework like the ESA MMFI, discussing benefits and pitfalls of the approach.

A lightweight messaging-based distributed processing and workflow execution framework for real-time and big data analysis

NASA Astrophysics Data System (ADS)

Laban, Shaban; El-Desouky, Aly

2014-05-01

To achieve a rapid, simple and reliable parallel processing of different types of tasks and big data processing on any compute cluster, a lightweight messaging-based distributed applications processing and workflow execution framework model is proposed. The framework is based on Apache ActiveMQ and Simple (or Streaming) Text Oriented Message Protocol (STOMP). ActiveMQ , a popular and powerful open source persistence messaging and integration patterns server with scheduler capabilities, acts as a message broker in the framework. STOMP provides an interoperable wire format that allows framework programs to talk and interact between each other and ActiveMQ easily. In order to efficiently use the message broker a unified message and topic naming pattern is utilized to achieve the required operation. Only three Python programs and simple library, used to unify and simplify the implementation of activeMQ and STOMP protocol, are needed to use the framework. A watchdog program is used to monitor, remove, add, start and stop any machine and/or its different tasks when necessary. For every machine a dedicated one and only one zoo keeper program is used to start different functions or tasks, stompShell program, needed for executing the user required workflow. The stompShell instances are used to execute any workflow jobs based on received message. A well-defined, simple and flexible message structure, based on JavaScript Object Notation (JSON), is used to build any complex workflow systems. Also, JSON format is used in configuration, communication between machines and programs. The framework is platform independent. Although, the framework is built using Python the actual workflow programs or jobs can be implemented by any programming language. The generic framework can be used in small national data centres for processing seismological and radionuclide data received from the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). Also, it is possible to extend the use of the framework in monitoring the IDC pipeline. The detailed design, implementation,conclusion and future work of the proposed framework will be presented.

Bridging experiment and theory: A template for unifying NMR data and electronic structure calculations

DOE PAGES

Brown, David M. L.; Cho, Herman; de Jong, Wibe A.

2016-02-09

Here, the testing of theoretical models with experimental data is an integral part of the scientific method, and a logical place to search for new ways of stimulating scientific productivity. Often experiment/theory comparisons may be viewed as a workflow comprised of well-defined, rote operations distributed over several distinct computers, as exemplified by the way in which predictions from electronic structure theories are evaluated with results from spectroscopic experiments. For workflows such as this, which may be laborious and time consuming to perform manually, software that could orchestrate the operations and transfer results between computers in a seamless and automated fashionmore » would offer major efficiency gains. Such tools also promise to alter how researchers interact with data outside their field of specialization by, e.g., making raw experimental results more accessible to theorists, and the outputs of theoretical calculations more readily comprehended by experimentalists.« less

Bridging experiment and theory: A template for unifying NMR data and electronic structure calculations

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

Brown, David M. L.; Cho, Herman; de Jong, Wibe A.

Here, the testing of theoretical models with experimental data is an integral part of the scientific method, and a logical place to search for new ways of stimulating scientific productivity. Often experiment/theory comparisons may be viewed as a workflow comprised of well-defined, rote operations distributed over several distinct computers, as exemplified by the way in which predictions from electronic structure theories are evaluated with results from spectroscopic experiments. For workflows such as this, which may be laborious and time consuming to perform manually, software that could orchestrate the operations and transfer results between computers in a seamless and automated fashionmore » would offer major efficiency gains. Such tools also promise to alter how researchers interact with data outside their field of specialization by, e.g., making raw experimental results more accessible to theorists, and the outputs of theoretical calculations more readily comprehended by experimentalists.« less

Traversing the many paths of workflow research: developing a conceptual framework of workflow terminology through a systematic literature review

PubMed Central

Novak, Laurie L; Johnson, Kevin B; Lorenzi, Nancy M

2010-01-01

The objective of this review was to describe methods used to study and model workflow. The authors included studies set in a variety of industries using qualitative, quantitative and mixed methods. Of the 6221 matching abstracts, 127 articles were included in the final corpus. The authors collected data from each article on researcher perspective, study type, methods type, specific methods, approaches to evaluating quality of results, definition of workflow and dependent variables. Ethnographic observation and interviews were the most frequently used methods. Long study durations revealed the large time commitment required for descriptive workflow research. The most frequently discussed technique for evaluating quality of study results was triangulation. The definition of the term “workflow” and choice of methods for studying workflow varied widely across research areas and researcher perspectives. The authors developed a conceptual framework of workflow-related terminology for use in future research and present this model for use by other researchers. PMID:20442143

Coupling of a continuum ice sheet model and a discrete element calving model using a scientific workflow system

NASA Astrophysics Data System (ADS)

Memon, Shahbaz; Vallot, Dorothée; Zwinger, Thomas; Neukirchen, Helmut

2017-04-01

Scientific communities generate complex simulations through orchestration of semi-structured analysis pipelines which involves execution of large workflows on multiple, distributed and heterogeneous computing and data resources. Modeling ice dynamics of glaciers requires workflows consisting of many non-trivial, computationally expensive processing tasks which are coupled to each other. From this domain, we present an e-Science use case, a workflow, which requires the execution of a continuum ice flow model and a discrete element based calving model in an iterative manner. Apart from the execution, this workflow also contains data format conversion tasks that support the execution of ice flow and calving by means of transition through sequential, nested and iterative steps. Thus, the management and monitoring of all the processing tasks including data management and transfer of the workflow model becomes more complex. From the implementation perspective, this workflow model was initially developed on a set of scripts using static data input and output references. In the course of application usage when more scripts or modifications introduced as per user requirements, the debugging and validation of results were more cumbersome to achieve. To address these problems, we identified a need to have a high-level scientific workflow tool through which all the above mentioned processes can be achieved in an efficient and usable manner. We decided to make use of the e-Science middleware UNICORE (Uniform Interface to Computing Resources) that allows seamless and automated access to different heterogenous and distributed resources which is supported by a scientific workflow engine. Based on this, we developed a high-level scientific workflow model for coupling of massively parallel High-Performance Computing (HPC) jobs: a continuum ice sheet model (Elmer/Ice) and a discrete element calving and crevassing model (HiDEM). In our talk we present how the use of a high-level scientific workflow middleware enables reproducibility of results more convenient and also provides a reusable and portable workflow template that can be deployed across different computing infrastructures. Acknowledgements This work was kindly supported by NordForsk as part of the Nordic Center of Excellence (NCoE) eSTICC (eScience Tools for Investigating Climate Change at High Northern Latitudes) and the Top-level Research Initiative NCoE SVALI (Stability and Variation of Arctic Land Ice).

Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows.

PubMed

Sztromwasser, Pawel; Puntervoll, Pål; Petersen, Kjell

2011-07-26

Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

Workflow-Based Software Development Environment

NASA Technical Reports Server (NTRS)

Izygon, Michel E.

2013-01-01

The Software Developer's Assistant (SDA) helps software teams more efficiently and accurately conduct or execute software processes associated with NASA mission-critical software. SDA is a process enactment platform that guides software teams through project-specific standards, processes, and procedures. Software projects are decomposed into all of their required process steps or tasks, and each task is assigned to project personnel. SDA orchestrates the performance of work required to complete all process tasks in the correct sequence. The software then notifies team members when they may begin work on their assigned tasks and provides the tools, instructions, reference materials, and supportive artifacts that allow users to compliantly perform the work. A combination of technology components captures and enacts any software process use to support the software lifecycle. It creates an adaptive workflow environment that can be modified as needed. SDA achieves software process automation through a Business Process Management (BPM) approach to managing the software lifecycle for mission-critical projects. It contains five main parts: TieFlow (workflow engine), Business Rules (rules to alter process flow), Common Repository (storage for project artifacts, versions, history, schedules, etc.), SOA (interface to allow internal, GFE, or COTS tools integration), and the Web Portal Interface (collaborative web environment

Building a Generic Virtual Research Environment Framework for Multiple Earth and Space Science Domains and a Diversity of Users.

NASA Astrophysics Data System (ADS)

Wyborn, L. A.; Fraser, R.; Evans, B. J. K.; Friedrich, C.; Klump, J. F.; Lescinsky, D. T.

2017-12-01

Virtual Research Environments (VREs) are now part of academic infrastructures. Online research workflows can be orchestrated whereby data can be accessed from multiple external repositories with processing taking place on public or private clouds, and centralised supercomputers using a mixture of user codes, and well-used community software and libraries. VREs enable distributed members of research teams to actively work together to share data, models, tools, software, workflows, best practices, infrastructures, etc. These environments and their components are increasingly able to support the needs of undergraduate teaching. External to the research sector, they can also be reused by citizen scientists, and be repurposed for industry users to help accelerate the diffusion and hence enable the translation of research innovations. The Virtual Geophysics Laboratory (VGL) in Australia was started in 2012, built using a collaboration between CSIRO, the National Computational Infrastructure (NCI) and Geoscience Australia, with support funding from the Australian Government Department of Education. VGL comprises three main modules that provide an interface to enable users to first select their required data; to choose a tool to process that data; and then access compute infrastructure for execution. VGL was initially built to enable a specific set of researchers in government agencies access to specific data sets and a limited number of tools. Over the years it has evolved into a multi-purpose Earth science platform with access to an increased variety of data (e.g., Natural Hazards, Geochemistry), a broader range of software packages, and an increasing diversity of compute infrastructures. This expansion has been possible because of the approach to loosely couple data, tools and compute resources via interfaces that are built on international standards and accessed as network-enabled services wherever possible. Built originally for researchers that were not fussy about general usability, increasing emphasis on User Interfaces (UIs) and stability will lead to increased uptake in the education and industry sectors. Simultaneously, improvements are being added to facilitate access to data and tools by experienced researchers who want direct access to both data and flexible workflows.

msCompare: A Framework for Quantitative Analysis of Label-free LC-MS Data for Comparative Candidate Biomarker Studies*

PubMed Central

Hoekman, Berend; Breitling, Rainer; Suits, Frank; Bischoff, Rainer; Horvatovich, Peter

2012-01-01

Data processing forms an integral part of biomarker discovery and contributes significantly to the ultimate result. To compare and evaluate various publicly available open source label-free data processing workflows, we developed msCompare, a modular framework that allows the arbitrary combination of different feature detection/quantification and alignment/matching algorithms in conjunction with a novel scoring method to evaluate their overall performance. We used msCompare to assess the performance of workflows built from modules of publicly available data processing packages such as SuperHirn, OpenMS, and MZmine and our in-house developed modules on peptide-spiked urine and trypsin-digested cerebrospinal fluid (CSF) samples. We found that the quality of results varied greatly among workflows, and interestingly, heterogeneous combinations of algorithms often performed better than the homogenous workflows. Our scoring method showed that the union of feature matrices of different workflows outperformed the original homogenous workflows in some cases. msCompare is open source software (https://trac.nbic.nl/mscompare), and we provide a web-based data processing service for our framework by integration into the Galaxy server of the Netherlands Bioinformatics Center (http://galaxy.nbic.nl/galaxy) to allow scientists to determine which combination of modules provides the most accurate processing for their particular LC-MS data sets. PMID:22318370

Task-technology fit of video telehealth for nurses in an outpatient clinic setting.

PubMed

Cady, Rhonda G; Finkelstein, Stanley M

2014-07-01

Incorporating telehealth into outpatient care delivery supports management of consumer health between clinic visits. Task-technology fit is a framework for understanding how technology helps and/or hinders a person during work processes. Evaluating the task-technology fit of video telehealth for personnel working in a pediatric outpatient clinic and providing care between clinic visits ensures the information provided matches the information needed to support work processes. The workflow of advanced practice registered nurse (APRN) care coordination provided via telephone and video telehealth was described and measured using a mixed-methods workflow analysis protocol that incorporated cognitive ethnography and time-motion study. Qualitative and quantitative results were merged and analyzed within the task-technology fit framework to determine the workflow fit of video telehealth for APRN care coordination. Incorporating video telehealth into APRN care coordination workflow provided visual information unavailable during telephone interactions. Despite additional tasks and interactions needed to obtain the visual information, APRN workflow efficiency, as measured by time, was not significantly changed. Analyzed within the task-technology fit framework, the increased visual information afforded by video telehealth supported the assessment and diagnostic information needs of the APRN. Telehealth must provide the right information to the right clinician at the right time. Evaluating task-technology fit using a mixed-methods protocol ensured rigorous analysis of fit within work processes and identified workflows that benefit most from the technology.

A scientific workflow framework for (13)C metabolic flux analysis.

PubMed

Dalman, Tolga; Wiechert, Wolfgang; Nöh, Katharina

2016-08-20

Metabolic flux analysis (MFA) with (13)C labeling data is a high-precision technique to quantify intracellular reaction rates (fluxes). One of the major challenges of (13)C MFA is the interactivity of the computational workflow according to which the fluxes are determined from the input data (metabolic network model, labeling data, and physiological rates). Here, the workflow assembly is inevitably determined by the scientist who has to consider interacting biological, experimental, and computational aspects. Decision-making is context dependent and requires expertise, rendering an automated evaluation process hardly possible. Here, we present a scientific workflow framework (SWF) for creating, executing, and controlling on demand (13)C MFA workflows. (13)C MFA-specific tools and libraries, such as the high-performance simulation toolbox 13CFLUX2, are wrapped as web services and thereby integrated into a service-oriented architecture. Besides workflow steering, the SWF features transparent provenance collection and enables full flexibility for ad hoc scripting solutions. To handle compute-intensive tasks, cloud computing is supported. We demonstrate how the challenges posed by (13)C MFA workflows can be solved with our approach on the basis of two proof-of-concept use cases. Copyright © 2015 Elsevier B.V. All rights reserved.

An ontology-based framework for bioinformatics workflows.

PubMed

Digiampietri, Luciano A; Perez-Alcazar, Jose de J; Medeiros, Claudia Bauzer

2007-01-01

The proliferation of bioinformatics activities brings new challenges - how to understand and organise these resources, how to exchange and reuse successful experimental procedures, and to provide interoperability among data and tools. This paper describes an effort toward these directions. It is based on combining research on ontology management, AI and scientific workflows to design, reuse and annotate bioinformatics experiments. The resulting framework supports automatic or interactive composition of tasks based on AI planning techniques and takes advantage of ontologies to support the specification and annotation of bioinformatics workflows. We validate our proposal with a prototype running on real data.

Linked Environments for Atmospheric Discovery (LEAD): A Cyberinfrastructure for Mesoscale Meteorology Research and Education

NASA Astrophysics Data System (ADS)

Droegemeier, K.

2004-12-01

A new National Science Foundation Large Information Technology Research (ITR) grant - known as Linked Environments for Atmospheric Discovery (LEAD) - has been funded to facilitate the identification, access, preparation, assimilation, prediction, management, analysis, mining, and visualization of a broad array of meteorological data and model output, independent of format and physical location. A transforming element of LEAD is dynamic workflow orchestration and data management, which will allow use of analysis tools, forecast models, and data repositories as dynamically adaptive, on-demand systems that can a) change configuration rapidly and automatically in response to weather; b) continually be steered by new data; c) respond to decision-driven inputs from users; d) initiate other processes automatically; and e) steer remote observing technologies to optimize data collection for the problem at hand. Having been in operation for slightly more than a year, LEAD has created a technology roadmap and architecture for developing its capabilities and placing them within the academic and research environment. Further, much of the LEAD infrastructure being developed for the WRF model, particularly workflow orchestration, will play a significant role in the nascent WRF Developmental Test Bed Center located at NCAR. This paper updates the status of LEAD (e.g., the topics noted above), its ties with other community activities (e.g., CONDUIT, THREDDS, MADIS, NOMADS), and the manner in which LEAD technologies will be made available for general use. Each component LEAD application is being created as a standards-based Web service that can be run in stand-alone configuration or chained together to build an end-to-end environment for on-demand, real time NWP. We describe in this paper the concepts, implementation plans, and expected impacts of LEAD, the underpinning of which will be a series of interconnected, heterogeneous virtual IT "Grid environments" designed to provide a complete framework for mesoscale meteorology research and education. A set of Integrated Grid and Web Services Testbeds will maintain a rolling archive of several months of recent data, provide tools for operating on them, and serve as an infrastructure (i.e., a mini Grid) for developing distributed Web services capabilities. Education Testbeds will integrate education and outreach throughout the entire LEAD program, and will help shape LEAD research into applications that are congruent with pedagogic requirements, national standards, and evaluation metrics. Ultimately, the LEAD environments will enable researchers, educators, and students to run atmospheric models and other tools in much more realistic, real time settings than is now possible, with emphasis on the use of locally or otherwise uniquely available data.

Enabling Big Geoscience Data Analytics with a Cloud-Based, MapReduce-Enabled and Service-Oriented Workflow Framework

PubMed Central

Li, Zhenlong; Yang, Chaowei; Jin, Baoxuan; Yu, Manzhu; Liu, Kai; Sun, Min; Zhan, Matthew

2015-01-01

Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists. PMID:25742012

Enabling big geoscience data analytics with a cloud-based, MapReduce-enabled and service-oriented workflow framework.

PubMed

Li, Zhenlong; Yang, Chaowei; Jin, Baoxuan; Yu, Manzhu; Liu, Kai; Sun, Min; Zhan, Matthew

2015-01-01

Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists.

JTSA: an open source framework for time series abstractions.

PubMed

Sacchi, Lucia; Capozzi, Davide; Bellazzi, Riccardo; Larizza, Cristiana

2015-10-01

The evaluation of the clinical status of a patient is frequently based on the temporal evolution of some parameters, making the detection of temporal patterns a priority in data analysis. Temporal abstraction (TA) is a methodology widely used in medical reasoning for summarizing and abstracting longitudinal data. This paper describes JTSA (Java Time Series Abstractor), a framework including a library of algorithms for time series preprocessing and abstraction and an engine to execute a workflow for temporal data processing. The JTSA framework is grounded on a comprehensive ontology that models temporal data processing both from the data storage and the abstraction computation perspective. The JTSA framework is designed to allow users to build their own analysis workflows by combining different algorithms. Thanks to the modular structure of a workflow, simple to highly complex patterns can be detected. The JTSA framework has been developed in Java 1.7 and is distributed under GPL as a jar file. JTSA provides: a collection of algorithms to perform temporal abstraction and preprocessing of time series, a framework for defining and executing data analysis workflows based on these algorithms, and a GUI for workflow prototyping and testing. The whole JTSA project relies on a formal model of the data types and of the algorithms included in the library. This model is the basis for the design and implementation of the software application. Taking into account this formalized structure, the user can easily extend the JTSA framework by adding new algorithms. Results are shown in the context of the EU project MOSAIC to extract relevant patterns from data coming related to the long term monitoring of diabetic patients. The proof that JTSA is a versatile tool to be adapted to different needs is given by its possible uses, both as a standalone tool for data summarization and as a module to be embedded into other architectures to select specific phenotypes based on TAs in a large dataset. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Semantic orchestration of image processing services for environmental analysis

NASA Astrophysics Data System (ADS)

Ranisavljević, Élisabeth; Devin, Florent; Laffly, Dominique; Le Nir, Yannick

2013-09-01

In order to analyze environmental dynamics, a major process is the classification of the different phenomena of the site (e.g. ice and snow for a glacier). When using in situ pictures, this classification requires data pre-processing. Not all the pictures need the same sequence of processes depending on the disturbances. Until now, these sequences have been done manually, which restricts the processing of large amount of data. In this paper, we present how to realize a semantic orchestration to automate the sequencing for the analysis. It combines two advantages: solving the problem of the amount of processing, and diversifying the possibilities in the data processing. We define a BPEL description to express the sequences. This BPEL uses some web services to run the data processing. Each web service is semantically annotated using an ontology of image processing. The dynamic modification of the BPEL is done using SPARQL queries on these annotated web services. The results obtained by a prototype implementing this method validate the construction of the different workflows that can be applied to a large number of pictures.

Integrating prediction, provenance, and optimization into high energy workflows

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

Schram, M.; Bansal, V.; Friese, R. D.

We propose a novel approach for efficient execution of workflows on distributed resources. The key components of this framework include: performance modeling to quantitatively predict workflow component behavior; optimization-based scheduling such as choosing an optimal subset of resources to meet demand and assignment of tasks to resources; distributed I/O optimizations such as prefetching; and provenance methods for collecting performance data. In preliminary results, these techniques improve throughput on a small Belle II workflow by 20%.

Task–Technology Fit of Video Telehealth for Nurses in an Outpatient Clinic Setting

PubMed Central

Finkelstein, Stanley M.

2014-01-01

Abstract Background: Incorporating telehealth into outpatient care delivery supports management of consumer health between clinic visits. Task–technology fit is a framework for understanding how technology helps and/or hinders a person during work processes. Evaluating the task–technology fit of video telehealth for personnel working in a pediatric outpatient clinic and providing care between clinic visits ensures the information provided matches the information needed to support work processes. Materials and Methods: The workflow of advanced practice registered nurse (APRN) care coordination provided via telephone and video telehealth was described and measured using a mixed-methods workflow analysis protocol that incorporated cognitive ethnography and time–motion study. Qualitative and quantitative results were merged and analyzed within the task–technology fit framework to determine the workflow fit of video telehealth for APRN care coordination. Results: Incorporating video telehealth into APRN care coordination workflow provided visual information unavailable during telephone interactions. Despite additional tasks and interactions needed to obtain the visual information, APRN workflow efficiency, as measured by time, was not significantly changed. Analyzed within the task–technology fit framework, the increased visual information afforded by video telehealth supported the assessment and diagnostic information needs of the APRN. Conclusions: Telehealth must provide the right information to the right clinician at the right time. Evaluating task–technology fit using a mixed-methods protocol ensured rigorous analysis of fit within work processes and identified workflows that benefit most from the technology. PMID:24841219

Enriching the Web Processing Service

NASA Astrophysics Data System (ADS)

Wosniok, Christoph; Bensmann, Felix; Wössner, Roman; Kohlus, Jörn; Roosmann, Rainer; Heidmann, Carsten; Lehfeldt, Rainer

2014-05-01

The OGC Web Processing Service (WPS) provides a standard for implementing geospatial processes in service-oriented networks. In its current version 1.0.0 it allocates the operations GetCapabilities, DescribeProcess and Execute, which can be used to offer custom processes based on single or multiple sub-processes. A large range of ready to use fine granular, fundamental geospatial processes have been developed by the GIS-community in the past. However, modern use cases or whole workflow processes demand specifications of lifecycle management and service orchestration. Orchestrating smaller sub-processes is a task towards interoperability; a comprehensive documentation by using appropriate metadata is also required. Though different approaches were tested in the past, developing complex WPS applications still requires programming skills, knowledge about software libraries in use and a lot of effort for integration. Our toolset RichWPS aims at providing a better overall experience by setting up two major components. The RichWPS ModelBuilder enables the graphics-aided design of workflow processes based on existing local and distributed processes and geospatial services. Once tested by the RichWPS Server, a composition can be deployed for production use on the RichWPS Server. The ModelBuilder obtains necessary processes and services from a directory service, the RichWPS semantic proxy. It manages the lifecycle and is able to visualize results and debugging-information. One aim will be to generate reproducible results; the workflow should be documented by metadata that can be integrated in Spatial Data Infrastructures. The RichWPS Server provides a set of interfaces to the ModelBuilder for, among others, testing composed workflow sequences, estimating their performance and to publish them as common processes. Therefore the server is oriented towards the upcoming WPS 2.0 standard and its ability to transactionally deploy and undeploy processes making use of a WPS-T interface. In order to deal with the results of these processing workflows, a server side extension enables the RichWPS Server and its clients to use WPS presentation directives (WPS-PD), a content related enhancement for the standardized WPS schema. We identified essential requirements of the components of our toolset by applying two use cases. The first enables the simplified comparison of modeled and measured data, a common task in hydro-engineering to validate the accuracy of a model. An implementation of the workflow includes reading, harmonizing and comparing two datasets in NetCDF-format. 2D Water level data from the German Bight can be chosen, presented and evaluated in a web client with interactive plots. The second use case is motivated by the Marine Strategy Directive (MSD) of the EU, which demands monitoring, action plans and at least an evaluation of the ecological situation in marine environment. Information technics adapted to those of INSPIRE should be used. One of the parameters monitored and evaluated for MSD is the expansion and quality of seagrass fields. With the view towards other evaluation parameters we decompose the complex process of evaluation of seagrass in reusable process steps and implement those packages as configurable WPS.

Workflow based framework for life science informatics.

PubMed

Tiwari, Abhishek; Sekhar, Arvind K T

2007-10-01

Workflow technology is a generic mechanism to integrate diverse types of available resources (databases, servers, software applications and different services) which facilitate knowledge exchange within traditionally divergent fields such as molecular biology, clinical research, computational science, physics, chemistry and statistics. Researchers can easily incorporate and access diverse, distributed tools and data to develop their own research protocols for scientific analysis. Application of workflow technology has been reported in areas like drug discovery, genomics, large-scale gene expression analysis, proteomics, and system biology. In this article, we have discussed the existing workflow systems and the trends in applications of workflow based systems.

A study of an adaptive replication framework for orchestrated composite web services.

PubMed

Mohamed, Marwa F; Elyamany, Hany F; Nassar, Hamed M

2013-01-01

Replication is considered one of the most important techniques to improve the Quality of Services (QoS) of published Web Services. It has achieved impressive success in managing resource sharing and usage in order to moderate the energy consumed in IT environments. For a robust and successful replication process, attention should be paid to suitable time as well as the constraints and capabilities in which the process runs. The replication process is time-consuming since outsourcing some new replicas into other hosts is lengthy. Furthermore, nowadays, most of the business processes that might be implemented over the Web are composed of multiple Web services working together in two main styles: Orchestration and Choreography. Accomplishing a replication over such business processes is another challenge due to the complexity and flexibility involved. In this paper, we present an adaptive replication framework for regular and orchestrated composite Web services. The suggested framework includes a number of components for detecting unexpected and unhappy events that might occur when consuming the original published web services including failure or overloading. It also includes a specific replication controller to manage the replication process and select the best host that would encapsulate a new replica. In addition, it includes a component for predicting the incoming load in order to decrease the time needed for outsourcing new replicas, enhancing the performance greatly. A simulation environment has been created to measure the performance of the suggested framework. The results indicate that adaptive replication with prediction scenario is the best option for enhancing the performance of the replication process in an online business environment.

Using the CMS threaded framework in a production environment

DOE PAGES

Jones, C. D.; Contreras, L.; Gartung, P.; ...

2015-12-23

During 2014, the CMS Offline and Computing Organization completed the necessary changes to use the CMS threaded framework in the full production environment. We will briefly discuss the design of the CMS Threaded Framework, in particular how the design affects scaling performance. We will then cover the effort involved in getting both the CMSSW application software and the workflow management system ready for using multiple threads for production. Finally, we will present metrics on the performance of the application and workflow system as well as the difficulties which were uncovered. As a result, we will end with CMS' plans formore » using the threaded framework to do production for LHC Run 2.« less

Using EHR audit trail logs to analyze clinical workflow: A case study from community-based ambulatory clinics.

PubMed

Wu, Danny T Y; Smart, Nikolas; Ciemins, Elizabeth L; Lanham, Holly J; Lindberg, Curt; Zheng, Kai

2017-01-01

To develop a workflow-supported clinical documentation system, it is a critical first step to understand clinical workflow. While Time and Motion studies has been regarded as the gold standard of workflow analysis, this method can be resource consuming and its data may be biased due to the cognitive limitation of human observers. In this study, we aimed to evaluate the feasibility and validity of using EHR audit trail logs to analyze clinical workflow. Specifically, we compared three known workflow changes from our previous study with the corresponding EHR audit trail logs of the study participants. The results showed that EHR audit trail logs can be a valid source for clinical workflow analysis, and can provide an objective view of clinicians' behaviors, multi-dimensional comparisons, and a highly extensible analysis framework.

Metadata Management on the SCEC PetaSHA Project: Helping Users Describe, Discover, Understand, and Use Simulation Data in a Large-Scale Scientific Collaboration

NASA Astrophysics Data System (ADS)

Okaya, D.; Deelman, E.; Maechling, P.; Wong-Barnum, M.; Jordan, T. H.; Meyers, D.

2007-12-01

Large scientific collaborations, such as the SCEC Petascale Cyberfacility for Physics-based Seismic Hazard Analysis (PetaSHA) Project, involve interactions between many scientists who exchange ideas and research results. These groups must organize, manage, and make accessible their community materials of observational data, derivative (research) results, computational products, and community software. The integration of scientific workflows as a paradigm to solve complex computations provides advantages of efficiency, reliability, repeatability, choices, and ease of use. The underlying resource needed for a scientific workflow to function and create discoverable and exchangeable products is the construction, tracking, and preservation of metadata. In the scientific workflow environment there is a two-tier structure of metadata. Workflow-level metadata and provenance describe operational steps, identity of resources, execution status, and product locations and names. Domain-level metadata essentially define the scientific meaning of data, codes and products. To a large degree the metadata at these two levels are separate. However, between these two levels is a subset of metadata produced at one level but is needed by the other. This crossover metadata suggests that some commonality in metadata handling is needed. SCEC researchers are collaborating with computer scientists at SDSC, the USC Information Sciences Institute, and Carnegie Mellon Univ. in order to perform earthquake science using high-performance computational resources. A primary objective of the "PetaSHA" collaboration is to perform physics-based estimations of strong ground motion associated with real and hypothetical earthquakes located within Southern California. Construction of 3D earth models, earthquake representations, and numerical simulation of seismic waves are key components of these estimations. Scientific workflows are used to orchestrate the sequences of scientific tasks and to access distributed computational facilities such as the NSF TeraGrid. Different types of metadata are produced and captured within the scientific workflows. One workflow within PetaSHA ("Earthworks") performs a linear sequence of tasks with workflow and seismological metadata preserved. Downstream scientific codes ingest these metadata produced by upstream codes. The seismological metadata uses attribute-value pairing in plain text; an identified need is to use more advanced handling methods. Another workflow system within PetaSHA ("Cybershake") involves several complex workflows in order to perform statistical analysis of ground shaking due to thousands of hypothetical but plausible earthquakes. Metadata management has been challenging due to its construction around a number of legacy scientific codes. We describe difficulties arising in the scientific workflow due to the lack of this metadata and suggest corrective steps, which in some cases include the cultural shift of domain science programmers coding for metadata.

Managing the life cycle of electronic clinical documents.

PubMed

Payne, Thomas H; Graham, Gail

2006-01-01

To develop a model of the life cycle of clinical documents from inception to use in a person's medical record, including workflow requirements from clinical practice, local policy, and regulation. We propose a model for the life cycle of clinical documents as a framework for research on documentation within electronic medical record (EMR) systems. Our proposed model includes three axes: the stages of the document, the roles of those involved with the document, and the actions those involved may take on the document at each stage. The model includes the rules to describe who (in what role) can perform what actions on the document, and at what stages they can perform them. Rules are derived from needs of clinicians, and requirements of hospital bylaws and regulators. Our model encompasses current practices for paper medical records and workflow in some EMR systems. Commercial EMR systems include methods for implementing document workflow rules. Workflow rules that are part of this model mirror functionality in the Department of Veterans Affairs (VA) EMR system where the Authorization/ Subscription Utility permits document life cycle rules to be written in English-like fashion. Creating a model of the life cycle of clinical documents serves as a framework for discussion of document workflow, how rules governing workflow can be implemented in EMR systems, and future research of electronic documentation.

Development of a tethered personal health record framework for early end-of-life discussions.

PubMed

Bose-Brill, Seuli; Kretovics, Matthew; Ballenger, Taylor; Modan, Gabriella; Lai, Albert; Belanger, Lindsay; Koesters, Stephen; Pressler-Vydra, Taylor; Wills, Celia

2016-06-01

End-of-life planning, known as advance care planning (ACP), is associated with numerous positive outcomes, such as improved patient satisfaction with care and improved patient quality of life in terminal illness. However, patient-provider ACP conversations are rarely performed or documented due to a number of barriers, including time required, perceived lack of skill, and a limited number of resources. Use of tethered personal health records (PHRs) may help streamline ACP conversations and documentations for outpatient workflows. Our objective was to develop an ACP-PHR framework that would be for use in a primary care, outpatient setting. Qualitative content analysis of focus groups and cognitive interviews (participatory design). A novel PHR-ACP tool was developed and tested using data and feedback collected from 4 patient focus groups (n = 13), 1 provider focus group (n = 4), and cognitive interviews (n = 22). Patient focus groups helped develop a focused, 4-question PHR communication tool. Cognitive interviews revealed that, while patients felt framework content and workflow were generally intuitive, minor changes to content and workflow would optimize the framework. A focused framework for electronic ACP communication using a patient portal tethered to the PHR was developed. This framework may provide an efficient way to have ACP conversations in busy outpatient settings.

NASA SensorWeb and OGC Standards for Disaster Management

NASA Technical Reports Server (NTRS)

Mandl, Dan

2010-01-01

I. Goal: Enable user to cost-effectively find and create customized data products to help manage disasters; a) On-demand; b) Low cost and non-specialized tools such as Google Earth and browsers; c) Access via open network but with sufficient security. II. Use standards to interface various sensors and resultant data: a) Wrap sensors in Open Geospatial Consortium (OGC) standards; b) Wrap data processing algorithms and servers with OGC standards c) Use standardized workflows to orchestrate and script the creation of these data; products. III. Target Web 2.0 mass market: a) Make it simple and easy to use; b) Leverage new capabilities and tools that are emerging; c) Improve speed and responsiveness.

Open-Source, Distributed Computational Environment for Virtual Materials Exploration

DTIC Science & Technology

2015-01-01

compromising structural integrity.  For  example, advanced designs could specify advanced materials processing techniques such as heat  treatments  in specific...orchestration of execution of multiple standalone codes at varying  length scales will need advanced  high ‐performance computing (HPC) integration in...possible hooks that could be used to  coordinate larger  workflows spanning tools developed by different groups.    The  high  level approach explored

Semantics-enabled service discovery framework in the SIMDAT pharma grid.

PubMed

Qu, Cangtao; Zimmermann, Falk; Kumpf, Kai; Kamuzinzi, Richard; Ledent, Valérie; Herzog, Robert

2008-03-01

We present the design and implementation of a semantics-enabled service discovery framework in the data Grids for process and product development using numerical simulation and knowledge discovery (SIMDAT) Pharma Grid, an industry-oriented Grid environment for integrating thousands of Grid-enabled biological data services and analysis services. The framework consists of three major components: the Web ontology language (OWL)-description logic (DL)-based biological domain ontology, OWL Web service ontology (OWL-S)-based service annotation, and semantic matchmaker based on the ontology reasoning. Built upon the framework, workflow technologies are extensively exploited in the SIMDAT to assist biologists in (semi)automatically performing in silico experiments. We present a typical usage scenario through the case study of a biological workflow: IXodus.

Earth Science Mining Web Services

NASA Astrophysics Data System (ADS)

Pham, L. B.; Lynnes, C. S.; Hegde, M.; Graves, S.; Ramachandran, R.; Maskey, M.; Keiser, K.

2008-12-01

To allow scientists further capabilities in the area of data mining and web services, the Goddard Earth Sciences Data and Information Services Center (GES DISC) and researchers at the University of Alabama in Huntsville (UAH) have developed a system to mine data at the source without the need of network transfers. The system has been constructed by linking together several pre-existing technologies: the Simple Scalable Script-based Science Processor for Measurements (S4PM), a processing engine at the GES DISC; the Algorithm Development and Mining (ADaM) system, a data mining toolkit from UAH that can be configured in a variety of ways to create customized mining processes; ActiveBPEL, a workflow execution engine based on BPEL (Business Process Execution Language); XBaya, a graphical workflow composer; and the EOS Clearinghouse (ECHO). XBaya is used to construct an analysis workflow at UAH using ADaM components, which are also installed remotely at the GES DISC, wrapped as Web Services. The S4PM processing engine searches ECHO for data using space-time criteria, staging them to cache, allowing the ActiveBPEL engine to remotely orchestrates the processing workflow within S4PM. As mining is completed, the output is placed in an FTP holding area for the end user. The goals are to give users control over the data they want to process, while mining data at the data source using the server's resources rather than transferring the full volume over the internet. These diverse technologies have been infused into a functioning, distributed system with only minor changes to the underlying technologies. The key to this infusion is the loosely coupled, Web- Services based architecture: All of the participating components are accessible (one way or another) through (Simple Object Access Protocol) SOAP-based Web Services.

A python framework for environmental model uncertainty analysis

USGS Publications Warehouse

White, Jeremy; Fienen, Michael N.; Doherty, John E.

2016-01-01

We have developed pyEMU, a python framework for Environmental Modeling Uncertainty analyses, open-source tool that is non-intrusive, easy-to-use, computationally efficient, and scalable to highly-parameterized inverse problems. The framework implements several types of linear (first-order, second-moment (FOSM)) and non-linear uncertainty analyses. The FOSM-based analyses can also be completed prior to parameter estimation to help inform important modeling decisions, such as parameterization and objective function formulation. Complete workflows for several types of FOSM-based and non-linear analyses are documented in example notebooks implemented using Jupyter that are available in the online pyEMU repository. Example workflows include basic parameter and forecast analyses, data worth analyses, and error-variance analyses, as well as usage of parameter ensemble generation and management capabilities. These workflows document the necessary steps and provides insights into the results, with the goal of educating users not only in how to apply pyEMU, but also in the underlying theory of applied uncertainty quantification.

Automatic Earth observation data service based on reusable geo-processing workflow

NASA Astrophysics Data System (ADS)

Chen, Nengcheng; Di, Liping; Gong, Jianya; Yu, Genong; Min, Min

2008-12-01

A common Sensor Web data service framework for Geo-Processing Workflow (GPW) is presented as part of the NASA Sensor Web project. This framework consists of a data service node, a data processing node, a data presentation node, a Catalogue Service node and BPEL engine. An abstract model designer is used to design the top level GPW model, model instantiation service is used to generate the concrete BPEL, and the BPEL execution engine is adopted. The framework is used to generate several kinds of data: raw data from live sensors, coverage or feature data, geospatial products, or sensor maps. A scenario for an EO-1 Sensor Web data service for fire classification is used to test the feasibility of the proposed framework. The execution time and influences of the service framework are evaluated. The experiments show that this framework can improve the quality of services for sensor data retrieval and processing.

Where Does My Augmented Reality Learning Experience (ARLE) Belong? A Student and Teacher Perspective to Positioning ARLEs

ERIC Educational Resources Information Center

Drljevic, Neven; Wong, Lung Hsiang; Boticki, Ivica

2017-01-01

The paper provides a high-level review of the current state of techno-pedagogical design in Augmented Reality Learning Experiences (ARLEs). The review is based on a rubric constructed from the Meaningful Learning with ICT framework and the Orchestration Load reduction framework, providing, respectively, a view of primarily student- and primarily…

A framework for streamlining research workflow in neuroscience and psychology

PubMed Central

Kubilius, Jonas

2014-01-01

Successful accumulation of knowledge is critically dependent on the ability to verify and replicate every part of scientific conduct. However, such principles are difficult to enact when researchers continue to resort on ad-hoc workflows and with poorly maintained code base. In this paper I examine the needs of neuroscience and psychology community, and introduce psychopy_ext, a unifying framework that seamlessly integrates popular experiment building, analysis and manuscript preparation tools by choosing reasonable defaults and implementing relatively rigid patterns of workflow. This structure allows for automation of multiple tasks, such as generated user interfaces, unit testing, control analyses of stimuli, single-command access to descriptive statistics, and publication quality plotting. Taken together, psychopy_ext opens an exciting possibility for a faster, more robust code development and collaboration for researchers. PMID:24478691

Comprehensive, powerful, efficient, intuitive: a new software framework for clinical imaging applications

NASA Astrophysics Data System (ADS)

Augustine, Kurt E.; Holmes, David R., III; Hanson, Dennis P.; Robb, Richard A.

2006-03-01

One of the greatest challenges for a software engineer is to create a complex application that is comprehensive enough to be useful to a diverse set of users, yet focused enough for individual tasks to be carried out efficiently with minimal training. This "powerful yet simple" paradox is particularly prevalent in advanced medical imaging applications. Recent research in the Biomedical Imaging Resource (BIR) at Mayo Clinic has been directed toward development of an imaging application framework that provides powerful image visualization/analysis tools in an intuitive, easy-to-use interface. It is based on two concepts very familiar to physicians - Cases and Workflows. Each case is associated with a unique patient and a specific set of routine clinical tasks, or a workflow. Each workflow is comprised of an ordered set of general-purpose modules which can be re-used for each unique workflow. Clinicians help describe and design the workflows, and then are provided with an intuitive interface to both patient data and analysis tools. Since most of the individual steps are common to many different workflows, the use of general-purpose modules reduces development time and results in applications that are consistent, stable, and robust. While the development of individual modules may reflect years of research by imaging scientists, new customized workflows based on the new modules can be developed extremely fast. If a powerful, comprehensive application is difficult to learn and complicated to use, it will be unacceptable to most clinicians. Clinical image analysis tools must be intuitive and effective or they simply will not be used.

Taking advantage of HTML5 browsers to realize the concepts of session state and workflow sharing in web-tool applications

NASA Astrophysics Data System (ADS)

Suftin, I.; Read, J. S.; Walker, J.

2013-12-01

Scientists prefer not having to be tied down to a specific machine or operating system in order to analyze local and remote data sets or publish work. Increasingly, analysis has been migrating to decentralized web services and data sets, using web clients to provide the analysis interface. While simplifying workflow access, analysis, and publishing of data, the move does bring with it its own unique set of issues. Web clients used for analysis typically offer workflows geared towards a single user, with steps and results that are often difficult to recreate and share with others. Furthermore, workflow results often may not be easily used as input for further analysis. Older browsers further complicate things by having no way to maintain larger chunks of information, often offloading the job of storage to the back-end server or trying to squeeze it into a cookie. It has been difficult to provide a concept of "session storage" or "workflow sharing" without a complex orchestration of the back-end for storage depending on either a centralized file system or database. With the advent of HTML5, browsers gained the ability to store more information through the use of the Web Storage API (a browser-cookie holds a maximum of 4 kilobytes). Web Storage gives us the ability to store megabytes of arbitrary data in-browser either with an expiration date or just for a session. This allows scientists to create, update, persist and share their workflow without depending on the backend to store session information, providing the flexibility for new web-based workflows to emerge. In the DSASWeb portal ( http://cida.usgs.gov/DSASweb/ ), using these techniques, the representation of every step in the analyst's workflow is stored as plain-text serialized JSON, which we can generate as a text file and provide to the analyst as an upload. This file may then be shared with others and loaded back into the application, restoring the application to the state it was in when the session file was generated. A user may then view results produced during that session or go back and alter input parameters, creating new results and producing new, unique sessions which they can then again share. This technique not only provides independence for the user to manage their session as they like, but also allows much greater freedom for the application provider to scale out without having to worry about carrying over user information or maintaining it in a central location.

Control and Information Systems for the National Ignition Facility

DOE PAGES

Brunton, Gordon; Casey, Allan; Christensen, Marvin; ...

2017-03-23

Orchestration of every National Ignition Facility (NIF) shot cycle is managed by the Integrated Computer Control System (ICCS), which uses a scalable software architecture running code on more than 1950 front-end processors, embedded controllers, and supervisory servers. The ICCS operates laser and industrial control hardware containing 66 000 control and monitor points to ensure that all of NIF’s laser beams arrive at the target within 30 ps of each other and are aligned to a pointing accuracy of less than 50 μm root-mean-square, while ensuring that a host of diagnostic instruments record data in a few billionths of a second.more » NIF’s automated control subsystems are built from a common object-oriented software framework that distributes the software across the computer network and achieves interoperation between different software languages and target architectures. A large suite of business and scientific software tools supports experimental planning, experimental setup, facility configuration, and post-shot analysis. Standard business services using open-source software, commercial workflow tools, and database and messaging technologies have been developed. An information technology infrastructure consisting of servers, network devices, and storage provides the foundation for these systems. Thus, this work is an overview of the control and information systems used to support a wide variety of experiments during the National Ignition Campaign.« less

Control and Information Systems for the National Ignition Facility

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

Brunton, Gordon; Casey, Allan; Christensen, Marvin

Orchestration of every National Ignition Facility (NIF) shot cycle is managed by the Integrated Computer Control System (ICCS), which uses a scalable software architecture running code on more than 1950 front-end processors, embedded controllers, and supervisory servers. The ICCS operates laser and industrial control hardware containing 66 000 control and monitor points to ensure that all of NIF’s laser beams arrive at the target within 30 ps of each other and are aligned to a pointing accuracy of less than 50 μm root-mean-square, while ensuring that a host of diagnostic instruments record data in a few billionths of a second.more » NIF’s automated control subsystems are built from a common object-oriented software framework that distributes the software across the computer network and achieves interoperation between different software languages and target architectures. A large suite of business and scientific software tools supports experimental planning, experimental setup, facility configuration, and post-shot analysis. Standard business services using open-source software, commercial workflow tools, and database and messaging technologies have been developed. An information technology infrastructure consisting of servers, network devices, and storage provides the foundation for these systems. Thus, this work is an overview of the control and information systems used to support a wide variety of experiments during the National Ignition Campaign.« less

A Role for Semantic Web Technologies in Patient Record Data Collection

NASA Astrophysics Data System (ADS)

Ogbuji, Chimezie

Business Process Management Systems (BPMS) are a component of the stack of Web standards that comprise Service Oriented Architecture (SOA). Such systems are representative of the architectural framework of modern information systems built in an enterprise intranet and are in contrast to systems built for deployment on the larger World Wide Web. The REST architectural style is an emerging style for building loosely coupled systems based purely on the native HTTP protocol. It is a coordinated set of architectural constraints with a goal to minimize latency, maximize the independence and scalability of distributed components, and facilitate the use of intermediary processors.Within the development community for distributed, Web-based systems, there has been a debate regarding themerits of both approaches. In some cases, there are legitimate concerns about the differences in both architectural styles. In other cases, the contention seems to be based on concerns that are marginal at best. In this chapter, we will attempt to contribute to this debate by focusing on a specific, deployed use case that emphasizes the role of the Semantic Web, a simple Web application architecture that leverages the use of declarative XML processing, and the needs of a workflow system. The use case involves orchestrating a work process associated with the data entry of structured patient record content into a research registry at the Cleveland Clinic's Clinical Investigation department in the Heart and Vascular Institute.

VERCE: a productive e-Infrastructure and e-Science environment for data-intensive seismology research

NASA Astrophysics Data System (ADS)

Vilotte, J. P.; Atkinson, M.; Spinuso, A.; Rietbrock, A.; Michelini, A.; Igel, H.; Frank, A.; Carpené, M.; Schwichtenberg, H.; Casarotti, E.; Filgueira, R.; Garth, T.; Germünd, A.; Klampanos, I.; Krause, A.; Krischer, L.; Leong, S. H.; Magnoni, F.; Matser, J.; Moguilny, G.

2015-12-01

Seismology addresses both fundamental problems in understanding the Earth's internal wave sources and structures and augmented societal applications, like earthquake and tsunami hazard assessment and risk mitigation; and puts a premium on open-data accessible by the Federated Digital Seismological Networks. The VERCE project, "Virtual Earthquake and seismology Research Community e-science environment in Europe", has initiated a virtual research environment to support complex orchestrated workflows combining state-of-art wave simulation codes and data analysis tools on distributed computing and data infrastructures (DCIs) along with multiple sources of observational data and new capabilities to combine simulation results with observational data. The VERCE Science Gateway provides a view of all the available resources, supporting collaboration with shared data and methods, with data access controls. The mapping to DCIs handles identity management, authority controls, transformations between representations and controls, and access to resources. The framework for computational science that provides simulation codes, like SPECFEM3D, democratizes their use by getting data from multiple sources, managing Earth models and meshes, distilling them as input data, and capturing results with meta-data. The dispel4py data-intensive framework allows for developing data-analysis applications using Python and the ObsPy library, which can be executed on different DCIs. A set of tools allows coupling with seismology and external data services. Provenance driven tools validate results and show relationships between data to facilitate method improvement. Lessons learned from VERCE training lead us to conclude that solid-Earth scientists could make significant progress by using VERCE e-science environment. VERCE has already contributed to the European Plate Observation System (EPOS), and is part of the EPOS implementation phase. Its cross-disciplinary capabilities are being extended for the EPOS implantation phase.

Abstracting application deployment on Cloud infrastructures

NASA Astrophysics Data System (ADS)

Aiftimiei, D. C.; Fattibene, E.; Gargana, R.; Panella, M.; Salomoni, D.

2017-10-01

Deploying a complex application on a Cloud-based infrastructure can be a challenging task. In this contribution we present an approach for Cloud-based deployment of applications and its present or future implementation in the framework of several projects, such as “!CHAOS: a cloud of controls” [1], a project funded by MIUR (Italian Ministry of Research and Education) to create a Cloud-based deployment of a control system and data acquisition framework, “INDIGO-DataCloud” [2], an EC H2020 project targeting among other things high-level deployment of applications on hybrid Clouds, and “Open City Platform”[3], an Italian project aiming to provide open Cloud solutions for Italian Public Administrations. We considered to use an orchestration service to hide the complex deployment of the application components, and to build an abstraction layer on top of the orchestration one. Through Heat [4] orchestration service, we prototyped a dynamic, on-demand, scalable platform of software components, based on OpenStack infrastructures. On top of the orchestration service we developed a prototype of a web interface exploiting the Heat APIs. The user can start an instance of the application without having knowledge about the underlying Cloud infrastructure and services. Moreover, the platform instance can be customized by choosing parameters related to the application such as the size of a File System or the number of instances of a NoSQL DB cluster. As soon as the desired platform is running, the web interface offers the possibility to scale some infrastructure components. In this contribution we describe the solution design and implementation, based on the application requirements, the details of the development of both the Heat templates and of the web interface, together with possible exploitation strategies of this work in Cloud data centers.

32 CFR 159.6 - Procedures.

Code of Federal Regulations, 2011 CFR

2011-07-01

....49, “Orchestrating, Synchronizing, and Integrating Program Management of Contingency Acquisition... increased risk or planned or ongoing military operations, including how PSC personnel will be rapidly... 13 shall provide the framework for the development of guidance and procedures without regard to the...

Supporting Collective Inquiry: A Technology Framework for Distributed Learning

NASA Astrophysics Data System (ADS)

Tissenbaum, Michael

This design-based study describes the implementation and evaluation of a technology framework to support smart classrooms and Distributed Technology Enhanced Learning (DTEL) called SAIL Smart Space (S3). S3 is an open-source technology framework designed to support students engaged in inquiry investigations as a knowledge community. To evaluate the effectiveness of S3 as a generalizable technology framework, a curriculum named PLACE (Physics Learning Across Contexts and Environments) was developed to support two grade-11 physics classes (n = 22; n = 23) engaged in a multi-context inquiry curriculum based on the Knowledge Community and Inquiry (KCI) pedagogical model. This dissertation outlines three initial design studies that established a set of design principles for DTEL curricula, and related technology infrastructures. These principles guided the development of PLACE, a twelve-week inquiry curriculum in which students drew upon their community-generated knowledge base as a source of evidence for solving ill-structured physics problems based on the physics of Hollywood movies. During the culminating smart classroom activity, the S3 framework played a central role in orchestrating student activities, including managing the flow of materials and students using real-time data mining and intelligent agents that responded to emergent class patterns. S3 supported students' construction of knowledge through the use individual, collective and collaborative scripts and technologies, including tablets and interactive large-format displays. Aggregate and real-time ambient visualizations helped the teacher act as a wondering facilitator, supporting students in their inquiry where needed. A teacher orchestration tablet gave the teacher some control over the flow of the scripted activities, and alerted him to critical moments for intervention. Analysis focuses on S3's effectiveness in supporting students' inquiry across multiple learning contexts and scales of time, and in making timely and effective use of the community's knowledge base, towards producing solutions to sophisticated, ill defined problems in the domain of physics. Video analysis examined whether S3 supported teacher orchestration, freeing him to focus less on classroom management and more on students' inquiry. Three important outcomes of this research are a set of design principles for DTEL environments, a specific technology infrastructure (S3), and a DTEL research framework.

Kwf-Grid workflow management system for Earth science applications

NASA Astrophysics Data System (ADS)

Tran, V.; Hluchy, L.

2009-04-01

In this paper, we present workflow management tool for Earth science applications in EGEE. The workflow management tool was originally developed within K-wf Grid project for GT4 middleware and has many advanced features like semi-automatic workflow composition, user-friendly GUI for managing workflows, knowledge management. In EGEE, we are porting the workflow management tool to gLite middleware for Earth science applications K-wf Grid workflow management system was developed within "Knowledge-based Workflow System for Grid Applications" under the 6th Framework Programme. The workflow mangement system intended to - semi-automatically compose a workflow of Grid services, - execute the composed workflow application in a Grid computing environment, - monitor the performance of the Grid infrastructure and the Grid applications, - analyze the resulting monitoring information, - capture the knowledge that is contained in the information by means of intelligent agents, - and finally to reuse the joined knowledge gathered from all participating users in a collaborative way in order to efficiently construct workflows for new Grid applications. Kwf Grid workflow engines can support different types of jobs (e.g. GRAM job, web services) in a workflow. New class of gLite job has been added to the system, allows system to manage and execute gLite jobs in EGEE infrastructure. The GUI has been adapted to the requirements of EGEE users, new credential management servlet is added to portal. Porting K-wf Grid workflow management system to gLite would allow EGEE users to use the system and benefit from its avanced features. The system is primarly tested and evaluated with applications from ES clusters.

eMZed: an open source framework in Python for rapid and interactive development of LC/MS data analysis workflows.

PubMed

Kiefer, Patrick; Schmitt, Uwe; Vorholt, Julia A

2013-04-01

The Python-based, open-source eMZed framework was developed for mass spectrometry (MS) users to create tailored workflows for liquid chromatography (LC)/MS data analysis. The goal was to establish a unique framework with comprehensive basic functionalities that are easy to apply and allow for the extension and modification of the framework in a straightforward manner. eMZed supports the iterative development and prototyping of individual evaluation strategies by providing a computing environment and tools for inspecting and modifying underlying LC/MS data. The framework specifically addresses non-expert programmers, as it requires only basic knowledge of Python and relies largely on existing successful open-source software, e.g. OpenMS. The framework eMZed and its documentation are freely available at http://emzed.biol.ethz.ch/. eMZed is published under the GPL 3.0 license, and an online discussion group is available at https://groups.google.com/group/emzed-users. Supplementary data are available at Bioinformatics online.

Autonomic Management of Application Workflows on Hybrid Computing Infrastructure

DOE PAGES

Kim, Hyunjoo; el-Khamra, Yaakoub; Rodero, Ivan; ...

2011-01-01

In this paper, we present a programming and runtime framework that enables the autonomic management of complex application workflows on hybrid computing infrastructures. The framework is designed to address system and application heterogeneity and dynamics to ensure that application objectives and constraints are satisfied. The need for such autonomic system and application management is becoming critical as computing infrastructures become increasingly heterogeneous, integrating different classes of resources from high-end HPC systems to commodity clusters and clouds. For example, the framework presented in this paper can be used to provision the appropriate mix of resources based on application requirements and constraints.more » The framework also monitors the system/application state and adapts the application and/or resources to respond to changing requirements or environment. To demonstrate the operation of the framework and to evaluate its ability, we employ a workflow used to characterize an oil reservoir executing on a hybrid infrastructure composed of TeraGrid nodes and Amazon EC2 instances of various types. Specifically, we show how different applications objectives such as acceleration, conservation and resilience can be effectively achieved while satisfying deadline and budget constraints, using an appropriate mix of dynamically provisioned resources. Our evaluations also demonstrate that public clouds can be used to complement and reinforce the scheduling and usage of traditional high performance computing infrastructure.« less

Alchemist multimodal workflows for diabetic retinopathy research, disease prevention and investigational drug discovery.

PubMed

Riposan, Adina; Taylor, Ian; Owens, David R; Rana, Omer; Conley, Edward C

2007-01-01

In this paper we present mechanisms for imaging and spectral data discovery, as applied to the early detection of pathologic mechanisms underlying diabetic retinopathy in research and clinical trial scenarios. We discuss the Alchemist framework, built using a generic peer-to-peer architecture, supporting distributed database queries and complex search algorithms based on workflow. The Alchemist is a domain-independent search mechanism that can be applied to search and data discovery scenarios in many areas. We illustrate Alchemist's ability to perform complex searches composed as a collection of peer-to-peer overlays, Grid-based services and workflows, e.g. applied to image and spectral data discovery, as applied to the early detection and prevention of retinal disease and investigational drug discovery. The Alchemist framework is built on top of decentralised technologies and uses industry standards such as Web services and SOAP for messaging.

Integrated pathway-based transcription regulation network mining and visualization based on gene expression profiles.

PubMed

Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko

2016-06-01

Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

Contextual cloud-based service oriented architecture for clinical workflow.

PubMed

Moreno-Conde, Jesús; Moreno-Conde, Alberto; Núñez-Benjumea, Francisco J; Parra-Calderón, Carlos

2015-01-01

Given that acceptance of systems within the healthcare domain multiple papers highlighted the importance of integrating tools with the clinical workflow. This paper analyse how clinical context management could be deployed in order to promote the adoption of cloud advanced services and within the clinical workflow. This deployment will be able to be integrated with the eHealth European Interoperability Framework promoted specifications. Throughout this paper, it is proposed a cloud-based service-oriented architecture. This architecture will implement a context management system aligned with the HL7 standard known as CCOW.

Theoretical Frameworks to Guide School Improvement

ERIC Educational Resources Information Center

Evans, Lisa; Thornton, Bill; Usinger, Janet

2012-01-01

A firm grounding in change theory can provide educational leaders with an opportunity to orchestrate meaningful organizational improvements. This article provides an opportunity for practicing leaders to review four major theories of organizational change--continuous improvement, two approaches to organizational learning, and appreciative inquiry.…

The impact of computerized provider order entry systems on inpatient clinical workflow: a literature review.

PubMed

Niazkhani, Zahra; Pirnejad, Habibollah; Berg, Marc; Aarts, Jos

2009-01-01

Previous studies have shown the importance of workflow issues in the implementation of CPOE systems and patient safety practices. To understand the impact of CPOE on clinical workflow, we developed a conceptual framework and conducted a literature search for CPOE evaluations between 1990 and June 2007. Fifty-one publications were identified that disclosed mixed effects of CPOE systems. Among the frequently reported workflow advantages were the legible orders, remote accessibility of the systems, and the shorter order turnaround times. Among the frequently reported disadvantages were the time-consuming and problematic user-system interactions, and the enforcement of a predefined relationship between clinical tasks and between providers. Regarding the diversity of findings in the literature, we conclude that more multi-method research is needed to explore CPOE's multidimensional and collective impact on especially collaborative workflow.

Understanding the dispensary workflow at the Birmingham Free Clinic: a proposed framework for an informatics intervention.

PubMed

Fisher, Arielle M; Herbert, Mary I; Douglas, Gerald P

2016-02-19

The Birmingham Free Clinic (BFC) in Pittsburgh, Pennsylvania, USA is a free, walk-in clinic that serves medically uninsured populations through the use of volunteer health care providers and an on-site medication dispensary. The introduction of an electronic medical record (EMR) has improved several aspects of clinic workflow. However, pharmacists' tasks involving medication management and dispensing have become more challenging since EMR implementation due to its inability to support workflows between the medical and pharmaceutical services. To inform the design of a systematic intervention, we conducted a needs assessment study to identify workflow challenges and process inefficiencies in the dispensary. We used contextual inquiry to document the dispensary workflow and facilitate identification of critical aspects of intervention design specific to the user. Pharmacists were observed according to contextual inquiry guidelines. Graphical models were produced to aid data and process visualization. We created a list of themes describing workflow challenges and asked the pharmacists to rank them in order of significance to narrow the scope of intervention design. Three pharmacists were observed at the BFC. Observer notes were documented and analyzed to produce 13 themes outlining the primary challenges pharmacists encounter during dispensation at the BFC. The dispensary workflow is labor intensive, redundant, and inefficient when integrated with the clinical service. Observations identified inefficiencies that may benefit from the introduction of informatics interventions including: medication labeling, insufficient process notification, triple documentation, and inventory control. We propose a system for Prescription Management and General Inventory Control (RxMAGIC). RxMAGIC is a framework designed to mitigate workflow challenges and improve the processes of medication management and inventory control. While RxMAGIC is described in the context of the BFC dispensary, we believe it will be generalizable to pharmacies in other low-resource settings, both domestically and internationally.

It's All About the Data: Workflow Systems and Weather

NASA Astrophysics Data System (ADS)

Plale, B.

2009-05-01

Digital data is fueling new advances in the computational sciences, particularly geospatial research as environmental sensing grows more practical through reduced technology costs, broader network coverage, and better instruments. e-Science research (i.e., cyberinfrastructure research) has responded to data intensive computing with tools, systems, and frameworks that support computationally oriented activities such as modeling, analysis, and data mining. Workflow systems support execution of sequences of tasks on behalf of a scientist. These systems, such as Taverna, Apache ODE, and Kepler, when built as part of a larger cyberinfrastructure framework, give the scientist tools to construct task graphs of execution sequences, often through a visual interface for connecting task boxes together with arcs representing control flow or data flow. Unlike business processing workflows, scientific workflows expose a high degree of detail and control during configuration and execution. Data-driven science imposes unique needs on workflow frameworks. Our research is focused on two issues. The first is the support for workflow-driven analysis over all kinds of data sets, including real time streaming data and locally owned and hosted data. The second is the essential role metadata/provenance collection plays in data driven science, for discovery, determining quality, for science reproducibility, and for long-term preservation. The research has been conducted over the last 6 years in the context of cyberinfrastructure for mesoscale weather research carried out as part of the Linked Environments for Atmospheric Discovery (LEAD) project. LEAD has pioneered new approaches for integrating complex weather data, assimilation, modeling, mining, and cyberinfrastructure systems. Workflow systems have the potential to generate huge volumes of data. Without some form of automated metadata capture, either metadata description becomes largely a manual task that is difficult if not impossible under high-volume conditions, or the searchability and manageability of the resulting data products is disappointingly low. The provenance of a data product is a record of its lineage, or trace of the execution history that resulted in the product. The provenance of a forecast model result, e.g., captures information about the executable version of the model, configuration parameters, input data products, execution environment, and owner. Provenance enables data to be properly attributed and captures critical parameters about the model run so the quality of the result can be ascertained. Proper provenance is essential to providing reproducible scientific computing results. Workflow languages used in science discovery are complete programming languages, and in theory can support any logic expressible by a programming language. The execution environments supporting the workflow engines, on the other hand, are subject to constraints on physical resources, and hence in practice the workflow task graphs used in science utilize relatively few of the cataloged workflow patterns. It is important to note that these workflows are executed on demand, and are executed once. Into this context is introduced the need for science discovery that is responsive to real time information. If we can use simple programming models and abstractions to make scientific discovery involving real-time data accessible to specialists who share and utilize data across scientific domains, we bring science one step closer to solving the largest of human problems.

Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics

PubMed Central

Giacomoni, Franck; Le Corguillé, Gildas; Monsoor, Misharl; Landi, Marion; Pericard, Pierre; Pétéra, Mélanie; Duperier, Christophe; Tremblay-Franco, Marie; Martin, Jean-François; Jacob, Daniel; Goulitquer, Sophie; Thévenot, Etienne A.; Caron, Christophe

2015-01-01

Summary: The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. Availability and implementation: http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). Contact: contact@workflow4metabolomics.org PMID:25527831

Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics.

PubMed

Giacomoni, Franck; Le Corguillé, Gildas; Monsoor, Misharl; Landi, Marion; Pericard, Pierre; Pétéra, Mélanie; Duperier, Christophe; Tremblay-Franco, Marie; Martin, Jean-François; Jacob, Daniel; Goulitquer, Sophie; Thévenot, Etienne A; Caron, Christophe

2015-05-01

The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). contact@workflow4metabolomics.org. © The Author 2014. Published by Oxford University Press.

PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows

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

Deelman, Ewa; Carothers, Christopher; Mandal, Anirban

Here we report that computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Therefore, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation andmore » data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.« less

PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows

DOE PAGES

Deelman, Ewa; Carothers, Christopher; Mandal, Anirban; ...

2015-07-14

Here we report that computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Therefore, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation andmore » data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.« less

Resource Aware Intelligent Network Services (RAINS) Final Technical Report

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

Lehman, Tom; Yang, Xi

The Resource Aware Intelligent Network Services (RAINS) project conducted research and developed technologies in the area of cyber infrastructure resource modeling and computation. The goal of this work was to provide a foundation to enable intelligent, software defined services which spanned the network AND the resources which connect to the network. A Multi-Resource Service Plane (MRSP) was defined, which allows resource owners/managers to locate and place themselves from a topology and service availability perspective within the dynamic networked cyberinfrastructure ecosystem. The MRSP enables the presentation of integrated topology views and computation results which can include resources across the spectrum ofmore » compute, storage, and networks. The RAINS project developed MSRP includes the following key components: i) Multi-Resource Service (MRS) Ontology/Multi-Resource Markup Language (MRML), ii) Resource Computation Engine (RCE), iii) Modular Driver Framework (to allow integration of a variety of external resources). The MRS/MRML is a general and extensible modeling framework that allows for resource owners to model, or describe, a wide variety of resource types. All resources are described using three categories of elements: Resources, Services, and Relationships between the elements. This modeling framework defines a common method for the transformation of cyber infrastructure resources into data in the form of MRML models. In order to realize this infrastructure datification, the RAINS project developed a model based computation system, i.e. “RAINS Computation Engine (RCE)”. The RCE has the ability to ingest, process, integrate, and compute based on automatically generated MRML models. The RCE interacts with the resources thru system drivers which are specific to the type of external network or resource controller. The RAINS project developed a modular and pluggable driver system which facilities a variety of resource controllers to automatically generate, maintain, and distribute MRML based resource descriptions. Once all of the resource topologies are absorbed by the RCE, a connected graph of the full distributed system topology is constructed, which forms the basis for computation and workflow processing. The RCE includes a Modular Computation Element (MCE) framework which allows for tailoring of the computation process to the specific set of resources under control, and the services desired. The input and output of an MCE are both model data based on MRS/MRML ontology and schema. Some of the RAINS project accomplishments include: Development of general and extensible multi-resource modeling framework; Design of a Resource Computation Engine (RCE) system which includes the following key capabilities; Absorb a variety of multi-resource model types and build integrated models; Novel architecture which uses model based communications across the full stack for all Flexible provision of abstract or intent based user facing interfaces; Workflow processing based on model descriptions; Release of the RCE as an open source software; Deployment of RCE in the University of Maryland/Mid-Atlantic Crossroad ScienceDMZ in prototype mode with a plan under way to transition to production; Deployment at the Argonne National Laboratory DTN Facility in prototype mode; Selection of RCE by the DOE SENSE (SDN for End-to-end Networked Science at the Exascale) project as the basis for their orchestration service.« less

Preclinical Feasibility of a Technology Framework for MRI-guided Iliac Angioplasty

PubMed Central

Rube, Martin A.; Fernandez-Gutierrez, Fabiola; Cox, Benjamin F.; Holbrook, Andrew B.; Houston, J. Graeme; White, Richard D.; McLeod, Helen; Fatahi, Mahsa; Melzer, Andreas

2015-01-01

Purpose Interventional MRI has significant potential for image guidance of iliac angioplasty and related vascular procedures. A technology framework with in-room image display, control, communication and MRI-guided intervention techniques was designed and tested for its potential to provide safe, fast and efficient MRI-guided angioplasty of the iliac arteries. Methods A 1.5T MRI scanner was adapted for interactive imaging during endovascular procedures using new or modified interventional devices such as guidewires and catheters. A perfused vascular phantom was used for testing. Pre-, intra- and post-procedural visualization and measurement of vascular morphology and flow was implemented. A detailed analysis of X-Ray fluoroscopic angiography workflow was conducted and applied. Two interventional radiologists and one physician in training performed 39 procedures. All procedures were timed and analyzed. Results MRI-guided iliac angioplasty procedures were successfully performed with progressive adaptation of techniques and workflow. The workflow, setup and protocol enabled a reduction in table time for a dedicated MRI-guided procedure to 6 min 33 s with a mean procedure time of 9 min 2 s, comparable to the mean procedure time of 8 min 42 s for the standard X-Ray guided procedure. Conclusions MRI-guided iliac vascular interventions were found to be feasible and practical using this framework and optimized workflow. In particular the real-time flow analysis was found to be helpful for pre- and post-interventional assessments. Design optimization of the catheters and in vivo experiments are required before clinical evaluation. PMID:25102933

The CARMEN software as a service infrastructure.

PubMed

Weeks, Michael; Jessop, Mark; Fletcher, Martyn; Hodge, Victoria; Jackson, Tom; Austin, Jim

2013-01-28

The CARMEN platform allows neuroscientists to share data, metadata, services and workflows, and to execute these services and workflows remotely via a Web portal. This paper describes how we implemented a service-based infrastructure into the CARMEN Virtual Laboratory. A Software as a Service framework was developed to allow generic new and legacy code to be deployed as services on a heterogeneous execution framework. Users can submit analysis code typically written in Matlab, Python, C/C++ and R as non-interactive standalone command-line applications and wrap them as services in a form suitable for deployment on the platform. The CARMEN Service Builder tool enables neuroscientists to quickly wrap their analysis software for deployment to the CARMEN platform, as a service without knowledge of the service framework or the CARMEN system. A metadata schema describes each service in terms of both system and user requirements. The search functionality allows services to be quickly discovered from the many services available. Within the platform, services may be combined into more complicated analyses using the workflow tool. CARMEN and the service infrastructure are targeted towards the neuroscience community; however, it is a generic platform, and can be targeted towards any discipline.

Towards a Unified Architecture for Data-Intensive Seismology in VERCE

NASA Astrophysics Data System (ADS)

Klampanos, I.; Spinuso, A.; Trani, L.; Krause, A.; Garcia, C. R.; Atkinson, M.

2013-12-01

Modern seismology involves managing, storing and processing large datasets, typically geographically distributed across organisations. Performing computational experiments using these data generates more data, which in turn have to be managed, further analysed and frequently be made available within or outside the scientific community. As part of the EU-funded project VERCE (http://verce.eu), we research and develop a number of use-cases, interfacing technologies to satisfy the data-intensive requirements of modern seismology. Our solution seeks to support: (1) familiar programming environments to develop and execute experiments, in particular via Python/ObsPy, (2) a unified view of heterogeneous computing resources, public or private, through the adoption of workflows, (3) monitoring the experiments and validating the data products at varying granularities, via a comprehensive provenance system, (4) reproducibility of experiments and consistency in collaboration, via a shared registry of processing units and contextual metadata (computing resources, data, etc.) Here, we provide a brief account of these components and their roles in the proposed architecture. Our design integrates heterogeneous distributed systems, while allowing researchers to retain current practices and control data handling and execution via higher-level abstractions. At the core of our solution lies the workflow language Dispel. While Dispel can be used to express workflows at fine detail, it may also be used as part of meta- or job-submission workflows. User interaction can be provided through a visual editor or through custom applications on top of parameterisable workflows, which is the approach VERCE follows. According to our design, the scientist may use versions of Dispel/workflow processing elements offered by the VERCE library or override them introducing custom scientific code, using ObsPy. This approach has the advantage that, while the scientist uses a familiar tool, the resulting workflow can be executed on a number of underlying stream-processing engines, such as STORM or OGSA-DAI, transparently. While making efficient use of arbitrarily distributed resources and large data-sets is of priority, such processing requires adequate provenance tracking and monitoring. Hiding computation and orchestration details via a workflow system, allows us to embed provenance harvesting where appropriate without impeding the user's regular working patterns. Our provenance model is based on the W3C PROV standard and can provide information of varying granularity regarding execution, systems and data consumption/production. A video demonstrating a prototype provenance exploration tool can be found at http://bit.ly/15t0Fz0. Keeping experimental methodology and results open and accessible, as well as encouraging reproducibility and collaboration, is of central importance to modern science. As our users are expected to be based at different geographical locations, to have access to different computing resources and to employ customised scientific codes, the use of a shared registry of workflow components, implementations, data and computing resources is critical.

Approximations of Practice in the Preparation of Prospective Elementary Science Teachers

ERIC Educational Resources Information Center

Nelson, Michele M.

2011-01-01

Elementary teacher education involves learning to teach science. Even in elementary school, teaching science is demanding work--teachers must orchestrate a complex set of teaching practices to support students' science learning. This dissertation examines the application of Grossman and colleagues' (2009) cross-professional learning framework,…

Nexus: A modular workflow management system for quantum simulation codes

NASA Astrophysics Data System (ADS)

Krogel, Jaron T.

2016-01-01

The management of simulation workflows represents a significant task for the individual computational researcher. Automation of the required tasks involved in simulation work can decrease the overall time to solution and reduce sources of human error. A new simulation workflow management system, Nexus, is presented to address these issues. Nexus is capable of automated job management on workstations and resources at several major supercomputing centers. Its modular design allows many quantum simulation codes to be supported within the same framework. Current support includes quantum Monte Carlo calculations with QMCPACK, density functional theory calculations with Quantum Espresso or VASP, and quantum chemical calculations with GAMESS. Users can compose workflows through a transparent, text-based interface, resembling the input file of a typical simulation code. A usage example is provided to illustrate the process.

Cyberinfrastructure for End-to-End Environmental Explorations

NASA Astrophysics Data System (ADS)

Merwade, V.; Kumar, S.; Song, C.; Zhao, L.; Govindaraju, R.; Niyogi, D.

2007-12-01

The design and implementation of a cyberinfrastructure for End-to-End Environmental Exploration (C4E4) is presented. The C4E4 framework addresses the need for an integrated data/computation platform for studying broad environmental impacts by combining heterogeneous data resources with state-of-the-art modeling and visualization tools. With Purdue being a TeraGrid Resource Provider, C4E4 builds on top of the Purdue TeraGrid data management system and Grid resources, and integrates them through a service-oriented workflow system. It allows researchers to construct environmental workflows for data discovery, access, transformation, modeling, and visualization. Using the C4E4 framework, we have implemented an end-to-end SWAT simulation and analysis workflow that connects our TeraGrid data and computation resources. It enables researchers to conduct comprehensive studies on the impact of land management practices in the St. Joseph watershed using data from various sources in hydrologic, atmospheric, agricultural, and other related disciplines.

Performance Analysis Tool for HPC and Big Data Applications on Scientific Clusters

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

Yoo, Wucherl; Koo, Michelle; Cao, Yu

Big data is prevalent in HPC computing. Many HPC projects rely on complex workflows to analyze terabytes or petabytes of data. These workflows often require running over thousands of CPU cores and performing simultaneous data accesses, data movements, and computation. It is challenging to analyze the performance involving terabytes or petabytes of workflow data or measurement data of the executions, from complex workflows over a large number of nodes and multiple parallel task executions. To help identify performance bottlenecks or debug the performance issues in large-scale scientific applications and scientific clusters, we have developed a performance analysis framework, using state-ofthe-more » art open-source big data processing tools. Our tool can ingest system logs and application performance measurements to extract key performance features, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of the big data analysis framework, we conduct case studies on the workflows from an astronomy project known as the Palomar Transient Factory (PTF) and the job logs from the genome analysis scientific cluster. Our study processed many terabytes of system logs and application performance measurements collected on the HPC systems at NERSC. The implementation of our tool is generic enough to be used for analyzing the performance of other HPC systems and Big Data workows.« less

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

geoKepler Workflow Module for Computationally Scalable and Reproducible Geoprocessing and Modeling

NASA Astrophysics Data System (ADS)

Cowart, C.; Block, J.; Crawl, D.; Graham, J.; Gupta, A.; Nguyen, M.; de Callafon, R.; Smarr, L.; Altintas, I.

2015-12-01

The NSF-funded WIFIRE project has developed an open-source, online geospatial workflow platform for unifying geoprocessing tools and models for for fire and other geospatially dependent modeling applications. It is a product of WIFIRE's objective to build an end-to-end cyberinfrastructure for real-time and data-driven simulation, prediction and visualization of wildfire behavior. geoKepler includes a set of reusable GIS components, or actors, for the Kepler Scientific Workflow System (https://kepler-project.org). Actors exist for reading and writing GIS data in formats such as Shapefile, GeoJSON, KML, and using OGC web services such as WFS. The actors also allow for calling geoprocessing tools in other packages such as GDAL and GRASS. Kepler integrates functions from multiple platforms and file formats into one framework, thus enabling optimal GIS interoperability, model coupling, and scalability. Products of the GIS actors can be fed directly to models such as FARSITE and WRF. Kepler's ability to schedule and scale processes using Hadoop and Spark also makes geoprocessing ultimately extensible and computationally scalable. The reusable workflows in geoKepler can be made to run automatically when alerted by real-time environmental conditions. Here, we show breakthroughs in the speed of creating complex data for hazard assessments with this platform. We also demonstrate geoKepler workflows that use Data Assimilation to ingest real-time weather data into wildfire simulations, and for data mining techniques to gain insight into environmental conditions affecting fire behavior. Existing machine learning tools and libraries such as R and MLlib are being leveraged for this purpose in Kepler, as well as Kepler's Distributed Data Parallel (DDP) capability to provide a framework for scalable processing. geoKepler workflows can be executed via an iPython notebook as a part of a Jupyter hub at UC San Diego for sharing and reporting of the scientific analysis and results from various runs of geoKepler workflows. The communication between iPython and Kepler workflow executions is established through an iPython magic function for Kepler that we have implemented. In summary, geoKepler is an ecosystem that makes geospatial processing and analysis of any kind programmable, reusable, scalable and sharable.

MROrchestrator: A Fine-Grained Resource Orchestration Framework for MapReduce Clusters

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

Sharma, Bikash; Prabhakar, Ramya; Kandemir, Mahmut

2012-01-01

Efficient resource management in data centers and clouds running large distributed data processing frameworks like MapReduce is crucial for enhancing the performance of hosted applications and boosting resource utilization. However, existing resource scheduling schemes in Hadoop MapReduce allocate resources at the granularity of fixed-size, static portions of nodes, called slots. In this work, we show that MapReduce jobs have widely varying demands for multiple resources, making the static and fixed-size slot-level resource allocation a poor choice both from the performance and resource utilization standpoints. Furthermore, lack of co-ordination in the management of mul- tiple resources across nodes prevents dynamic slotmore » reconfigura- tion, and leads to resource contention. Motivated by this, we propose MROrchestrator, a MapReduce resource Orchestrator framework, which can dynamically identify resource bottlenecks, and resolve them through fine-grained, co-ordinated, and on- demand resource allocations. We have implemented MROrches- trator on two 24-node native and virtualized Hadoop clusters. Experimental results with a suite of representative MapReduce benchmarks demonstrate up to 38% reduction in job completion times, and up to 25% increase in resource utilization. We further show how popular resource managers like NGM and Mesos when augmented with MROrchestrator can hike up their performance.« less

Implementation of workflow engine technology to deliver basic clinical decision support functionality.

PubMed

Huser, Vojtech; Rasmussen, Luke V; Oberg, Ryan; Starren, Justin B

2011-04-10

Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform.

Nexus: a modular workflow management system for quantum simulation codes

DOE PAGES

Krogel, Jaron T.

2015-08-24

The management of simulation workflows is a significant task for the individual computational researcher. Automation of the required tasks involved in simulation work can decrease the overall time to solution and reduce sources of human error. A new simulation workflow management system, Nexus, is presented to address these issues. Nexus is capable of automated job management on workstations and resources at several major supercomputing centers. Its modular design allows many quantum simulation codes to be supported within the same framework. Current support includes quantum Monte Carlo calculations with QMCPACK, density functional theory calculations with Quantum Espresso or VASP, and quantummore » chemical calculations with GAMESS. Users can compose workflows through a transparent, text-based interface, resembling the input file of a typical simulation code. A usage example is provided to illustrate the process.« less

The VERCE platform: Enabling Computational Seismology via Streaming Workflows and Science Gateways

NASA Astrophysics Data System (ADS)

Spinuso, Alessandro; Filgueira, Rosa; Krause, Amrey; Matser, Jonas; Casarotti, Emanuele; Magnoni, Federica; Gemund, Andre; Frobert, Laurent; Krischer, Lion; Atkinson, Malcolm

2015-04-01

The VERCE project is creating an e-Science platform to facilitate innovative data analysis and coding methods that fully exploit the wealth of data in global seismology. One of the technologies developed within the project is the Dispel4Py python library, which allows to describe abstract stream-based workflows for data-intensive applications and to execute them in a distributed environment. At runtime Dispel4Py is able to map workflow descriptions dynamically onto a number of computational resources (Apache Storm clusters, MPI powered clusters, and shared-memory multi-core machines, single-core machines), setting it apart from other workflow frameworks. Therefore, Dispel4Py enables scientists to focus on their computation instead of being distracted by details of the computing infrastructure they use. Among the workflows developed with Dispel4Py in VERCE, we mention here those for Seismic Ambient Noise Cross-Correlation and MISFIT calculation, which address two data-intensive problems that are common in computational seismology. The former, also called Passive Imaging, allows the detection of relative seismic-wave velocity variations during the time of recording, to be associated with the stress-field changes that occurred in the test area. The MISFIT instead, takes as input the synthetic seismograms generated from HPC simulations for a certain Earth model and earthquake and, after a preprocessing stage, compares them with real observations in order to foster subsequent model updates and improvement (Inversion). The VERCE Science Gateway exposes the MISFIT calculation workflow as a service, in combination with the simulation phase. Both phases can be configured, controlled and monitored by the user via a rich user interface which is integrated within the gUSE Science Gateway framework, hiding the complexity of accessing third parties data services, security mechanisms and enactment on the target resources. Thanks to a modular extension to the Dispel4Py framework, the system collects provenance data adopting the W3C-PROV data model. Provenance recordings can be explored and analysed at run time for rapid diagnostic and workflow steering, or later for further validation and comparisons across runs. We will illustrate the interactive services of the gateway and the capabilities of the produced metadata, coupled with the VERCE data management layer based on iRODS. The Cross-Correlation workflow was evaluated on SuperMUC, a supercomputing cluster at the Leibniz Supercomputing Centre in Munich, with 155,656 processor cores in 9400 compute nodes. SuperMUC is based on the Intel Xeon architecture consisting of 18 Thin Node Islands and one Fat Node Island. This work has only had access to the Thin Node Islands, which contain Sandy Bridge nodes, each having 16 cores and 32 GB of memory. In the evaluations we used 1000 stations, and we applied two types of methods (whiten and non-whiten) for pre-processing the data. The workflow was tested on a varying number of cores (16, 32, 64, 128, and 256 cores) using the MPI mapping of Dispel4Py. The results show that Dispel4Py is able to improve the performance by increasing the number of cores without changing the description of the workflow.

ballaxy: web services for structural bioinformatics.

PubMed

Hildebrandt, Anna Katharina; Stöckel, Daniel; Fischer, Nina M; de la Garza, Luis; Krüger, Jens; Nickels, Stefan; Röttig, Marc; Schärfe, Charlotta; Schumann, Marcel; Thiel, Philipp; Lenhof, Hans-Peter; Kohlbacher, Oliver; Hildebrandt, Andreas

2015-01-01

Web-based workflow systems have gained considerable momentum in sequence-oriented bioinformatics. In structural bioinformatics, however, such systems are still relatively rare; while commercial stand-alone workflow applications are common in the pharmaceutical industry, academic researchers often still rely on command-line scripting to glue individual tools together. In this work, we address the problem of building a web-based system for workflows in structural bioinformatics. For the underlying molecular modelling engine, we opted for the BALL framework because of its extensive and well-tested functionality in the field of structural bioinformatics. The large number of molecular data structures and algorithms implemented in BALL allows for elegant and sophisticated development of new approaches in the field. We hence connected the versatile BALL library and its visualization and editing front end BALLView with the Galaxy workflow framework. The result, which we call ballaxy, enables the user to simply and intuitively create sophisticated pipelines for applications in structure-based computational biology, integrated into a standard tool for molecular modelling.  ballaxy consists of three parts: some minor modifications to the Galaxy system, a collection of tools and an integration into the BALL framework and the BALLView application for molecular modelling. Modifications to Galaxy will be submitted to the Galaxy project, and the BALL and BALLView integrations will be integrated in the next major BALL release. After acceptance of the modifications into the Galaxy project, we will publish all ballaxy tools via the Galaxy toolshed. In the meantime, all three components are available from http://www.ball-project.org/ballaxy. Also, docker images for ballaxy are available at https://registry.hub.docker.com/u/anhi/ballaxy/dockerfile/. ballaxy is licensed under the terms of the GPL. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Evaluation of MRI acquisition workflow with lean six sigma method: case study of liver and knee examinations.

PubMed

Roth, Christopher J; Boll, Daniel T; Wall, Lisa K; Merkle, Elmar M

2010-08-01

The purpose of this investigation was to assess workflow for medical imaging studies, specifically comparing liver and knee MRI examinations by use of the Lean Six Sigma methodologic framework. The hypothesis tested was that the Lean Six Sigma framework can be used to quantify MRI workflow and to identify sources of inefficiency to target for sequence and protocol improvement. Audio-video interleave streams representing individual acquisitions were obtained with graphic user interface screen capture software in the examinations of 10 outpatients undergoing MRI of the liver and 10 outpatients undergoing MRI of the knee. With Lean Six Sigma methods, the audio-video streams were dissected into value-added time (true image data acquisition periods), business value-added time (time spent that provides no direct patient benefit but is requisite in the current system), and non-value-added time (scanner inactivity while awaiting manual input). For overall MRI table time, value-added time was 43.5% (range, 39.7-48.3%) of the time for liver examinations and 89.9% (range, 87.4-93.6%) for knee examinations. Business value-added time was 16.3% of the table time for the liver and 4.3% of the table time for the knee examinations. Non-value-added time was 40.2% of the overall table time for the liver and 5.8% for the knee examinations. Liver MRI examinations consume statistically significantly more non-value-added and business value-added times than do knee examinations, primarily because of respiratory command management and contrast administration. Workflow analyses and accepted inefficiency reduction frameworks can be applied with use of a graphic user interface screen capture program.

[Integration of the radiotherapy irradiation planning in the digital workflow].

PubMed

Röhner, F; Schmucker, M; Henne, K; Momm, F; Bruggmoser, G; Grosu, A-L; Frommhold, H; Heinemann, F E

2013-02-01

At the Clinic of Radiotherapy at the University Hospital Freiburg, all relevant workflow is paperless. After implementing the Operating Schedule System (OSS) as a framework, all processes are being implemented into the departmental system MOSAIQ. Designing a digital workflow for radiotherapy irradiation planning is a large challenge, it requires interdisciplinary expertise and therefore the interfaces between the professions also have to be interdisciplinary. For every single step of radiotherapy irradiation planning, distinct responsibilities have to be defined and documented. All aspects of digital storage, backup and long-term availability of data were considered and have already been realized during the OSS project. After an analysis of the complete workflow and the statutory requirements, a detailed project plan was designed. In an interdisciplinary workgroup, problems were discussed and a detailed flowchart was developed. The new functionalities were implemented in a testing environment by the Clinical and Administrative IT Department (CAI). After extensive tests they were integrated into the new modular department system. The Clinic of Radiotherapy succeeded in realizing a completely digital workflow for radiotherapy irradiation planning. During the testing phase, our digital workflow was examined and afterwards was approved by the responsible authority.

Integrating Remote and Social Sensing Data for a Scenario on Secure Societies in Big Data Platform

NASA Astrophysics Data System (ADS)

Albani, Sergio; Lazzarini, Michele; Koubarakis, Manolis; Taniskidou, Efi Karra; Papadakis, George; Karkaletsis, Vangelis; Giannakopoulos, George

2016-08-01

In the framework of the Horizon 2020 project BigDataEurope (Integrating Big Data, Software & Communities for Addressing Europe's Societal Challenges), a pilot for the Secure Societies Societal Challenge was designed considering the requirements coming from relevant stakeholders. The pilot is focusing on the integration in a Big Data platform of data coming from remote and social sensing.The information on land changes coming from the Copernicus Sentinel 1A sensor (Change Detection workflow) is integrated with information coming from selected Twitter and news agencies accounts (Event Detection workflow) in order to provide the user with multiple sources of information.The Change Detection workflow implements a processing chain in a distributed parallel manner, exploiting the Big Data capabilities in place; the Event Detection workflow implements parallel and distributed social media and news agencies monitoring as well as suitable mechanisms to detect and geo-annotate the related events.

Outside the Framework of Thinkable Thought: The Modern Orchestration Project

ERIC Educational Resources Information Center

Gattegno, Eliot Aron

2010-01-01

In today's world of too much information, context--not content--is king. This proposal is for the development of an unparalleled sonic analysis tool that converts audio files into musical score notation and a Web site (API) to collect manage and preserve information about the musical sounds analyzed, as well as music scores, videos, and articles…

Deploying and sharing U-Compare workflows as web services.

PubMed

Kontonatsios, Georgios; Korkontzelos, Ioannis; Kolluru, Balakrishna; Thompson, Paul; Ananiadou, Sophia

2013-02-18

U-Compare is a text mining platform that allows the construction, evaluation and comparison of text mining workflows. U-Compare contains a large library of components that are tuned to the biomedical domain. Users can rapidly develop biomedical text mining workflows by mixing and matching U-Compare's components. Workflows developed using U-Compare can be exported and sent to other users who, in turn, can import and re-use them. However, the resulting workflows are standalone applications, i.e., software tools that run and are accessible only via a local machine, and that can only be run with the U-Compare platform. We address the above issues by extending U-Compare to convert standalone workflows into web services automatically, via a two-click process. The resulting web services can be registered on a central server and made publicly available. Alternatively, users can make web services available on their own servers, after installing the web application framework, which is part of the extension to U-Compare. We have performed a user-oriented evaluation of the proposed extension, by asking users who have tested the enhanced functionality of U-Compare to complete questionnaires that assess its functionality, reliability, usability, efficiency and maintainability. The results obtained reveal that the new functionality is well received by users. The web services produced by U-Compare are built on top of open standards, i.e., REST and SOAP protocols, and therefore, they are decoupled from the underlying platform. Exported workflows can be integrated with any application that supports these open standards. We demonstrate how the newly extended U-Compare enhances the cross-platform interoperability of workflows, by seamlessly importing a number of text mining workflow web services exported from U-Compare into Taverna, i.e., a generic scientific workflow construction platform.

Deploying and sharing U-Compare workflows as web services

PubMed Central

2013-01-01

Background U-Compare is a text mining platform that allows the construction, evaluation and comparison of text mining workflows. U-Compare contains a large library of components that are tuned to the biomedical domain. Users can rapidly develop biomedical text mining workflows by mixing and matching U-Compare’s components. Workflows developed using U-Compare can be exported and sent to other users who, in turn, can import and re-use them. However, the resulting workflows are standalone applications, i.e., software tools that run and are accessible only via a local machine, and that can only be run with the U-Compare platform. Results We address the above issues by extending U-Compare to convert standalone workflows into web services automatically, via a two-click process. The resulting web services can be registered on a central server and made publicly available. Alternatively, users can make web services available on their own servers, after installing the web application framework, which is part of the extension to U-Compare. We have performed a user-oriented evaluation of the proposed extension, by asking users who have tested the enhanced functionality of U-Compare to complete questionnaires that assess its functionality, reliability, usability, efficiency and maintainability. The results obtained reveal that the new functionality is well received by users. Conclusions The web services produced by U-Compare are built on top of open standards, i.e., REST and SOAP protocols, and therefore, they are decoupled from the underlying platform. Exported workflows can be integrated with any application that supports these open standards. We demonstrate how the newly extended U-Compare enhances the cross-platform interoperability of workflows, by seamlessly importing a number of text mining workflow web services exported from U-Compare into Taverna, i.e., a generic scientific workflow construction platform. PMID:23419017

Health information exchange technology on the front lines of healthcare: workflow factors and patterns of use

PubMed Central

Johnson, Kevin B; Lorenzi, Nancy M

2011-01-01

Objective The goal of this study was to develop an in-depth understanding of how a health information exchange (HIE) fits into clinical workflow at multiple clinical sites. Materials and Methods The ethnographic qualitative study was conducted over a 9-month period in six emergency departments (ED) and eight ambulatory clinics in Memphis, Tennessee, USA. Data were collected using direct observation, informal interviews during observation, and formal semi-structured interviews. The authors observed for over 180 h, during which providers used the exchange 130 times. Results HIE-related workflow was modeled for each ED site and ambulatory clinic group and substantial site-to-site workflow differences were identified. Common patterns in HIE-related workflow were also identified across all sites, leading to the development of two role-based workflow models: nurse based and physician based. The workflow elements framework was applied to the two role-based patterns. An in-depth description was developed of how providers integrated HIE into existing clinical workflow, including prompts for HIE use. Discussion Workflow differed substantially among sites, but two general role-based HIE usage models were identified. Although providers used HIE to improve continuity of patient care, patient–provider trust played a significant role. Types of information retrieved related to roles, with nurses seeking to retrieve recent hospitalization data and more open-ended usage by nurse practitioners and physicians. User and role-specific customization to accommodate differences in workflow and information needs may increase the adoption and use of HIE. Conclusion Understanding end users' perspectives towards HIE technology is crucial to the long-term success of HIE. By applying qualitative methods, an in-depth understanding of HIE usage was developed. PMID:22003156

VisRseq: R-based visual framework for analysis of sequencing data

PubMed Central

2015-01-01

Background Several tools have been developed to enable biologists to perform initial browsing and exploration of sequencing data. However the computational tool set for further analyses often requires significant computational expertise to use and many of the biologists with the knowledge needed to interpret these data must rely on programming experts. Results We present VisRseq, a framework for analysis of sequencing datasets that provides a computationally rich and accessible framework for integrative and interactive analyses without requiring programming expertise. We achieve this aim by providing R apps, which offer a semi-auto generated and unified graphical user interface for computational packages in R and repositories such as Bioconductor. To address the interactivity limitation inherent in R libraries, our framework includes several native apps that provide exploration and brushing operations as well as an integrated genome browser. The apps can be chained together to create more powerful analysis workflows. Conclusions To validate the usability of VisRseq for analysis of sequencing data, we present two case studies performed by our collaborators and report their workflow and insights. PMID:26328469

VisRseq: R-based visual framework for analysis of sequencing data.

PubMed

Younesy, Hamid; Möller, Torsten; Lorincz, Matthew C; Karimi, Mohammad M; Jones, Steven J M

2015-01-01

Several tools have been developed to enable biologists to perform initial browsing and exploration of sequencing data. However the computational tool set for further analyses often requires significant computational expertise to use and many of the biologists with the knowledge needed to interpret these data must rely on programming experts. We present VisRseq, a framework for analysis of sequencing datasets that provides a computationally rich and accessible framework for integrative and interactive analyses without requiring programming expertise. We achieve this aim by providing R apps, which offer a semi-auto generated and unified graphical user interface for computational packages in R and repositories such as Bioconductor. To address the interactivity limitation inherent in R libraries, our framework includes several native apps that provide exploration and brushing operations as well as an integrated genome browser. The apps can be chained together to create more powerful analysis workflows. To validate the usability of VisRseq for analysis of sequencing data, we present two case studies performed by our collaborators and report their workflow and insights.

TRIO: Burst Buffer Based I/O Orchestration

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

Wang, Teng; Oral, H Sarp; Pritchard, Michael

The growing computing power on leadership HPC systems is often accompanied by ever-escalating failure rates. Checkpointing is a common defensive mechanism used by scientific applications for failure recovery. However, directly writing the large and bursty checkpointing dataset to parallel filesystem can incur significant I/O contention on storage servers. Such contention in turn degrades the raw bandwidth utilization of storage servers and prolongs the average job I/O time of concurrent applications. Recently burst buffer has been proposed as an intermediate layer to absorb the bursty I/O traffic from compute nodes to storage backend. But an I/O orchestration mechanism is still desiredmore » to efficiently move checkpointing data from bursty buffers to storage backend. In this paper, we propose a burst buffer based I/O orchestration framework, named TRIO, to intercept and reshape the bursty writes for better sequential write traffic to storage severs. Meanwhile, TRIO coordinates the flushing orders among concurrent burst buffers to alleviate the contention on storage server bandwidth. Our experimental results reveal that TRIO can deliver 30.5% higher bandwidth and reduce the average job I/O time by 37% on average for data-intensive applications in various checkpointing scenarios.« less

Implementation of workflow engine technology to deliver basic clinical decision support functionality

PubMed Central

2011-01-01

Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform. PMID:21477364

A lightweight, flow-based toolkit for parallel and distributed bioinformatics pipelines

PubMed Central

2011-01-01

Background Bioinformatic analyses typically proceed as chains of data-processing tasks. A pipeline, or 'workflow', is a well-defined protocol, with a specific structure defined by the topology of data-flow interdependencies, and a particular functionality arising from the data transformations applied at each step. In computer science, the dataflow programming (DFP) paradigm defines software systems constructed in this manner, as networks of message-passing components. Thus, bioinformatic workflows can be naturally mapped onto DFP concepts. Results To enable the flexible creation and execution of bioinformatics dataflows, we have written a modular framework for parallel pipelines in Python ('PaPy'). A PaPy workflow is created from re-usable components connected by data-pipes into a directed acyclic graph, which together define nested higher-order map functions. The successive functional transformations of input data are evaluated on flexibly pooled compute resources, either local or remote. Input items are processed in batches of adjustable size, all flowing one to tune the trade-off between parallelism and lazy-evaluation (memory consumption). An add-on module ('NuBio') facilitates the creation of bioinformatics workflows by providing domain specific data-containers (e.g., for biomolecular sequences, alignments, structures) and functionality (e.g., to parse/write standard file formats). Conclusions PaPy offers a modular framework for the creation and deployment of parallel and distributed data-processing workflows. Pipelines derive their functionality from user-written, data-coupled components, so PaPy also can be viewed as a lightweight toolkit for extensible, flow-based bioinformatics data-processing. The simplicity and flexibility of distributed PaPy pipelines may help users bridge the gap between traditional desktop/workstation and grid computing. PaPy is freely distributed as open-source Python code at http://muralab.org/PaPy, and includes extensive documentation and annotated usage examples. PMID:21352538

A lightweight, flow-based toolkit for parallel and distributed bioinformatics pipelines.

PubMed

Cieślik, Marcin; Mura, Cameron

2011-02-25

Bioinformatic analyses typically proceed as chains of data-processing tasks. A pipeline, or 'workflow', is a well-defined protocol, with a specific structure defined by the topology of data-flow interdependencies, and a particular functionality arising from the data transformations applied at each step. In computer science, the dataflow programming (DFP) paradigm defines software systems constructed in this manner, as networks of message-passing components. Thus, bioinformatic workflows can be naturally mapped onto DFP concepts. To enable the flexible creation and execution of bioinformatics dataflows, we have written a modular framework for parallel pipelines in Python ('PaPy'). A PaPy workflow is created from re-usable components connected by data-pipes into a directed acyclic graph, which together define nested higher-order map functions. The successive functional transformations of input data are evaluated on flexibly pooled compute resources, either local or remote. Input items are processed in batches of adjustable size, all flowing one to tune the trade-off between parallelism and lazy-evaluation (memory consumption). An add-on module ('NuBio') facilitates the creation of bioinformatics workflows by providing domain specific data-containers (e.g., for biomolecular sequences, alignments, structures) and functionality (e.g., to parse/write standard file formats). PaPy offers a modular framework for the creation and deployment of parallel and distributed data-processing workflows. Pipelines derive their functionality from user-written, data-coupled components, so PaPy also can be viewed as a lightweight toolkit for extensible, flow-based bioinformatics data-processing. The simplicity and flexibility of distributed PaPy pipelines may help users bridge the gap between traditional desktop/workstation and grid computing. PaPy is freely distributed as open-source Python code at http://muralab.org/PaPy, and includes extensive documentation and annotated usage examples.

The QuakeSim Project: Web Services for Managing Geophysical Data and Applications

NASA Astrophysics Data System (ADS)

Pierce, Marlon E.; Fox, Geoffrey C.; Aktas, Mehmet S.; Aydin, Galip; Gadgil, Harshawardhan; Qi, Zhigang; Sayar, Ahmet

2008-04-01

We describe our distributed systems research efforts to build the “cyberinfrastructure” components that constitute a geophysical Grid, or more accurately, a Grid of Grids. Service-oriented computing principles are used to build a distributed infrastructure of Web accessible components for accessing data and scientific applications. Our data services fall into two major categories: Archival, database-backed services based around Geographical Information System (GIS) standards from the Open Geospatial Consortium, and streaming services that can be used to filter and route real-time data sources such as Global Positioning System data streams. Execution support services include application execution management services and services for transferring remote files. These data and execution service families are bound together through metadata information and workflow services for service orchestration. Users may access the system through the QuakeSim scientific Web portal, which is built using a portlet component approach.

Transforming a Fourth Year Modern Optics Course Using a Deliberate Practice Framework

ERIC Educational Resources Information Center

Jones, David J.; Madison, Kirk W.; Wieman, Carl E.

2015-01-01

We present a study of active learning pedagogies in an upper-division physics course. This work was guided by the principle of deliberate practice for the development of expertise, and this principle was used in the design of the materials and the orchestration of the classroom activities of the students. We present our process for efficiently…

Exploring Two Approaches for an End-to-End Scientific Analysis Workflow

NASA Astrophysics Data System (ADS)

Dodelson, Scott; Kent, Steve; Kowalkowski, Jim; Paterno, Marc; Sehrish, Saba

2015-12-01

The scientific discovery process can be advanced by the integration of independently-developed programs run on disparate computing facilities into coherent workflows usable by scientists who are not experts in computing. For such advancement, we need a system which scientists can use to formulate analysis workflows, to integrate new components to these workflows, and to execute different components on resources that are best suited to run those components. In addition, we need to monitor the status of the workflow as components get scheduled and executed, and to access the intermediate and final output for visual exploration and analysis. Finally, it is important for scientists to be able to share their workflows with collaborators. We have explored two approaches for such an analysis framework for the Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC); the first one is based on the use and extension of Galaxy, a web-based portal for biomedical research, and the second one is based on a programming language, Python. In this paper, we present a brief description of the two approaches, describe the kinds of extensions to the Galaxy system we have found necessary in order to support the wide variety of scientific analysis in the cosmology community, and discuss how similar efforts might be of benefit to the HEP community.

Experiences and lessons learned from creating a generalized workflow for data publication of field campaign datasets

NASA Astrophysics Data System (ADS)

Santhana Vannan, S. K.; Ramachandran, R.; Deb, D.; Beaty, T.; Wright, D.

2017-12-01

This paper summarizes the workflow challenges of curating and publishing data produced from disparate data sources and provides a generalized workflow solution to efficiently archive data generated by researchers. The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for biogeochemical dynamics and the Global Hydrology Resource Center (GHRC) DAAC have been collaborating on the development of a generalized workflow solution to efficiently manage the data publication process. The generalized workflow presented here are built on lessons learned from implementations of the workflow system. Data publication consists of the following steps: Accepting the data package from the data providers, ensuring the full integrity of the data files. Identifying and addressing data quality issues Assembling standardized, detailed metadata and documentation, including file level details, processing methodology, and characteristics of data files Setting up data access mechanisms Setup of the data in data tools and services for improved data dissemination and user experience Registering the dataset in online search and discovery catalogues Preserving the data location through Digital Object Identifiers (DOI) We will describe the steps taken to automate, and realize efficiencies to the above process. The goals of the workflow system are to reduce the time taken to publish a dataset, to increase the quality of documentation and metadata, and to track individual datasets through the data curation process. Utilities developed to achieve these goal will be described. We will also share metrics driven value of the workflow system and discuss the future steps towards creation of a common software framework.

speaq 2.0: A complete workflow for high-throughput 1D NMR spectra processing and quantification.

PubMed

Beirnaert, Charlie; Meysman, Pieter; Vu, Trung Nghia; Hermans, Nina; Apers, Sandra; Pieters, Luc; Covaci, Adrian; Laukens, Kris

2018-03-01

Nuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. Meanwhile its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping, thus avoiding the binning step. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using a simulated dataset and two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq).

speaq 2.0: A complete workflow for high-throughput 1D NMR spectra processing and quantification

PubMed Central

Pieters, Luc; Covaci, Adrian

2018-01-01

Nuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. Meanwhile its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping, thus avoiding the binning step. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using a simulated dataset and two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq). PMID:29494588

An ontological knowledge framework for adaptive medical workflow.

PubMed

Dang, Jiangbo; Hedayati, Amir; Hampel, Ken; Toklu, Candemir

2008-10-01

As emerging technologies, semantic Web and SOA (Service-Oriented Architecture) allow BPMS (Business Process Management System) to automate business processes that can be described as services, which in turn can be used to wrap existing enterprise applications. BPMS provides tools and methodologies to compose Web services that can be executed as business processes and monitored by BPM (Business Process Management) consoles. Ontologies are a formal declarative knowledge representation model. It provides a foundation upon which machine understandable knowledge can be obtained, and as a result, it makes machine intelligence possible. Healthcare systems can adopt these technologies to make them ubiquitous, adaptive, and intelligent, and then serve patients better. This paper presents an ontological knowledge framework that covers healthcare domains that a hospital encompasses-from the medical or administrative tasks, to hospital assets, medical insurances, patient records, drugs, and regulations. Therefore, our ontology makes our vision of personalized healthcare possible by capturing all necessary knowledge for a complex personalized healthcare scenario involving patient care, insurance policies, and drug prescriptions, and compliances. For example, our ontology facilitates a workflow management system to allow users, from physicians to administrative assistants, to manage, even create context-aware new medical workflows and execute them on-the-fly.

Research Infrastructure for Collaborative Team Science: Challenges in Technology-Supported Workflows in and Across Laboratories, Institutions, and Geographies.

PubMed

Mirel, Barbara; Luo, Airong; Harris, Marcelline

2015-05-01

Collaborative research has many challenges. One under-researched challenge is how to align collaborators' research practices and evolving analytical reasoning with technologies and configurations of technologies that best support them. The goal of such alignment is to enhance collaborative problem solving capabilities in research. Toward this end, we draw on our own research and a synthesis of the literature to characterize the workflow of collaborating scientists in systems-level renal disease research. We describe the various phases of a hypothetical workflow among diverse collaborators within and across laboratories, extending from their primary analysis through secondary analysis. For each phase, we highlight required technology supports, and. At time, complementary organizational supports. This survey of supports matching collaborators' analysis practices and needs in research projects to technological support is preliminary, aimed ultimately at developing a research capability framework that can help scientists and technologists mutually understand workflows and technologies that can help enable and enhance them. Copyright © 2015 Elsevier Inc. All rights reserved.

Workflows for microarray data processing in the Kepler environment.

PubMed

Stropp, Thomas; McPhillips, Timothy; Ludäscher, Bertram; Bieda, Mark

2012-05-17

Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or R/BioConductor scripting approaches to pipeline design. Finally, we suggest that microarray data processing task workflows may provide a basis for future example-based comparison of different workflow systems. We provide a set of tools and complete workflows for microarray data analysis in the Kepler environment, which has the advantages of offering graphical, clear display of conceptual steps and parameters and the ability to easily integrate other resources such as remote data and web services.

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

Oppel, III, Fred; Hart, Brian; Hart, Derek

Umbra is a software package that has been in development at Sandia National Laboratories since 1995, under the name Umbra since 1997. Umbra is a software framework written in C++ and Tcl/Tk that has been applied to many operations, primarily dealing with robotics and simulation. Umbra executables are C++ libraries orchestrated with Tcl/Tk scripts. Two major feature upgrades occurred from 4.7 to 4.8 1. System Umbra Module with its own Update Graph within the C++ framework. 2. New terrain graph for fast line-of-sight calculations All else were minor updates such as later versions of Visual Studio, OpenSceneGraph and Boost.

From the desktop to the grid: scalable bioinformatics via workflow conversion.

PubMed

de la Garza, Luis; Veit, Johannes; Szolek, Andras; Röttig, Marc; Aiche, Stephan; Gesing, Sandra; Reinert, Knut; Kohlbacher, Oliver

2016-03-12

Reproducibility is one of the tenets of the scientific method. Scientific experiments often comprise complex data flows, selection of adequate parameters, and analysis and visualization of intermediate and end results. Breaking down the complexity of such experiments into the joint collaboration of small, repeatable, well defined tasks, each with well defined inputs, parameters, and outputs, offers the immediate benefit of identifying bottlenecks, pinpoint sections which could benefit from parallelization, among others. Workflows rest upon the notion of splitting complex work into the joint effort of several manageable tasks. There are several engines that give users the ability to design and execute workflows. Each engine was created to address certain problems of a specific community, therefore each one has its advantages and shortcomings. Furthermore, not all features of all workflow engines are royalty-free -an aspect that could potentially drive away members of the scientific community. We have developed a set of tools that enables the scientific community to benefit from workflow interoperability. We developed a platform-free structured representation of parameters, inputs, outputs of command-line tools in so-called Common Tool Descriptor documents. We have also overcome the shortcomings and combined the features of two royalty-free workflow engines with a substantial user community: the Konstanz Information Miner, an engine which we see as a formidable workflow editor, and the Grid and User Support Environment, a web-based framework able to interact with several high-performance computing resources. We have thus created a free and highly accessible way to design workflows on a desktop computer and execute them on high-performance computing resources. Our work will not only reduce time spent on designing scientific workflows, but also make executing workflows on remote high-performance computing resources more accessible to technically inexperienced users. We strongly believe that our efforts not only decrease the turnaround time to obtain scientific results but also have a positive impact on reproducibility, thus elevating the quality of obtained scientific results.

Visualization and Analysis for Near-Real-Time Decision Making in Distributed Workflows

DOE PAGES

Pugmire, David; Kress, James; Choi, Jong; ...

2016-08-04

Data driven science is becoming increasingly more common, complex, and is placing tremendous stresses on visualization and analysis frameworks. Data sources producing 10GB per second (and more) are becoming increasingly commonplace in both simulation, sensor and experimental sciences. These data sources, which are often distributed around the world, must be analyzed by teams of scientists that are also distributed. Enabling scientists to view, query and interact with such large volumes of data in near-real-time requires a rich fusion of visualization and analysis techniques, middleware and workflow systems. Here, this paper discusses initial research into visualization and analysis of distributed datamore » workflows that enables scientists to make near-real-time decisions of large volumes of time varying data.« less

Documenting Models for Interoperability and Reusability (proceedings)

EPA Science Inventory

Many modeling frameworks compartmentalize science via individual models that link sets of small components to create larger modeling workflows. Developing integrated watershed models increasingly requires coupling multidisciplinary, independent models, as well as collaboration be...

Documenting Models for Interoperability and Reusability

EPA Science Inventory

Many modeling frameworks compartmentalize science via individual models that link sets of small components to create larger modeling workflows. Developing integrated watershed models increasingly requires coupling multidisciplinary, independent models, as well as collaboration be...

Risk management frameworks: supporting the next generation of Murray-Darling Basin water sharing plans

NASA Astrophysics Data System (ADS)

Podger, G. M.; Cuddy, S. M.; Peeters, L.; Smith, T.; Bark, R. H.; Black, D. C.; Wallbrink, P.

2014-09-01

Water jurisdictions in Australia are required to prepare and implement water resource plans. In developing these plans the common goal is realising the best possible use of the water resources - maximising outcomes while minimising negative impacts. This requires managing the risks associated with assessing and balancing cultural, industrial, agricultural, social and environmental demands for water within a competitive and resource-limited environment. Recognising this, conformance to international risk management principles (ISO 31000:2009) have been embedded within the Murray-Darling Basin Plan. Yet, to date, there has been little strategic investment by water jurisdictions in bridging the gap between principle and practice. The ISO 31000 principles and the risk management framework that embodies them align well with an adaptive management paradigm within which to conduct water resource planning. They also provide an integrative framework for the development of workflows that link risk analysis with risk evaluation and mitigation (adaptation) scenarios, providing a transparent, repeatable and robust platform. This study, through a demonstration use case and a series of workflows, demonstrates to policy makers how these principles can be used to support the development of the next generation of water sharing plans in 2019. The workflows consider the uncertainty associated with climate and flow inputs, and model parameters on irrigation and hydropower production, meeting environmental flow objectives and recreational use of the water resource. The results provide insights to the risks associated with meeting a range of different objectives.

Commentary on "Theory-Led Design of Instruments and Representations in Learning Analytics: Developing a Novel Tool for Orchestration of Online Collaborative Learning"

ERIC Educational Resources Information Center

Teplovs, Chris

2015-01-01

This commentary reflects on the contributions to learning analytics and theory by a paper that describes how multiple theoretical frameworks were woven together to inform the creation of a new, automated discourse analysis tool. The commentary highlights the contributions of the original paper, provides some alternative approaches, and touches on…

Medication Management: The Macrocognitive Workflow of Older Adults With Heart Failure

PubMed Central

2016-01-01

Background Older adults with chronic disease struggle to manage complex medication regimens. Health information technology has the potential to improve medication management, but only if it is based on a thorough understanding of the complexity of medication management workflow as it occurs in natural settings. Prior research reveals that patient work related to medication management is complex, cognitive, and collaborative. Macrocognitive processes are theorized as how people individually and collaboratively think in complex, adaptive, and messy nonlaboratory settings supported by artifacts. Objective The objective of this research was to describe and analyze the work of medication management by older adults with heart failure, using a macrocognitive workflow framework. Methods We interviewed and observed 61 older patients along with 30 informal caregivers about self-care practices including medication management. Descriptive qualitative content analysis methods were used to develop categories, subcategories, and themes about macrocognitive processes used in medication management workflow. Results We identified 5 high-level macrocognitive processes affecting medication management—sensemaking, planning, coordination, monitoring, and decision making—and 15 subprocesses. Data revealed workflow as occurring in a highly collaborative, fragile system of interacting people, artifacts, time, and space. Process breakdowns were common and patients had little support for macrocognitive workflow from current tools. Conclusions Macrocognitive processes affected medication management performance. Describing and analyzing this performance produced recommendations for technology supporting collaboration and sensemaking, decision making and problem detection, and planning and implementation. PMID:27733331

Exploring Two Approaches for an End-to-End Scientific Analysis Workflow

DOE PAGES

Dodelson, Scott; Kent, Steve; Kowalkowski, Jim; ...

2015-12-23

The advance of the scientific discovery process is accomplished by the integration of independently-developed programs run on disparate computing facilities into coherent workflows usable by scientists who are not experts in computing. For such advancement, we need a system which scientists can use to formulate analysis workflows, to integrate new components to these workflows, and to execute different components on resources that are best suited to run those components. In addition, we need to monitor the status of the workflow as components get scheduled and executed, and to access the intermediate and final output for visual exploration and analysis. Finally,more » it is important for scientists to be able to share their workflows with collaborators. Moreover we have explored two approaches for such an analysis framework for the Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC), the first one is based on the use and extension of Galaxy, a web-based portal for biomedical research, and the second one is based on a programming language, Python. In our paper, we present a brief description of the two approaches, describe the kinds of extensions to the Galaxy system we have found necessary in order to support the wide variety of scientific analysis in the cosmology community, and discuss how similar efforts might be of benefit to the HEP community.« less

Medication Management: The Macrocognitive Workflow of Older Adults With Heart Failure.

PubMed

Mickelson, Robin S; Unertl, Kim M; Holden, Richard J

2016-10-12

Older adults with chronic disease struggle to manage complex medication regimens. Health information technology has the potential to improve medication management, but only if it is based on a thorough understanding of the complexity of medication management workflow as it occurs in natural settings. Prior research reveals that patient work related to medication management is complex, cognitive, and collaborative. Macrocognitive processes are theorized as how people individually and collaboratively think in complex, adaptive, and messy nonlaboratory settings supported by artifacts. The objective of this research was to describe and analyze the work of medication management by older adults with heart failure, using a macrocognitive workflow framework. We interviewed and observed 61 older patients along with 30 informal caregivers about self-care practices including medication management. Descriptive qualitative content analysis methods were used to develop categories, subcategories, and themes about macrocognitive processes used in medication management workflow. We identified 5 high-level macrocognitive processes affecting medication management-sensemaking, planning, coordination, monitoring, and decision making-and 15 subprocesses. Data revealed workflow as occurring in a highly collaborative, fragile system of interacting people, artifacts, time, and space. Process breakdowns were common and patients had little support for macrocognitive workflow from current tools. Macrocognitive processes affected medication management performance. Describing and analyzing this performance produced recommendations for technology supporting collaboration and sensemaking, decision making and problem detection, and planning and implementation.

From Peer-Reviewed to Peer-Reproduced in Scholarly Publishing: The Complementary Roles of Data Models and Workflows in Bioinformatics

PubMed Central

Zhao, Jun; Avila-Garcia, Maria Susana; Roos, Marco; Thompson, Mark; van der Horst, Eelke; Kaliyaperumal, Rajaram; Luo, Ruibang; Lee, Tin-Lap; Lam, Tak-wah; Edmunds, Scott C.; Sansone, Susanna-Assunta

2015-01-01

Motivation Reproducing the results from a scientific paper can be challenging due to the absence of data and the computational tools required for their analysis. In addition, details relating to the procedures used to obtain the published results can be difficult to discern due to the use of natural language when reporting how experiments have been performed. The Investigation/Study/Assay (ISA), Nanopublications (NP), and Research Objects (RO) models are conceptual data modelling frameworks that can structure such information from scientific papers. Computational workflow platforms can also be used to reproduce analyses of data in a principled manner. We assessed the extent by which ISA, NP, and RO models, together with the Galaxy workflow system, can capture the experimental processes and reproduce the findings of a previously published paper reporting on the development of SOAPdenovo2, a de novo genome assembler. Results Executable workflows were developed using Galaxy, which reproduced results that were consistent with the published findings. A structured representation of the information in the SOAPdenovo2 paper was produced by combining the use of ISA, NP, and RO models. By structuring the information in the published paper using these data and scientific workflow modelling frameworks, it was possible to explicitly declare elements of experimental design, variables, and findings. The models served as guides in the curation of scientific information and this led to the identification of inconsistencies in the original published paper, thereby allowing its authors to publish corrections in the form of an errata. Availability SOAPdenovo2 scripts, data, and results are available through the GigaScience Database: http://dx.doi.org/10.5524/100044; the workflows are available from GigaGalaxy: http://galaxy.cbiit.cuhk.edu.hk; and the representations using the ISA, NP, and RO models are available through the SOAPdenovo2 case study website http://isa-tools.github.io/soapdenovo2/. Contact: philippe.rocca-serra@oerc.ox.ac.uk and susanna-assunta.sansone@oerc.ox.ac.uk. PMID:26154165

The Archive Solution for Distributed Workflow Management Agents of the CMS Experiment at LHC

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

Kuznetsov, Valentin; Fischer, Nils Leif; Guo, Yuyi

The CMS experiment at the CERN LHC developed the Workflow Management Archive system to persistently store unstructured framework job report documents produced by distributed workflow management agents. In this paper we present its architecture, implementation, deployment, and integration with the CMS and CERN computing infrastructures, such as central HDFS and Hadoop Spark cluster. The system leverages modern technologies such as a document oriented database and the Hadoop eco-system to provide the necessary flexibility to reliably process, store, and aggregatemore » $$\\mathcal{O}$$(1M) documents on a daily basis. We describe the data transformation, the short and long term storage layers, the query language, along with the aggregation pipeline developed to visualize various performance metrics to assist CMS data operators in assessing the performance of the CMS computing system.« less

The Archive Solution for Distributed Workflow Management Agents of the CMS Experiment at LHC

DOE PAGES

Kuznetsov, Valentin; Fischer, Nils Leif; Guo, Yuyi

2018-03-19

The CMS experiment at the CERN LHC developed the Workflow Management Archive system to persistently store unstructured framework job report documents produced by distributed workflow management agents. In this paper we present its architecture, implementation, deployment, and integration with the CMS and CERN computing infrastructures, such as central HDFS and Hadoop Spark cluster. The system leverages modern technologies such as a document oriented database and the Hadoop eco-system to provide the necessary flexibility to reliably process, store, and aggregatemore » $$\\mathcal{O}$$(1M) documents on a daily basis. We describe the data transformation, the short and long term storage layers, the query language, along with the aggregation pipeline developed to visualize various performance metrics to assist CMS data operators in assessing the performance of the CMS computing system.« less

Networks in ATLAS

NASA Astrophysics Data System (ADS)

McKee, Shawn; ATLAS Collaboration

2017-10-01

Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks. We will report on a number of networking initiatives in ATLAS including participation in the global perfSONAR network monitoring and measuring efforts of WLCG and OSG, the collaboration with the LHCOPN/LHCONE effort, the integration of network awareness into PanDA, the use of the evolving ATLAS analytics framework to better understand our networks and the changes in our DDM system to allow remote access to data. We will also discuss new efforts underway that are exploring the inclusion and use of software defined networks (SDN) and how ATLAS might benefit from: • Orchestration and optimization of distributed data access and data movement. • Better control of workflows, end to end. • Enabling prioritization of time-critical vs normal tasks • Improvements in the efficiency of resource usage

GeneFisher-P: variations of GeneFisher as processes in Bio-jETI

PubMed Central

Lamprecht, Anna-Lena; Margaria, Tiziana; Steffen, Bernhard; Sczyrba, Alexander; Hartmeier, Sven; Giegerich, Robert

2008-01-01

Background PCR primer design is an everyday, but not trivial task requiring state-of-the-art software. We describe the popular tool GeneFisher and explain its recent restructuring using workflow techniques. We apply a service-oriented approach to model and implement GeneFisher-P, a process-based version of the GeneFisher web application, as a part of the Bio-jETI platform for service modeling and execution. We show how to introduce a flexible process layer to meet the growing demand for improved user-friendliness and flexibility. Results Within Bio-jETI, we model the process using the jABC framework, a mature model-driven, service-oriented process definition platform. We encapsulate remote legacy tools and integrate web services using jETI, an extension of the jABC for seamless integration of remote resources as basic services, ready to be used in the process. Some of the basic services used by GeneFisher are in fact already provided as individual web services at BiBiServ and can be directly accessed. Others are legacy programs, and are made available to Bio-jETI via the jETI technology. The full power of service-based process orientation is required when more bioinformatics tools, available as web services or via jETI, lead to easy extensions or variations of the basic process. This concerns for instance variations of data retrieval or alignment tools as provided by the European Bioinformatics Institute (EBI). Conclusions The resulting service- and process-oriented GeneFisher-P demonstrates how basic services from heterogeneous sources can be easily orchestrated in the Bio-jETI platform and lead to a flexible family of specialized processes tailored to specific tasks. PMID:18460174

An Automated Design Framework for Multicellular Recombinase Logic.

PubMed

Guiziou, Sarah; Ulliana, Federico; Moreau, Violaine; Leclere, Michel; Bonnet, Jerome

2018-05-18

Tools to systematically reprogram cellular behavior are crucial to address pressing challenges in manufacturing, environment, or healthcare. Recombinases can very efficiently encode Boolean and history-dependent logic in many species, yet current designs are performed on a case-by-case basis, limiting their scalability and requiring time-consuming optimization. Here we present an automated workflow for designing recombinase logic devices executing Boolean functions. Our theoretical framework uses a reduced library of computational devices distributed into different cellular subpopulations, which are then composed in various manners to implement all desired logic functions at the multicellular level. Our design platform called CALIN (Composable Asynchronous Logic using Integrase Networks) is broadly accessible via a web server, taking truth tables as inputs and providing corresponding DNA designs and sequences as outputs (available at http://synbio.cbs.cnrs.fr/calin ). We anticipate that this automated design workflow will streamline the implementation of Boolean functions in many organisms and for various applications.

Supporting metabolomics with adaptable software: design architectures for the end-user.

PubMed

Sarpe, Vladimir; Schriemer, David C

2017-02-01

Large and disparate sets of LC-MS data are generated by modern metabolomics profiling initiatives, and while useful software tools are available to annotate and quantify compounds, the field requires continued software development in order to sustain methodological innovation. Advances in software development practices allow for a new paradigm in tool development for metabolomics, where increasingly the end-user can develop or redeploy utilities ranging from simple algorithms to complex workflows. Resources that provide an organized framework for development are described and illustrated with LC-MS processing packages that have leveraged their design tools. Full access to these resources depends in part on coding experience, but the emergence of workflow builders and pluggable frameworks strongly reduces the skill level required. Developers in the metabolomics community are encouraged to use these resources and design content for uptake and reuse. Copyright © 2016 Elsevier Ltd. All rights reserved.

IceProd 2: A Next Generation Data Analysis Framework for the IceCube Neutrino Observatory

NASA Astrophysics Data System (ADS)

Schultz, D.

2015-12-01

We describe the overall structure and new features of the second generation of IceProd, a data processing and management framework. IceProd was developed by the IceCube Neutrino Observatory for processing of Monte Carlo simulations, detector data, and analysis levels. It runs as a separate layer on top of grid and batch systems. This is accomplished by a set of daemons which process job workflow, maintaining configuration and status information on the job before, during, and after processing. IceProd can also manage complex workflow DAGs across distributed computing grids in order to optimize usage of resources. IceProd is designed to be very light-weight; it runs as a python application fully in user space and can be set up easily. For the initial completion of this second version of IceProd, improvements have been made to increase security, reliability, scalability, and ease of use.

PaaS for web applications with OpenShift Origin

NASA Astrophysics Data System (ADS)

Lossent, A.; Rodriguez Peon, A.; Wagner, A.

2017-10-01

The CERN Web Frameworks team has deployed OpenShift Origin to facilitate deployment of web applications and to improving efficiency in terms of computing resource usage. OpenShift leverages Docker containers and Kubernetes orchestration to provide a Platform-as-a-service solution oriented for web applications. We will review use cases and how OpenShift was integrated with other services such as source control, web site management and authentication services.

Disseminating Metaproteomic Informatics Capabilities and Knowledge Using the Galaxy-P Framework

PubMed Central

Easterly, Caleb; Gruening, Bjoern; Johnson, James; Kolmeder, Carolin A.; Kumar, Praveen; May, Damon; Mehta, Subina; Mesuere, Bart; Brown, Zachary; Elias, Joshua E.; Hervey, W. Judson; McGowan, Thomas; Muth, Thilo; Rudney, Joel; Griffin, Timothy J.

2018-01-01

The impact of microbial communities, also known as the microbiome, on human health and the environment is receiving increased attention. Studying translated gene products (proteins) and comparing metaproteomic profiles may elucidate how microbiomes respond to specific environmental stimuli, and interact with host organisms. Characterizing proteins expressed by a complex microbiome and interpreting their functional signature requires sophisticated informatics tools and workflows tailored to metaproteomics. Additionally, there is a need to disseminate these informatics resources to researchers undertaking metaproteomic studies, who could use them to make new and important discoveries in microbiome research. The Galaxy for proteomics platform (Galaxy-P) offers an open source, web-based bioinformatics platform for disseminating metaproteomics software and workflows. Within this platform, we have developed easily-accessible and documented metaproteomic software tools and workflows aimed at training researchers in their operation and disseminating the tools for more widespread use. The modular workflows encompass the core requirements of metaproteomic informatics: (a) database generation; (b) peptide spectral matching; (c) taxonomic analysis and (d) functional analysis. Much of the software available via the Galaxy-P platform was selected, packaged and deployed through an online metaproteomics “Contribution Fest“ undertaken by a unique consortium of expert software developers and users from the metaproteomics research community, who have co-authored this manuscript. These resources are documented on GitHub and freely available through the Galaxy Toolshed, as well as a publicly accessible metaproteomics gateway Galaxy instance. These documented workflows are well suited for the training of novice metaproteomics researchers, through online resources such as the Galaxy Training Network, as well as hands-on training workshops. Here, we describe the metaproteomics tools available within these Galaxy-based resources, as well as the process by which they were selected and implemented in our community-based work. We hope this description will increase access to and utilization of metaproteomics tools, as well as offer a framework for continued community-based development and dissemination of cutting edge metaproteomics software. PMID:29385081

Disseminating Metaproteomic Informatics Capabilities and Knowledge Using the Galaxy-P Framework.

PubMed

Blank, Clemens; Easterly, Caleb; Gruening, Bjoern; Johnson, James; Kolmeder, Carolin A; Kumar, Praveen; May, Damon; Mehta, Subina; Mesuere, Bart; Brown, Zachary; Elias, Joshua E; Hervey, W Judson; McGowan, Thomas; Muth, Thilo; Nunn, Brook; Rudney, Joel; Tanca, Alessandro; Griffin, Timothy J; Jagtap, Pratik D

2018-01-31

The impact of microbial communities, also known as the microbiome, on human health and the environment is receiving increased attention. Studying translated gene products (proteins) and comparing metaproteomic profiles may elucidate how microbiomes respond to specific environmental stimuli, and interact with host organisms. Characterizing proteins expressed by a complex microbiome and interpreting their functional signature requires sophisticated informatics tools and workflows tailored to metaproteomics. Additionally, there is a need to disseminate these informatics resources to researchers undertaking metaproteomic studies, who could use them to make new and important discoveries in microbiome research. The Galaxy for proteomics platform (Galaxy-P) offers an open source, web-based bioinformatics platform for disseminating metaproteomics software and workflows. Within this platform, we have developed easily-accessible and documented metaproteomic software tools and workflows aimed at training researchers in their operation and disseminating the tools for more widespread use. The modular workflows encompass the core requirements of metaproteomic informatics: (a) database generation; (b) peptide spectral matching; (c) taxonomic analysis and (d) functional analysis. Much of the software available via the Galaxy-P platform was selected, packaged and deployed through an online metaproteomics "Contribution Fest" undertaken by a unique consortium of expert software developers and users from the metaproteomics research community, who have co-authored this manuscript. These resources are documented on GitHub and freely available through the Galaxy Toolshed, as well as a publicly accessible metaproteomics gateway Galaxy instance. These documented workflows are well suited for the training of novice metaproteomics researchers, through online resources such as the Galaxy Training Network, as well as hands-on training workshops. Here, we describe the metaproteomics tools available within these Galaxy-based resources, as well as the process by which they were selected and implemented in our community-based work. We hope this description will increase access to and utilization of metaproteomics tools, as well as offer a framework for continued community-based development and dissemination of cutting edge metaproteomics software.

Solutions for Mining Distributed Scientific Data

NASA Astrophysics Data System (ADS)

Lynnes, C.; Pham, L.; Graves, S.; Ramachandran, R.; Maskey, M.; Keiser, K.

2007-12-01

Researchers at the University of Alabama in Huntsville (UAH) and the Goddard Earth Sciences Data and Information Services Center (GES DISC) are working on approaches and methodologies facilitating the analysis of large amounts of distributed scientific data. Despite the existence of full-featured analysis tools, such as the Algorithm Development and Mining (ADaM) toolkit from UAH, and data repositories, such as the GES DISC, that provide online access to large amounts of data, there remain obstacles to getting the analysis tools and the data together in a workable environment. Does one bring the data to the tools or deploy the tools close to the data? The large size of many current Earth science datasets incurs significant overhead in network transfer for analysis workflows, even with the advanced networking capabilities that are available between many educational and government facilities. The UAH and GES DISC team are developing a capability to define analysis workflows using distributed services and online data resources. We are developing two solutions for this problem that address different analysis scenarios. The first is a Data Center Deployment of the analysis services for large data selections, orchestrated by a remotely defined analysis workflow. The second is a Data Mining Center approach of providing a cohesive analysis solution for smaller subsets of data. The two approaches can be complementary and thus provide flexibility for researchers to exploit the best solution for their data requirements. The Data Center Deployment of the analysis services has been implemented by deploying ADaM web services at the GES DISC so they can access the data directly, without the need of network transfers. Using the Mining Workflow Composer, a user can define an analysis workflow that is then submitted through a Web Services interface to the GES DISC for execution by a processing engine. The workflow definition is composed, maintained and executed at a distributed location, but most of the actual services comprising the workflow are available local to the GES DISC data repository. Additional refinements will ultimately provide a package that is easily implemented and configured at additional data centers for analysis of additional science data sets. Enhancements to the ADaM toolkit allow the staging of distributed data wherever the services are deployed, to support a Data Mining Center that can provide additional computational resources, large storage of output, easier addition and updates to available services, and access to data from multiple repositories. The Data Mining Center case provides researchers more flexibility to quickly try different workflow configurations and refine the process, using smaller amounts of data that may likely be transferred from distributed online repositories. This environment is sufficient for some analyses, but can also be used as an initial sandbox to test and refine a solution before staging the execution at a Data Center Deployment. Detection of airborne dust both over water and land in MODIS imagery using mining services for both solutions will be presented. The dust detection is just one possible example of the mining and analysis capabilities the proposed mining services solutions will provide to the science community. More information about the available services and the current status of this project is available at http://www.itsc.uah.edu/mws/

Integration of CBIR in radiological routine in accordance with IHE

NASA Astrophysics Data System (ADS)

Welter, Petra; Deserno, Thomas M.; Fischer, Benedikt; Wein, Berthold B.; Ott, Bastian; Günther, Rolf W.

2009-02-01

Increasing use of digital imaging processing leads to an enormous amount of imaging data. The access to picture archiving and communication systems (PACS), however, is solely textually, leading to sparse retrieval results because of ambiguous or missing image descriptions. Content-based image retrieval (CBIR) systems can improve the clinical diagnostic outcome significantly. However, current CBIR systems are not able to integrate their results with clinical workflow and PACS. Existing communication standards like DICOM and HL7 leave many options for implementation and do not ensure full interoperability. We present a concept of the standardized integration of a CBIR system for the radiology workflow in accordance with the Integrating the Healthcare Enterprise (IHE) framework. This is based on the IHE integration profile 'Post-Processing Workflow' (PPW) defining responsibilities as well as standardized communication and utilizing the DICOM Structured Report (DICOM SR). Because nowadays most of PACS and RIS systems are not yet fully IHE compliant to PPW, we also suggest an intermediate approach with the concepts of the CAD-PACS Toolkit. The integration is independent of the particular PACS and RIS system. Therefore, it supports the widespread application of CBIR in radiological routine. As a result, the approach is exemplarily applied to the Image Retrieval in Medical Applications (IRMA) framework.

Automatic system testing of a decision support system for insulin dosing using Google Android.

PubMed

Spat, Stephan; Höll, Bernhard; Petritsch, Georg; Schaupp, Lukas; Beck, Peter; Pieber, Thomas R

2013-01-01

Hyperglycaemia in hospitalized patients is a common and costly health care problem. The GlucoTab system is a mobile workflow and decision support system, aiming to facilitate efficient and safe glycemic control of non-critically ill patients. Being a medical device, the GlucoTab requires extensive and reproducible testing. A framework for high-volume, reproducible and automated system testing of the GlucoTab system was set up applying several Open Source tools for test automation and system time handling. The REACTION insulin titration protocol was investigated in a paper-based clinical trial (PBCT). In order to validate the GlucoTab system, data from this trial was used for simulation and system tests. In total, 1190 decision support action points were identified and simulated. Four data points (0.3%) resulted in a GlucoTab system error caused by a defective implementation. In 144 data points (12.1%), calculation errors of physicians and nurses in the PBCT were detected. The test framework was able to verify manual calculation of insulin doses and detect relatively many user errors and workflow anomalies in the PBCT data. This shows the high potential of the electronic decision support application to improve safety of implementation of an insulin titration protocol and workflow management system in clinical wards.

Automated quality control in a file-based broadcasting workflow

NASA Astrophysics Data System (ADS)

Zhang, Lina

2014-04-01

Benefit from the development of information and internet technologies, television broadcasting is transforming from inefficient tape-based production and distribution to integrated file-based workflows. However, no matter how many changes have took place, successful broadcasting still depends on the ability to deliver a consistent high quality signal to the audiences. After the transition from tape to file, traditional methods of manual quality control (QC) become inadequate, subjective, and inefficient. Based on China Central Television's full file-based workflow in the new site, this paper introduces an automated quality control test system for accurate detection of hidden troubles in media contents. It discusses the system framework and workflow control when the automated QC is added. It puts forward a QC criterion and brings forth a QC software followed this criterion. It also does some experiments on QC speed by adopting parallel processing and distributed computing. The performance of the test system shows that the adoption of automated QC can make the production effective and efficient, and help the station to achieve a competitive advantage in the media market.

A real-time phenotyping framework using machine learning for plant stress severity rating in soybean.

PubMed

Naik, Hsiang Sing; Zhang, Jiaoping; Lofquist, Alec; Assefa, Teshale; Sarkar, Soumik; Ackerman, David; Singh, Arti; Singh, Asheesh K; Ganapathysubramanian, Baskar

2017-01-01

Phenotyping is a critical component of plant research. Accurate and precise trait collection, when integrated with genetic tools, can greatly accelerate the rate of genetic gain in crop improvement. However, efficient and automatic phenotyping of traits across large populations is a challenge; which is further exacerbated by the necessity of sampling multiple environments and growing replicated trials. A promising approach is to leverage current advances in imaging technology, data analytics and machine learning to enable automated and fast phenotyping and subsequent decision support. In this context, the workflow for phenotyping (image capture → data storage and curation → trait extraction → machine learning/classification → models/apps for decision support) has to be carefully designed and efficiently executed to minimize resource usage and maximize utility. We illustrate such an end-to-end phenotyping workflow for the case of plant stress severity phenotyping in soybean, with a specific focus on the rapid and automatic assessment of iron deficiency chlorosis (IDC) severity on thousands of field plots. We showcase this analytics framework by extracting IDC features from a set of ~4500 unique canopies representing a diverse germplasm base that have different levels of IDC, and subsequently training a variety of classification models to predict plant stress severity. The best classifier is then deployed as a smartphone app for rapid and real time severity rating in the field. We investigated 10 different classification approaches, with the best classifier being a hierarchical classifier with a mean per-class accuracy of ~96%. We construct a phenotypically meaningful 'population canopy graph', connecting the automatically extracted canopy trait features with plant stress severity rating. We incorporated this image capture → image processing → classification workflow into a smartphone app that enables automated real-time evaluation of IDC scores using digital images of the canopy. We expect this high-throughput framework to help increase the rate of genetic gain by providing a robust extendable framework for other abiotic and biotic stresses. We further envision this workflow embedded onto a high throughput phenotyping ground vehicle and unmanned aerial system that will allow real-time, automated stress trait detection and quantification for plant research, breeding and stress scouting applications.

Using Workflows to Explore and Optimise Named Entity Recognition for Chemistry

PubMed Central

Kolluru, BalaKrishna; Hawizy, Lezan; Murray-Rust, Peter; Tsujii, Junichi; Ananiadou, Sophia

2011-01-01

Chemistry text mining tools should be interoperable and adaptable regardless of system-level implementation, installation or even programming issues. We aim to abstract the functionality of these tools from the underlying implementation via reconfigurable workflows for automatically identifying chemical names. To achieve this, we refactored an established named entity recogniser (in the chemistry domain), OSCAR and studied the impact of each component on the net performance. We developed two reconfigurable workflows from OSCAR using an interoperable text mining framework, U-Compare. These workflows can be altered using the drag-&-drop mechanism of the graphical user interface of U-Compare. These workflows also provide a platform to study the relationship between text mining components such as tokenisation and named entity recognition (using maximum entropy Markov model (MEMM) and pattern recognition based classifiers). Results indicate that, for chemistry in particular, eliminating noise generated by tokenisation techniques lead to a slightly better performance than others, in terms of named entity recognition (NER) accuracy. Poor tokenisation translates into poorer input to the classifier components which in turn leads to an increase in Type I or Type II errors, thus, lowering the overall performance. On the Sciborg corpus, the workflow based system, which uses a new tokeniser whilst retaining the same MEMM component, increases the F-score from 82.35% to 84.44%. On the PubMed corpus, it recorded an F-score of 84.84% as against 84.23% by OSCAR. PMID:21633495

Using workflows to explore and optimise named entity recognition for chemistry.

PubMed

Kolluru, Balakrishna; Hawizy, Lezan; Murray-Rust, Peter; Tsujii, Junichi; Ananiadou, Sophia

2011-01-01

Chemistry text mining tools should be interoperable and adaptable regardless of system-level implementation, installation or even programming issues. We aim to abstract the functionality of these tools from the underlying implementation via reconfigurable workflows for automatically identifying chemical names. To achieve this, we refactored an established named entity recogniser (in the chemistry domain), OSCAR and studied the impact of each component on the net performance. We developed two reconfigurable workflows from OSCAR using an interoperable text mining framework, U-Compare. These workflows can be altered using the drag-&-drop mechanism of the graphical user interface of U-Compare. These workflows also provide a platform to study the relationship between text mining components such as tokenisation and named entity recognition (using maximum entropy Markov model (MEMM) and pattern recognition based classifiers). Results indicate that, for chemistry in particular, eliminating noise generated by tokenisation techniques lead to a slightly better performance than others, in terms of named entity recognition (NER) accuracy. Poor tokenisation translates into poorer input to the classifier components which in turn leads to an increase in Type I or Type II errors, thus, lowering the overall performance. On the Sciborg corpus, the workflow based system, which uses a new tokeniser whilst retaining the same MEMM component, increases the F-score from 82.35% to 84.44%. On the PubMed corpus, it recorded an F-score of 84.84% as against 84.23% by OSCAR.

Large scale and cloud-based multi-model analytics experiments on climate change data in the Earth System Grid Federation

NASA Astrophysics Data System (ADS)

Fiore, Sandro; Płóciennik, Marcin; Doutriaux, Charles; Blanquer, Ignacio; Barbera, Roberto; Donvito, Giacinto; Williams, Dean N.; Anantharaj, Valentine; Salomoni, Davide D.; Aloisio, Giovanni

2017-04-01

In many scientific domains such as climate, data is often n-dimensional and requires tools that support specialized data types and primitives to be properly stored, accessed, analysed and visualized. Moreover, new challenges arise in large-scale scenarios and eco-systems where petabytes (PB) of data can be available and data can be distributed and/or replicated, such as the Earth System Grid Federation (ESGF) serving the Coupled Model Intercomparison Project, Phase 5 (CMIP5) experiment, providing access to 2.5PB of data for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). A case study on climate models intercomparison data analysis addressing several classes of multi-model experiments is being implemented in the context of the EU H2020 INDIGO-DataCloud project. Such experiments require the availability of large amount of data (multi-terabyte order) related to the output of several climate models simulations as well as the exploitation of scientific data management tools for large-scale data analytics. More specifically, the talk discusses in detail a use case on precipitation trend analysis in terms of requirements, architectural design solution, and infrastructural implementation. The experiment has been tested and validated on CMIP5 datasets, in the context of a large scale distributed testbed across EU and US involving three ESGF sites (LLNL, ORNL, and CMCC) and one central orchestrator site (PSNC). The general "environment" of the case study relates to: (i) multi-model data analysis inter-comparison challenges; (ii) addressed on CMIP5 data; and (iii) which are made available through the IS-ENES/ESGF infrastructure. The added value of the solution proposed in the INDIGO-DataCloud project are summarized in the following: (i) it implements a different paradigm (from client- to server-side); (ii) it intrinsically reduces data movement; (iii) it makes lightweight the end-user setup; (iv) it fosters re-usability (of data, final/intermediate products, workflows, sessions, etc.) since everything is managed on the server-side; (v) it complements, extends and interoperates with the ESGF stack; (vi) it provides a "tool" for scientists to run multi-model experiments, and finally; and (vii) it can drastically reduce the time-to-solution for these experiments from weeks to hours. At the time the contribution is being written, the proposed testbed represents the first concrete implementation of a distributed multi-model experiment in the ESGF/CMIP context joining server-side and parallel processing, end-to-end workflow management and cloud computing. As opposed to the current scenario based on search & discovery, data download, and client-based data analysis, the INDIGO-DataCloud architectural solution described in this contribution addresses the scientific computing & analytics requirements by providing a paradigm shift based on server-side and high performance big data frameworks jointly with two-level workflow management systems realized at the PaaS level via a cloud infrastructure.

ASaiM: a Galaxy-based framework to analyze microbiota data.

PubMed

Batut, Bérénice; Gravouil, Kévin; Defois, Clémence; Hiltemann, Saskia; Brugère, Jean-François; Peyretaillade, Eric; Peyret, Pierre

2018-05-22

New generations of sequencing platforms coupled to numerous bioinformatics tools has led to rapid technological progress in metagenomics and metatranscriptomics to investigate complex microorganism communities. Nevertheless, a combination of different bioinformatic tools remains necessary to draw conclusions out of microbiota studies. Modular and user-friendly tools would greatly improve such studies. We therefore developed ASaiM, an Open-Source Galaxy-based framework dedicated to microbiota data analyses. ASaiM provides an extensive collection of tools to assemble, extract, explore and visualize microbiota information from raw metataxonomic, metagenomic or metatranscriptomic sequences. To guide the analyses, several customizable workflows are included and are supported by tutorials and Galaxy interactive tours, which guide users through the analyses step by step. ASaiM is implemented as a Galaxy Docker flavour. It is scalable to thousands of datasets, but also can be used on a normal PC. The associated source code is available under Apache 2 license at https://github.com/ASaiM/framework and documentation can be found online (http://asaim.readthedocs.io). Based on the Galaxy framework, ASaiM offers a sophisticated environment with a variety of tools, workflows, documentation and training to scientists working on complex microorganism communities. It makes analysis and exploration analyses of microbiota data easy, quick, transparent, reproducible and shareable.

The architecture of a virtual grid GIS server

NASA Astrophysics Data System (ADS)

Wu, Pengfei; Fang, Yu; Chen, Bin; Wu, Xi; Tian, Xiaoting

2008-10-01

The grid computing technology provides the service oriented architecture for distributed applications. The virtual Grid GIS server is the distributed and interoperable enterprise application GIS architecture running in the grid environment, which integrates heterogeneous GIS platforms. All sorts of legacy GIS platforms join the grid as members of GIS virtual organization. Based on Microkernel we design the ESB and portal GIS service layer, which compose Microkernel GIS. Through web portals, portal GIS services and mediation of service bus, following the principle of SoC, we separate business logic from implementing logic. Microkernel GIS greatly reduces the coupling degree between applications and GIS platforms. The enterprise applications are independent of certain GIS platforms, and making the application developers to pay attention to the business logic. Via configuration and orchestration of a set of fine-grained services, the system creates GIS Business, which acts as a whole WebGIS request when activated. In this way, the system satisfies a business workflow directly and simply, with little or no new code.

Orchestrating emotion and action in an evolutionary framework. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

NASA Astrophysics Data System (ADS)

Arbib, Michael A.

2015-06-01

The lead author of the Quartet Theory [10] is, appropriately enough, an expert on the neuroscience linking music and emotion, and examples of this linkage are a welcome feature of the article. Actually, the article charts two quartets: A structural quartet of affect systems centered on (i) brainstem, (ii) diencephalon, (iii) hippocampus and (iv) orbitofrontal cortex.

Towards Dynamic Authentication in the Grid — Secure and Mobile Business Workflows Using GSet

NASA Astrophysics Data System (ADS)

Mangler, Jürgen; Schikuta, Erich; Witzany, Christoph; Jorns, Oliver; Ul Haq, Irfan; Wanek, Helmut

Until now, the research community mainly focused on the technical aspects of Grid computing and neglected commercial issues. However, recently the community tends to accept that the success of the Grid is crucially based on commercial exploitation. In our vision Foster's and Kesselman's statement "The Grid is all about sharing." has to be extended by "... and making money out of it!". To allow for the realization of this vision the trust-worthyness of the underlying technology needs to be ensured. This can be achieved by the use of gSET (Gridified Secure Electronic Transaction) as a basic technology for trust management and secure accounting in the presented Grid based workflow. We present a framework, conceptually and technically, from the area of the Mobile-Grid, which justifies the Grid infrastructure as a viable platform to enable commercially successful business workflows.

Enhanced reproducibility of SADI web service workflows with Galaxy and Docker.

PubMed

Aranguren, Mikel Egaña; Wilkinson, Mark D

2015-01-01

Semantic Web technologies have been widely applied in the life sciences, for example by data providers such as OpenLifeData and through web services frameworks such as SADI. The recently reported OpenLifeData2SADI project offers access to the vast OpenLifeData data store through SADI services. This article describes how to merge data retrieved from OpenLifeData2SADI with other SADI services using the Galaxy bioinformatics analysis platform, thus making this semantic data more amenable to complex analyses. This is demonstrated using a working example, which is made distributable and reproducible through a Docker image that includes SADI tools, along with the data and workflows that constitute the demonstration. The combination of Galaxy and Docker offers a solution for faithfully reproducing and sharing complex data retrieval and analysis workflows based on the SADI Semantic web service design patterns.

Virtual Sensor Web Architecture

NASA Astrophysics Data System (ADS)

Bose, P.; Zimdars, A.; Hurlburt, N.; Doug, S.

2006-12-01

NASA envisions the development of smart sensor webs, intelligent and integrated observation network that harness distributed sensing assets, their associated continuous and complex data sets, and predictive observation processing mechanisms for timely, collaborative hazard mitigation and enhanced science productivity and reliability. This paper presents Virtual Sensor Web Infrastructure for Collaborative Science (VSICS) Architecture for sustained coordination of (numerical and distributed) model-based processing, closed-loop resource allocation, and observation planning. VSICS's key ideas include i) rich descriptions of sensors as services based on semantic markup languages like OWL and SensorML; ii) service-oriented workflow composition and repair for simple and ensemble models; event-driven workflow execution based on event-based and distributed workflow management mechanisms; and iii) development of autonomous model interaction management capabilities providing closed-loop control of collection resources driven by competing targeted observation needs. We present results from initial work on collaborative science processing involving distributed services (COSEC framework) that is being extended to create VSICS.

IceProd 2 Usage Experience

NASA Astrophysics Data System (ADS)

Delventhal, D.; Schultz, D.; Diaz Velez, J. C.

2017-10-01

IceProd is a data processing and management framework developed by the IceCube Neutrino Observatory for processing of Monte Carlo simulations, detector data, and data driven analysis. It runs as a separate layer on top of grid and batch systems. This is accomplished by a set of daemons which process job workflow, maintaining configuration and status information on the job before, during, and after processing. IceProd can also manage complex workflow DAGs across distributed computing grids in order to optimize usage of resources. IceProd has recently been rewritten to increase its scaling capabilities, handle user analysis workflows together with simulation production, and facilitate the integration with 3rd party scheduling tools. IceProd 2, the second generation of IceProd, has been running in production for several months now. We share our experience setting up the system and things we’ve learned along the way.

Modeling workflow to design machine translation applications for public health practice

PubMed Central

Turner, Anne M.; Brownstein, Megumu K.; Cole, Kate; Karasz, Hilary; Kirchhoff, Katrin

2014-01-01

Objective Provide a detailed understanding of the information workflow processes related to translating health promotion materials for limited English proficiency individuals in order to inform the design of context-driven machine translation (MT) tools for public health (PH). Materials and Methods We applied a cognitive work analysis framework to investigate the translation information workflow processes of two large health departments in Washington State. Researchers conducted interviews, performed a task analysis, and validated results with PH professionals to model translation workflow and identify functional requirements for a translation system for PH. Results The study resulted in a detailed description of work related to translation of PH materials, an information workflow diagram, and a description of attitudes towards MT technology. We identified a number of themes that hold design implications for incorporating MT in PH translation practice. A PH translation tool prototype was designed based on these findings. Discussion This study underscores the importance of understanding the work context and information workflow for which systems will be designed. Based on themes and translation information workflow processes, we identified key design guidelines for incorporating MT into PH translation work. Primary amongst these is that MT should be followed by human review for translations to be of high quality and for the technology to be adopted into practice. Counclusion The time and costs of creating multilingual health promotion materials are barriers to translation. PH personnel were interested in MT's potential to improve access to low-cost translated PH materials, but expressed concerns about ensuring quality. We outline design considerations and a potential machine translation tool to best fit MT systems into PH practice. PMID:25445922

Abstracted Workow Framework with a Structure from Motion Application

NASA Astrophysics Data System (ADS)

Rossi, Adam J.

In scientific and engineering disciplines, from academia to industry, there is an increasing need for the development of custom software to perform experiments, construct systems, and develop products. The natural mindset initially is to shortcut and bypass all overhead and process rigor in order to obtain an immediate result for the problem at hand, with the misconception that the software will simply be thrown away at the end. In a majority of the cases, it turns out the software persists for many years, and likely ends up in production systems for which it was not initially intended. In the current study, a framework that can be used in both industry and academic applications mitigates underlying problems associated with developing scientific and engineering software. This results in software that is much more maintainable, documented, and usable by others, specifically allowing new users to extend capabilities of components already implemented in the framework. There is a multi-disciplinary need in the fields of imaging science, computer science, and software engineering for a unified implementation model, which motivates the development of an abstracted software framework. Structure from motion (SfM) has been identified as one use case where the abstracted workflow framework can improve research efficiencies and eliminate implementation redundancies in scientific fields. The SfM process begins by obtaining 2D images of a scene from different perspectives. Features from the images are extracted and correspondences are established. This provides a sufficient amount of information to initialize the problem for fully automated processing. Transformations are established between views, and 3D points are established via triangulation algorithms. The parameters for the camera models for all views / images are solved through bundle adjustment, establishing a highly consistent point cloud. The initial sparse point cloud and camera matrices are used to generate a dense point cloud through patch based techniques or densification algorithms such as Semi-Global Matching (SGM). The point cloud can be visualized or exploited by both humans and automated techniques. In some cases the point cloud is "draped" with original imagery in order to enhance the 3D model for a human viewer. The SfM workflow can be implemented in the abstracted framework, making it easily leverageable and extensible by multiple users. Like many processes in scientific and engineering domains, the workflow described for SfM is complex and requires many disparate components to form a functional system, often utilizing algorithms implemented by many users in different languages / environments and without knowledge of how the component fits into the larger system. In practice, this generally leads to issues interfacing the components, building the software for desired platforms, understanding its concept of operations, and how it can be manipulated in order to fit the desired function for a particular application. In addition, other scientists and engineers instinctively wish to analyze the performance of the system, establish new algorithms, optimize existing processes, and establish new functionality based on current research. This requires a framework whereby new components can be easily plugged in without affecting the current implemented functionality. The need for a universal programming environment establishes the motivation for the development of the abstracted workflow framework. This software implementation, named Catena, provides base classes from which new components must derive in order to operate within the framework. The derivation mandates requirements be satisfied in order to provide a complete implementation. Additionally, the developer must provide documentation of the component in terms of its overall function and inputs. The interface input and output values corresponding to the component must be defined in terms of their respective data types, and the implementation uses mechanisms within the framework to retrieve and send the values. This process requires the developer to componentize their algorithm rather than implement it monolithically. Although the requirements of the developer are slightly greater, the benefits realized from using Catena far outweigh the overhead, and results in extensible software. This thesis provides a basis for the abstracted workflow framework concept and the Catena software implementation. The benefits are also illustrated using a detailed examination of the SfM process as an example application.

A conceptual framework for managing clinical processes.

PubMed

Buffone, G J; Moreau, D

1997-01-01

Reengineering of the health care delivery system is underway, as is the transformation of the processes and methods used for recording information describing patient care (i.e., the development of a computer-based record). This report describes the use of object-oriented analysis and design to develop and implement clinical process reengineering as well as the organization of clinical data. In addition, the facility of the proposed framework for implementing workflow computing is discussed.

Comparing Information Access Approaches.

ERIC Educational Resources Information Center

Chalmers, Matthew

1999-01-01

Presents a broad view of information access, drawing from philosophy and semiology in constructing a framework for comparative discussion that is used to examine the information representations that underlie four approaches to information access--information retrieval, workflow, collaborative filtering, and the path model. Contains 32 references.…

JACOB: an enterprise framework for computational chemistry.

PubMed

Waller, Mark P; Dresselhaus, Thomas; Yang, Jack

2013-06-15

Here, we present just a collection of beans (JACOB): an integrated batch-based framework designed for the rapid development of computational chemistry applications. The framework expedites developer productivity by handling the generic infrastructure tier, and can be easily extended by user-specific scientific code. Paradigms from enterprise software engineering were rigorously applied to create a scalable, testable, secure, and robust framework. A centralized web application is used to configure and control the operation of the framework. The application-programming interface provides a set of generic tools for processing large-scale noninteractive jobs (e.g., systematic studies), or for coordinating systems integration (e.g., complex workflows). The code for the JACOB framework is open sourced and is available at: www.wallerlab.org/jacob. Copyright © 2013 Wiley Periodicals, Inc.

Histostitcher™: An informatics software platform for reconstructing whole-mount prostate histology using the extensible imaging platform framework

PubMed Central

Toth, Robert J.; Shih, Natalie; Tomaszewski, John E.; Feldman, Michael D.; Kutter, Oliver; Yu, Daphne N.; Paulus, John C.; Paladini, Ginaluca; Madabhushi, Anant

2014-01-01

Context: Co-registration of ex-vivo histologic images with pre-operative imaging (e.g., magnetic resonance imaging [MRI]) can be used to align and map disease extent, and to identify quantitative imaging signatures. However, ex-vivo histology images are frequently sectioned into quarters prior to imaging. Aims: This work presents Histostitcher™, a software system designed to create a pseudo whole mount histology section (WMHS) from a stitching of four individual histology quadrant images. Materials and Methods: Histostitcher™ uses user-identified fiducials on the boundary of two quadrants to stitch such quadrants. An original prototype of Histostitcher™ was designed using the Matlab programming languages. However, clinical use was limited due to slow performance, computer memory constraints and an inefficient workflow. The latest version was created using the extensible imaging platform (XIP™) architecture in the C++ programming language. A fast, graphics processor unit renderer was designed to intelligently cache the visible parts of the histology quadrants and the workflow was significantly improved to allow modifying existing fiducials, fast transformations of the quadrants and saving/loading sessions. Results: The new stitching platform yielded significantly more efficient workflow and reconstruction than the previous prototype. It was tested on a traditional desktop computer, a Windows 8 Surface Pro table device and a 27 inch multi-touch display, with little performance difference between the different devices. Conclusions: Histostitcher™ is a fast, efficient framework for reconstructing pseudo WMHS from individually imaged quadrants. The highly modular XIP™ framework was used to develop an intuitive interface and future work will entail mapping the disease extent from the pseudo WMHS onto pre-operative MRI. PMID:24843820

pyNSMC: A Python Module for Null-Space Monte Carlo Uncertainty Analysis

NASA Astrophysics Data System (ADS)

White, J.; Brakefield, L. K.

2015-12-01

The null-space monte carlo technique is a non-linear uncertainty analyses technique that is well-suited to high-dimensional inverse problems. While the technique is powerful, the existing workflow for completing null-space monte carlo is cumbersome, requiring the use of multiple commandline utilities, several sets of intermediate files and even a text editor. pyNSMC is an open-source python module that automates the workflow of null-space monte carlo uncertainty analyses. The module is fully compatible with the PEST and PEST++ software suites and leverages existing functionality of pyEMU, a python framework for linear-based uncertainty analyses. pyNSMC greatly simplifies the existing workflow for null-space monte carlo by taking advantage of object oriented design facilities in python. The core of pyNSMC is the ensemble class, which draws and stores realized random vectors and also provides functionality for exporting and visualizing results. By relieving users of the tedium associated with file handling and command line utility execution, pyNSMC instead focuses the user on the important steps and assumptions of null-space monte carlo analysis. Furthermore, pyNSMC facilitates learning through flow charts and results visualization, which are available at many points in the algorithm. The ease-of-use of the pyNSMC workflow is compared to the existing workflow for null-space monte carlo for a synthetic groundwater model with hundreds of estimable parameters.

Galaxy tools and workflows for sequence analysis with applications in molecular plant pathology.

PubMed

Cock, Peter J A; Grüning, Björn A; Paszkiewicz, Konrad; Pritchard, Leighton

2013-01-01

The Galaxy Project offers the popular web browser-based platform Galaxy for running bioinformatics tools and constructing simple workflows. Here, we present a broad collection of additional Galaxy tools for large scale analysis of gene and protein sequences. The motivating research theme is the identification of specific genes of interest in a range of non-model organisms, and our central example is the identification and prediction of "effector" proteins produced by plant pathogens in order to manipulate their host plant. This functional annotation of a pathogen's predicted capacity for virulence is a key step in translating sequence data into potential applications in plant pathology. This collection includes novel tools, and widely-used third-party tools such as NCBI BLAST+ wrapped for use within Galaxy. Individual bioinformatics software tools are typically available separately as standalone packages, or in online browser-based form. The Galaxy framework enables the user to combine these and other tools to automate organism scale analyses as workflows, without demanding familiarity with command line tools and scripting. Workflows created using Galaxy can be saved and are reusable, so may be distributed within and between research groups, facilitating the construction of a set of standardised, reusable bioinformatic protocols. The Galaxy tools and workflows described in this manuscript are open source and freely available from the Galaxy Tool Shed (http://usegalaxy.org/toolshed or http://toolshed.g2.bx.psu.edu).

Build and Execute Environment

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

Guan, Qiang

At exascale, the challenge becomes to develop applications that run at scale and use exascale platforms reliably, efficiently, and flexibly. Workflows become much more complex because they must seamlessly integrate simulation and data analytics. They must include down-sampling, post-processing, feature extraction, and visualization. Power and data transfer limitations require these analysis tasks to be run in-situ or in-transit. We expect successful workflows will comprise multiple linked simulations along with tens of analysis routines. Users will have limited development time at scale and, therefore, must have rich tools to develop, debug, test, and deploy applications. At this scale, successful workflows willmore » compose linked computations from an assortment of reliable, well-defined computation elements, ones that can come and go as required, based on the needs of the workflow over time. We propose a novel framework that utilizes both virtual machines (VMs) and software containers to create a workflow system that establishes a uniform build and execution environment (BEE) beyond the capabilities of current systems. In this environment, applications will run reliably and repeatably across heterogeneous hardware and software. Containers, both commercial (Docker and Rocket) and open-source (LXC and LXD), define a runtime that isolates all software dependencies from the machine operating system. Workflows may contain multiple containers that run different operating systems, different software, and even different versions of the same software. We will run containers in open-source virtual machines (KVM) and emulators (QEMU) so that workflows run on any machine entirely in user-space. On this platform of containers and virtual machines, we will deliver workflow software that provides services, including repeatable execution, provenance, checkpointing, and future proofing. We will capture provenance about how containers were launched and how they interact to annotate workflows for repeatable and partial re-execution. We will coordinate the physical snapshots of virtual machines with parallel programming constructs, such as barriers, to automate checkpoint and restart. We will also integrate with HPC-specific container runtimes to gain access to accelerators and other specialized hardware to preserve native performance. Containers will link development to continuous integration. When application developers check code in, it will automatically be tested on a suite of different software and hardware architectures.« less

Horizon: The Portable, Scalable, and Reusable Framework for Developing Automated Data Management and Product Generation Systems

NASA Astrophysics Data System (ADS)

Huang, T.; Alarcon, C.; Quach, N. T.

2014-12-01

Capture, curate, and analysis are the typical activities performed at any given Earth Science data center. Modern data management systems must be adaptable to heterogeneous science data formats, scalable to meet the mission's quality of service requirements, and able to manage the life-cycle of any given science data product. Designing a scalable data management doesn't happen overnight. It takes countless hours of refining, refactoring, retesting, and re-architecting. The Horizon data management and workflow framework, developed at the Jet Propulsion Laboratory, is a portable, scalable, and reusable framework for developing high-performance data management and product generation workflow systems to automate data capturing, data curation, and data analysis activities. The NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC)'s Data Management and Archive System (DMAS) is its core data infrastructure that handles capturing and distribution of hundreds of thousands of satellite observations each day around the clock. DMAS is an application of the Horizon framework. The NASA Global Imagery Browse Services (GIBS) is NASA's Earth Observing System Data and Information System (EOSDIS)'s solution for making high-resolution global imageries available to the science communities. The Imagery Exchange (TIE), an application of the Horizon framework, is a core subsystem for GIBS responsible for data capturing and imagery generation automation to support the EOSDIS' 12 distributed active archive centers and 17 Science Investigator-led Processing Systems (SIPS). This presentation discusses our ongoing effort in refining, refactoring, retesting, and re-architecting the Horizon framework to enable data-intensive science and its applications.

PATHA: Performance Analysis Tool for HPC Applications

DOE PAGES

Yoo, Wucherl; Koo, Michelle; Cao, Yi; ...

2016-02-18

Large science projects rely on complex workflows to analyze terabytes or petabytes of data. These jobs are often running over thousands of CPU cores and simultaneously performing data accesses, data movements, and computation. It is difficult to identify bottlenecks or to debug the performance issues in these large workflows. In order to address these challenges, we have developed Performance Analysis Tool for HPC Applications (PATHA) using the state-of-art open source big data processing tools. Our framework can ingest system logs to extract key performance measures, and apply the most sophisticated statistical tools and data mining methods on the performance data.more » Furthermore, it utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of PATHA, we conduct a case study on the workflows from an astronomy project known as the Palomar Transient Factory (PTF). This study processed 1.6 TB of system logs collected on the NERSC supercomputer Edison. Using PATHA, we were able to identify performance bottlenecks, which reside in three tasks of PTF workflow with the dependency on the density of celestial objects.« less

Sensor-based architecture for medical imaging workflow analysis.

PubMed

Silva, Luís A Bastião; Campos, Samuel; Costa, Carlos; Oliveira, José Luis

2014-08-01

The growing use of computer systems in medical institutions has been generating a tremendous quantity of data. While these data have a critical role in assisting physicians in the clinical practice, the information that can be extracted goes far beyond this utilization. This article proposes a platform capable of assembling multiple data sources within a medical imaging laboratory, through a network of intelligent sensors. The proposed integration framework follows a SOA hybrid architecture based on an information sensor network, capable of collecting information from several sources in medical imaging laboratories. Currently, the system supports three types of sensors: DICOM repository meta-data, network workflows and examination reports. Each sensor is responsible for converting unstructured information from data sources into a common format that will then be semantically indexed in the framework engine. The platform was deployed in the Cardiology department of a central hospital, allowing identification of processes' characteristics and users' behaviours that were unknown before the utilization of this solution.

Large-Scale Compute-Intensive Analysis via a Combined In-situ and Co-scheduling Workflow Approach

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

Messer, Bronson; Sewell, Christopher; Heitmann, Katrin

2015-01-01

Large-scale simulations can produce tens of terabytes of data per analysis cycle, complicating and limiting the efficiency of workflows. Traditionally, outputs are stored on the file system and analyzed in post-processing. With the rapidly increasing size and complexity of simulations, this approach faces an uncertain future. Trending techniques consist of performing the analysis in situ, utilizing the same resources as the simulation, and/or off-loading subsets of the data to a compute-intensive analysis system. We introduce an analysis framework developed for HACC, a cosmological N-body code, that uses both in situ and co-scheduling approaches for handling Petabyte-size outputs. An initial inmore » situ step is used to reduce the amount of data to be analyzed, and to separate out the data-intensive tasks handled off-line. The analysis routines are implemented using the PISTON/VTK-m framework, allowing a single implementation of an algorithm that simultaneously targets a variety of GPU, multi-core, and many-core architectures.« less

A conceptual framework for using DOE 5700.6C and the other DOE orders as an integrated management system; the Fermilab experience

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

Bodnarczuk, M.

In this paper, I describe a conceptual framework that uses DOE Order 5700.6C and more than 140 other DOE Orders as an integrated management system -- but I describe it within the context of the broader sociological and cultural issues of doing research at DOE funded facilities. The conceptual framework has two components. The first involves an interpretation of the 10 criteria of DOE 5700.6C that is tailored for a research environment. The second component involves using the 10 criteria as functional categories that orchestrate and integrate the other DOE Orders into a total management system. The Fermilab approach aimsmore » at reducing (or eliminating) the redundancy and overlap within the DOE Orders system at the contractor level.« less

A conceptual framework for using DOE 5700. 6C and the other DOE orders as an integrated management system; the Fermilab experience

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

Bodnarczuk, M.

In this paper, I describe a conceptual framework that uses DOE Order 5700.6C and more than 140 other DOE Orders as an integrated management system -- but I describe it within the context of the broader sociological and cultural issues of doing research at DOE funded facilities. The conceptual framework has two components. The first involves an interpretation of the 10 criteria of DOE 5700.6C that is tailored for a research environment. The second component involves using the 10 criteria as functional categories that orchestrate and integrate the other DOE Orders into a total management system. The Fermilab approach aimsmore » at reducing (or eliminating) the redundancy and overlap within the DOE Orders system at the contractor level.« less

Talkoot Portals: Discover, Tag, Share, and Reuse Collaborative Science Workflows

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Ramachandran, R.; Lynnes, C.

2009-05-01

A small but growing number of scientists are beginning to harness Web 2.0 technologies, such as wikis, blogs, and social tagging, as a transformative way of doing science. These technologies provide researchers easy mechanisms to critique, suggest and share ideas, data and algorithms. At the same time, large suites of algorithms for science analysis are being made available as remotely-invokable Web Services, which can be chained together to create analysis workflows. This provides the research community an unprecedented opportunity to collaborate by sharing their workflows with one another, reproducing and analyzing research results, and leveraging colleagues' expertise to expedite the process of scientific discovery. However, wikis and similar technologies are limited to text, static images and hyperlinks, providing little support for collaborative data analysis. A team of information technology and Earth science researchers from multiple institutions have come together to improve community collaboration in science analysis by developing a customizable "software appliance" to build collaborative portals for Earth Science services and analysis workflows. The critical requirement is that researchers (not just information technologists) be able to build collaborative sites around service workflows within a few hours. We envision online communities coming together, much like Finnish "talkoot" (a barn raising), to build a shared research space. Talkoot extends a freely available, open source content management framework with a series of modules specific to Earth Science for registering, creating, managing, discovering, tagging and sharing Earth Science web services and workflows for science data processing, analysis and visualization. Users will be able to author a "science story" in shareable web notebooks, including plots or animations, backed up by an executable workflow that directly reproduces the science analysis. New services and workflows of interest will be discoverable using tag search, and advertised using "service casts" and "interest casts" (Atom feeds). Multiple science workflow systems will be plugged into the system, with initial support for UAH's Mining Workflow Composer and the open-source Active BPEL engine, and JPL's SciFlo engine and the VizFlow visual programming interface. With the ability to share and execute analysis workflows, Talkoot portals can be used to do collaborative science in addition to communicate ideas and results. It will be useful for different science domains, mission teams, research projects and organizations. Thus, it will help to solve the "sociological" problem of bringing together disparate groups of researchers, and the technical problem of advertising, discovering, developing, documenting, and maintaining inter-agency science workflows. The presentation will discuss the goals of and barriers to Science 2.0, the social web technologies employed in the Talkoot software appliance (e.g. CMS, social tagging, personal presence, advertising by feeds, etc.), illustrate the resulting collaborative capabilities, and show early prototypes of the web interfaces (e.g. embedded workflows).

Developing a Workflow Composite Score to Measure Clinical Information Logistics. A Top-down Approach.

PubMed

Liebe, J D; Hübner, U; Straede, M C; Thye, J

2015-01-01

Availability and usage of individual IT applications have been studied intensively in the past years. Recently, IT support of clinical processes is attaining increasing attention. The underlying construct that describes the IT support of clinical workflows is clinical information logistics. This construct needs to be better understood, operationalised and measured. It is therefore the aim of this study to propose and develop a workflow composite score (WCS) for measuring clinical information logistics and to examine its quality based on reliability and validity analyses. We largely followed the procedural model of MacKenzie and colleagues (2011) for defining and conceptualising the construct domain, for developing the measurement instrument, assessing the content validity, pretesting the instrument, specifying the model, capturing the data and computing the WCS and testing the reliability and validity. Clinical information logistics was decomposed into the descriptors data and information, function, integration and distribution, which embraced the framework validated by an analysis of the international literature. This framework was refined selecting representative clinical processes. We chose ward rounds, pre- and post-surgery processes and discharge as sample processes that served as concrete instances for the measurements. They are sufficiently complex, represent core clinical processes and involve different professions, departments and settings. The score was computed on the basis of data from 183 hospitals of different size, ownership, location and teaching status. Testing the reliability and validity yielded encouraging results: the reliability was high with r(split-half) = 0.89, the WCS discriminated between groups; the WCS correlated significantly and moderately with two EHR models and the WCS received good evaluation results by a sample of chief information officers (n = 67). These findings suggest the further utilisation of the WCS. As the WCS does not assume ideal workflows as a gold standard but measures IT support of clinical workflows according to validated descriptors a high portability of the WCS to other hospitals in other countries is very likely. The WCS will contribute to a better understanding of the construct clinical information logistics.

Big data analytics workflow management for eScience

NASA Astrophysics Data System (ADS)

Fiore, Sandro; D'Anca, Alessandro; Palazzo, Cosimo; Elia, Donatello; Mariello, Andrea; Nassisi, Paola; Aloisio, Giovanni

2015-04-01

In many domains such as climate and astrophysics, scientific data is often n-dimensional and requires tools that support specialized data types and primitives if it is to be properly stored, accessed, analysed and visualized. Currently, scientific data analytics relies on domain-specific software and libraries providing a huge set of operators and functionalities. However, most of these software fail at large scale since they: (i) are desktop based, rely on local computing capabilities and need the data locally; (ii) cannot benefit from available multicore/parallel machines since they are based on sequential codes; (iii) do not provide declarative languages to express scientific data analysis tasks, and (iv) do not provide newer or more scalable storage models to better support the data multidimensionality. Additionally, most of them: (v) are domain-specific, which also means they support a limited set of data formats, and (vi) do not provide a workflow support, to enable the construction, execution and monitoring of more complex "experiments". The Ophidia project aims at facing most of the challenges highlighted above by providing a big data analytics framework for eScience. Ophidia provides several parallel operators to manipulate large datasets. Some relevant examples include: (i) data sub-setting (slicing and dicing), (ii) data aggregation, (iii) array-based primitives (the same operator applies to all the implemented UDF extensions), (iv) data cube duplication, (v) data cube pivoting, (vi) NetCDF-import and export. Metadata operators are available too. Additionally, the Ophidia framework provides array-based primitives to perform data sub-setting, data aggregation (i.e. max, min, avg), array concatenation, algebraic expressions and predicate evaluation on large arrays of scientific data. Bit-oriented plugins have also been implemented to manage binary data cubes. Defining processing chains and workflows with tens, hundreds of data analytics operators is the real challenge in many practical scientific use cases. This talk will specifically address the main needs, requirements and challenges regarding data analytics workflow management applied to large scientific datasets. Three real use cases concerning analytics workflows for sea situational awareness, fire danger prevention, climate change and biodiversity will be discussed in detail.

A computational framework for automation of point defect calculations

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

Goyal, Anuj; Gorai, Prashun; Peng, Haowei

We have developed a complete and rigorously validated open-source Python framework to automate point defect calculations using density functional theory. Furthermore, the framework provides an effective and efficient method for defect structure generation, and creation of simple yet customizable workflows to analyze defect calculations. This package provides the capability to compute widely-accepted correction schemes to overcome finite-size effects, including (1) potential alignment, (2) image-charge correction, and (3) band filling correction to shallow defects. Using Si, ZnO and In2O3 as test examples, we demonstrate the package capabilities and validate the methodology.

A computational framework for automation of point defect calculations

DOE PAGES

Goyal, Anuj; Gorai, Prashun; Peng, Haowei; ...

2017-01-13

We have developed a complete and rigorously validated open-source Python framework to automate point defect calculations using density functional theory. Furthermore, the framework provides an effective and efficient method for defect structure generation, and creation of simple yet customizable workflows to analyze defect calculations. This package provides the capability to compute widely-accepted correction schemes to overcome finite-size effects, including (1) potential alignment, (2) image-charge correction, and (3) band filling correction to shallow defects. Using Si, ZnO and In2O3 as test examples, we demonstrate the package capabilities and validate the methodology.

An open data mining framework for the analysis of medical images: application on obstructive nephropathy microscopy images.

PubMed

Doukas, Charalampos; Goudas, Theodosis; Fischer, Simon; Mierswa, Ingo; Chatziioannou, Aristotle; Maglogiannis, Ilias

2010-01-01

This paper presents an open image-mining framework that provides access to tools and methods for the characterization of medical images. Several image processing and feature extraction operators have been implemented and exposed through Web Services. Rapid-Miner, an open source data mining system has been utilized for applying classification operators and creating the essential processing workflows. The proposed framework has been applied for the detection of salient objects in Obstructive Nephropathy microscopy images. Initial classification results are quite promising demonstrating the feasibility of automated characterization of kidney biopsy images.

ASCEM Data Brower (ASCEMDB) v0.8

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

ROMOSAN, ALEXANDRU

Data management tool designed for the Advanced Simulation Capability for Environmental Management (ASCEM) framework. Distinguishing features of this gateway include: (1) handling of complex geometry data, (2) advance selection mechanism, (3) state of art rendering of spatiotemporal data records, and (4) seamless integration with a distributed workflow engine.

WRF4SG: A Scientific Gateway for climate experiment workflows

NASA Astrophysics Data System (ADS)

Blanco, Carlos; Cofino, Antonio S.; Fernandez-Quiruelas, Valvanuz

2013-04-01

The Weather Research and Forecasting model (WRF) is a community-driven and public domain model widely used by the weather and climate communities. As opposite to other application-oriented models, WRF provides a flexible and computationally-efficient framework which allows solving a variety of problems for different time-scales, from weather forecast to climate change projection. Furthermore, WRF is also widely used as a research tool in modeling physics, dynamics, and data assimilation by the research community. Climate experiment workflows based on Weather Research and Forecasting (WRF) are nowadays among the one of the most cutting-edge applications. These workflows are complex due to both large storage and the huge number of simulations executed. In order to manage that, we have developed a scientific gateway (SG) called WRF for Scientific Gateway (WRF4SG) based on WS-PGRADE/gUSE and WRF4G frameworks to ease achieve WRF users needs (see [1] and [2]). WRF4SG provides services for different use cases that describe the different interactions between WRF users and the WRF4SG interface in order to show how to run a climate experiment. As WS-PGRADE/gUSE uses portlets (see [1]) to interact with users, its portlets will support these use cases. A typical experiment to be carried on by a WRF user will consist on a high-resolution regional re-forecast. These re-forecasts are common experiments used as input data form wind power energy and natural hazards (wind and precipitation fields). In the cases below, the user is able to access to different resources such as Grid due to the fact that WRF needs a huge amount of computing resources in order to generate useful simulations: * Resource configuration and user authentication: The first step is to authenticate on users' Grid resources by virtual organizations. After login, the user is able to select which virtual organization is going to be used by the experiment. * Data assimilation: In order to assimilate the data sources, the user has to select them browsing through LFC Portlet. * Design Experiment workflow: In order to configure the experiment, the user will define the type of experiment (i.e. re-forecast), and its attributes to simulate. In this case the main attributes are: the field of interest (wind, precipitation, ...), the start and end date simulation and the requirements of the experiment. * Monitor workflow: In order to monitor the experiment the user will receive notification messages based on events and also the gateway will display the progress of the experiment. * Data storage: Like Data assimilation case, the user is able to browse and view the output data simulations using LFC Portlet. The objectives of WRF4SG can be described by considering two goals. The first goal is to show how WRF4SG facilitates to execute, monitor and manage climate workflows based on the WRF4G framework. And the second goal of WRF4SG is to help WRF users to execute their experiment workflows concurrently using heterogeneous computing resources such as HPC and Grid. [1] Kacsuk, P.: P-GRADE portal family for grid infrastructures. Concurrency and Computation: Practice and Experience. 23, 235-245 (2011). [2] http://www.meteo.unican.es/software/wrf4g

Metavisitor, a Suite of Galaxy Tools for Simple and Rapid Detection and Discovery of Viruses in Deep Sequence Data

PubMed Central

Vernick, Kenneth D.

2017-01-01

Metavisitor is a software package that allows biologists and clinicians without specialized bioinformatics expertise to detect and assemble viral genomes from deep sequence datasets. The package is composed of a set of modular bioinformatic tools and workflows that are implemented in the Galaxy framework. Using the graphical Galaxy workflow editor, users with minimal computational skills can use existing Metavisitor workflows or adapt them to suit specific needs by adding or modifying analysis modules. Metavisitor works with DNA, RNA or small RNA sequencing data over a range of read lengths and can use a combination of de novo and guided approaches to assemble genomes from sequencing reads. We show that the software has the potential for quick diagnosis as well as discovery of viruses from a vast array of organisms. Importantly, we provide here executable Metavisitor use cases, which increase the accessibility and transparency of the software, ultimately enabling biologists or clinicians to focus on biological or medical questions. PMID:28045932

SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research.

PubMed

Yaniv, Ziv; Lowekamp, Bradley C; Johnson, Hans J; Beare, Richard

2018-06-01

Modern scientific endeavors increasingly require team collaborations to construct and interpret complex computational workflows. This work describes an image-analysis environment that supports the use of computational tools that facilitate reproducible research and support scientists with varying levels of software development skills. The Jupyter notebook web application is the basis of an environment that enables flexible, well-documented, and reproducible workflows via literate programming. Image-analysis software development is made accessible to scientists with varying levels of programming experience via the use of the SimpleITK toolkit, a simplified interface to the Insight Segmentation and Registration Toolkit. Additional features of the development environment include user friendly data sharing using online data repositories and a testing framework that facilitates code maintenance. SimpleITK provides a large number of examples illustrating educational and research-oriented image analysis workflows for free download from GitHub under an Apache 2.0 license: github.com/InsightSoftwareConsortium/SimpleITK-Notebooks .

MetaNET--a web-accessible interactive platform for biological metabolic network analysis.

PubMed

Narang, Pankaj; Khan, Shawez; Hemrom, Anmol Jaywant; Lynn, Andrew Michael

2014-01-01

Metabolic reactions have been extensively studied and compiled over the last century. These have provided a theoretical base to implement models, simulations of which are used to identify drug targets and optimize metabolic throughput at a systemic level. While tools for the perturbation of metabolic networks are available, their applications are limited and restricted as they require varied dependencies and often a commercial platform for full functionality. We have developed MetaNET, an open source user-friendly platform-independent and web-accessible resource consisting of several pre-defined workflows for metabolic network analysis. MetaNET is a web-accessible platform that incorporates a range of functions which can be combined to produce different simulations related to metabolic networks. These include (i) optimization of an objective function for wild type strain, gene/catalyst/reaction knock-out/knock-down analysis using flux balance analysis. (ii) flux variability analysis (iii) chemical species participation (iv) cycles and extreme paths identification and (v) choke point reaction analysis to facilitate identification of potential drug targets. The platform is built using custom scripts along with the open-source Galaxy workflow and Systems Biology Research Tool as components. Pre-defined workflows are available for common processes, and an exhaustive list of over 50 functions are provided for user defined workflows. MetaNET, available at http://metanet.osdd.net , provides a user-friendly rich interface allowing the analysis of genome-scale metabolic networks under various genetic and environmental conditions. The framework permits the storage of previous results, the ability to repeat analysis and share results with other users over the internet as well as run different tools simultaneously using pre-defined workflows, and user-created custom workflows.

Nanosurveyor: a framework for real-time data processing

DOE PAGES

Daurer, Benedikt J.; Krishnan, Hari; Perciano, Talita; ...

2017-01-31

Background: The ever improving brightness of accelerator based sources is enabling novel observations and discoveries with faster frame rates, larger fields of view, higher resolution, and higher dimensionality. Results: Here we present an integrated software/algorithmic framework designed to capitalize on high-throughput experiments through efficient kernels, load-balanced workflows, which are scalable in design. We describe the streamlined processing pipeline of ptychography data analysis. Conclusions: The pipeline provides throughput, compression, and resolution as well as rapid feedback to the microscope operators.

Improved framework model to allocate optimal rainwater harvesting sites in small watersheds for agro-forestry uses

NASA Astrophysics Data System (ADS)

Terêncio, D. P. S.; Sanches Fernandes, L. F.; Cortes, R. M. V.; Pacheco, F. A. L.

2017-07-01

This study introduces an improved rainwater harvesting (RWH) suitability model to help the implementation of agro-forestry projects (irrigation, wildfire combat) in catchments. The model combines a planning workflow to define suitability of catchments based on physical, socio-economic and ecologic variables, with an allocation workflow to constrain suitable RWH sites as function of project specific features (e.g., distance from rainfall collection to application area). The planning workflow comprises a Multi Criteria Analysis (MCA) implemented on a Geographic Information System (GIS), whereas the allocation workflow is based on a multiple-parameter ranking analysis. When compared to other similar models, improvement comes with the flexible weights of MCA and the entire allocation workflow. The method is tested in a contaminated watershed (the Ave River basin) located in Portugal. The pilot project encompasses the irrigation of a 400 ha crop land that consumes 2.69 Mm3 of water per year. The application of harvested water in the irrigation replaces the use of stream water with excessive anthropogenic nutrients that may raise nitrosamines in the food and accumulation in the food chain, with severe consequences to human health (cancer). The selected rainfall collection catchment is capable to harvest 12 Mm3·yr-1 (≈ 4.5 × the requirement) and is roughly 3 km far from the application area assuring crop irrigation by gravity flow with modest transport costs. The RWH system is an 8-meter high that can be built in earth with reduced costs.

Integrative analysis workflow for the structural and functional classification of C-type lectins

PubMed Central

2011-01-01

Background It is important to understand the roles of C-type lectins in the immune system due to their ubiquity and diverse range of functions in animal cells. It has been observed that currently confirmed C-type lectins share a highly conserved domain known as the C-type carbohydrate recognition domain (CRD). Using the sequence profile of the CRD, an increasing number of putative C-type lectins have been identified. Hence, it is highly needed to develop a systematic framework that enables us to elucidate their carbohydrate (glycan) recognition function, and discover their physiological and pathological roles. Results Presented herein is an integrated workflow for characterizing the sequence and structural features of novel C-type lectins. Our workflow utilizes web-based queries and available software suites to annotate features that can be found on the C-type lectin, given its amino acid sequence. At the same time, it incorporates modeling and analysis of glycans - a major class of ligands that interact with C-type lectins. Thereafter, the results are analyzed together with context-specific knowledge to filter off unlikely predictions. This allows researchers to design their subsequent experiments to confirm the functions of the C-type lectins in a systematic manner. Conclusions The efficacy and usefulness of our proposed immunoinformatics workflow was demonstrated by applying our integrated workflow to a novel C-type lectin -CLEC17A - and we report some of its possible functions that warrants further validation through wet-lab experiments. PMID:22372988

Galaxy tools and workflows for sequence analysis with applications in molecular plant pathology

PubMed Central

Grüning, Björn A.; Paszkiewicz, Konrad; Pritchard, Leighton

2013-01-01

The Galaxy Project offers the popular web browser-based platform Galaxy for running bioinformatics tools and constructing simple workflows. Here, we present a broad collection of additional Galaxy tools for large scale analysis of gene and protein sequences. The motivating research theme is the identification of specific genes of interest in a range of non-model organisms, and our central example is the identification and prediction of “effector” proteins produced by plant pathogens in order to manipulate their host plant. This functional annotation of a pathogen’s predicted capacity for virulence is a key step in translating sequence data into potential applications in plant pathology. This collection includes novel tools, and widely-used third-party tools such as NCBI BLAST+ wrapped for use within Galaxy. Individual bioinformatics software tools are typically available separately as standalone packages, or in online browser-based form. The Galaxy framework enables the user to combine these and other tools to automate organism scale analyses as workflows, without demanding familiarity with command line tools and scripting. Workflows created using Galaxy can be saved and are reusable, so may be distributed within and between research groups, facilitating the construction of a set of standardised, reusable bioinformatic protocols. The Galaxy tools and workflows described in this manuscript are open source and freely available from the Galaxy Tool Shed (http://usegalaxy.org/toolshed or http://toolshed.g2.bx.psu.edu). PMID:24109552

A Hybrid Task Graph Scheduler for High Performance Image Processing Workflows.

PubMed

Blattner, Timothy; Keyrouz, Walid; Bhattacharyya, Shuvra S; Halem, Milton; Brady, Mary

2017-12-01

Designing applications for scalability is key to improving their performance in hybrid and cluster computing. Scheduling code to utilize parallelism is difficult, particularly when dealing with data dependencies, memory management, data motion, and processor occupancy. The Hybrid Task Graph Scheduler (HTGS) improves programmer productivity when implementing hybrid workflows for multi-core and multi-GPU systems. The Hybrid Task Graph Scheduler (HTGS) is an abstract execution model, framework, and API that increases programmer productivity when implementing hybrid workflows for such systems. HTGS manages dependencies between tasks, represents CPU and GPU memories independently, overlaps computations with disk I/O and memory transfers, keeps multiple GPUs occupied, and uses all available compute resources. Through these abstractions, data motion and memory are explicit; this makes data locality decisions more accessible. To demonstrate the HTGS application program interface (API), we present implementations of two example algorithms: (1) a matrix multiplication that shows how easily task graphs can be used; and (2) a hybrid implementation of microscopy image stitching that reduces code size by ≈ 43% compared to a manually coded hybrid workflow implementation and showcases the minimal overhead of task graphs in HTGS. Both of the HTGS-based implementations show good performance. In image stitching the HTGS implementation achieves similar performance to the hybrid workflow implementation. Matrix multiplication with HTGS achieves 1.3× and 1.8× speedup over the multi-threaded OpenBLAS library for 16k × 16k and 32k × 32k size matrices, respectively.

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

Pugmire, David; Kress, James; Choi, Jong

Data driven science is becoming increasingly more common, complex, and is placing tremendous stresses on visualization and analysis frameworks. Data sources producing 10GB per second (and more) are becoming increasingly commonplace in both simulation, sensor and experimental sciences. These data sources, which are often distributed around the world, must be analyzed by teams of scientists that are also distributed. Enabling scientists to view, query and interact with such large volumes of data in near-real-time requires a rich fusion of visualization and analysis techniques, middleware and workflow systems. Here, this paper discusses initial research into visualization and analysis of distributed datamore » workflows that enables scientists to make near-real-time decisions of large volumes of time varying data.« less

Developing a workflow to identify inconsistencies in volunteered geographic information: a phenological case study

USGS Publications Warehouse

Mehdipoor, Hamed; Zurita-Milla, Raul; Rosemartin, Alyssa; Gerst, Katharine L.; Weltzin, Jake F.

2015-01-01

Recent improvements in online information communication and mobile location-aware technologies have led to the production of large volumes of volunteered geographic information. Widespread, large-scale efforts by volunteers to collect data can inform and drive scientific advances in diverse fields, including ecology and climatology. Traditional workflows to check the quality of such volunteered information can be costly and time consuming as they heavily rely on human interventions. However, identifying factors that can influence data quality, such as inconsistency, is crucial when these data are used in modeling and decision-making frameworks. Recently developed workflows use simple statistical approaches that assume that the majority of the information is consistent. However, this assumption is not generalizable, and ignores underlying geographic and environmental contextual variability that may explain apparent inconsistencies. Here we describe an automated workflow to check inconsistency based on the availability of contextual environmental information for sampling locations. The workflow consists of three steps: (1) dimensionality reduction to facilitate further analysis and interpretation of results, (2) model-based clustering to group observations according to their contextual conditions, and (3) identification of inconsistent observations within each cluster. The workflow was applied to volunteered observations of flowering in common and cloned lilac plants (Syringa vulgaris and Syringa x chinensis) in the United States for the period 1980 to 2013. About 97% of the observations for both common and cloned lilacs were flagged as consistent, indicating that volunteers provided reliable information for this case study. Relative to the original dataset, the exclusion of inconsistent observations changed the apparent rate of change in lilac bloom dates by two days per decade, indicating the importance of inconsistency checking as a key step in data quality assessment for volunteered geographic information. Initiatives that leverage volunteered geographic information can adapt this workflow to improve the quality of their datasets and the robustness of their scientific analyses.

A Drupal-Based Collaborative Framework for Science Workflows

NASA Astrophysics Data System (ADS)

Pinheiro da Silva, P.; Gandara, A.

2010-12-01

Cyber-infrastructure is built from utilizing technical infrastructure to support organizational practices and social norms to provide support for scientific teams working together or dependent on each other to conduct scientific research. Such cyber-infrastructure enables the sharing of information and data so that scientists can leverage knowledge and expertise through automation. Scientific workflow systems have been used to build automated scientific systems used by scientists to conduct scientific research and, as a result, create artifacts in support of scientific discoveries. These complex systems are often developed by teams of scientists who are located in different places, e.g., scientists working in distinct buildings, and sometimes in different time zones, e.g., scientist working in distinct national laboratories. The sharing of these specifications is currently supported by the use of version control systems such as CVS or Subversion. Discussions about the design, improvement, and testing of these specifications, however, often happen elsewhere, e.g., through the exchange of email messages and IM chatting. Carrying on a discussion about these specifications is challenging because comments and specifications are not necessarily connected. For instance, the person reading a comment about a given workflow specification may not be able to see the workflow and even if the person can see the workflow, the person may not specifically know to which part of the workflow a given comments applies to. In this paper, we discuss the design, implementation and use of CI-Server, a Drupal-based infrastructure, to support the collaboration of both local and distributed teams of scientists using scientific workflows. CI-Server has three primary goals: to enable information sharing by providing tools that scientists can use within their scientific research to process data, publish and share artifacts; to build community by providing tools that support discussions between scientists about artifacts used or created through scientific processes; and to leverage the knowledge collected within the artifacts and scientific collaborations to support scientific discoveries.

DIaaS: Data-Intensive workflows as a service - Enabling easy composition and deployment of data-intensive workflows on Virtual Research Environments

NASA Astrophysics Data System (ADS)

Filgueira, R.; Ferreira da Silva, R.; Deelman, E.; Atkinson, M.

2016-12-01

We present the Data-Intensive workflows as a Service (DIaaS) model for enabling easy data-intensive workflow composition and deployment on clouds using containers. DIaaS model backbone is Asterism, an integrated solution for running data-intensive stream-based applications on heterogeneous systems, which combines the benefits of dispel4py with Pegasus workflow systems. The stream-based executions of an Asterism workflow are managed by dispel4py, while the data movement between different e-Infrastructures, and the coordination of the application execution are automatically managed by Pegasus. DIaaS combines Asterism framework with Docker containers to provide an integrated, complete, easy-to-use, portable approach to run data-intensive workflows on distributed platforms. Three containers integrate the DIaaS model: a Pegasus node, and an MPI and an Apache Storm clusters. Container images are described as Dockerfiles (available online at http://github.com/dispel4py/pegasus_dispel4py), linked to Docker Hub for providing continuous integration (automated image builds), and image storing and sharing. In this model, all required software (workflow systems and execution engines) for running scientific applications are packed into the containers, which significantly reduces the effort (and possible human errors) required by scientists or VRE administrators to build such systems. The most common use of DIaaS will be to act as a backend of VREs or Scientific Gateways to run data-intensive applications, deploying cloud resources upon request. We have demonstrated the feasibility of DIaaS using the data-intensive seismic ambient noise cross-correlation application (Figure 1). The application preprocesses (Phase1) and cross-correlates (Phase2) traces from several seismic stations. The application is submitted via Pegasus (Container1), and Phase1 and Phase2 are executed in the MPI (Container2) and Storm (Container3) clusters respectively. Although both phases could be executed within the same environment, this setup demonstrates the flexibility of DIaaS to run applications across e-Infrastructures. In summary, DIaaS delivers specialized software to execute data-intensive applications in a scalable, efficient, and robust manner reducing the engineering time and computational cost.

Optimizing CyberShake Seismic Hazard Workflows for Large HPC Resources

NASA Astrophysics Data System (ADS)

Callaghan, S.; Maechling, P. J.; Juve, G.; Vahi, K.; Deelman, E.; Jordan, T. H.

2014-12-01

The CyberShake computational platform is a well-integrated collection of scientific software and middleware that calculates 3D simulation-based probabilistic seismic hazard curves and hazard maps for the Los Angeles region. Currently each CyberShake model comprises about 235 million synthetic seismograms from about 415,000 rupture variations computed at 286 sites. CyberShake integrates large-scale parallel and high-throughput serial seismological research codes into a processing framework in which early stages produce files used as inputs by later stages. Scientific workflow tools are used to manage the jobs, data, and metadata. The Southern California Earthquake Center (SCEC) developed the CyberShake platform using USC High Performance Computing and Communications systems and open-science NSF resources.CyberShake calculations were migrated to the NSF Track 1 system NCSA Blue Waters when it became operational in 2013, via an interdisciplinary team approach including domain scientists, computer scientists, and middleware developers. Due to the excellent performance of Blue Waters and CyberShake software optimizations, we reduced the makespan (a measure of wallclock time-to-solution) of a CyberShake study from 1467 to 342 hours. We will describe the technical enhancements behind this improvement, including judicious introduction of new GPU software, improved scientific software components, increased workflow-based automation, and Blue Waters-specific workflow optimizations.Our CyberShake performance improvements highlight the benefits of scientific workflow tools. The CyberShake workflow software stack includes the Pegasus Workflow Management System (Pegasus-WMS, which includes Condor DAGMan), HTCondor, and Globus GRAM, with Pegasus-mpi-cluster managing the high-throughput tasks on the HPC resources. The workflow tools handle data management, automatically transferring about 13 TB back to SCEC storage.We will present performance metrics from the most recent CyberShake study, executed on Blue Waters. We will compare the performance of CPU and GPU versions of our large-scale parallel wave propagation code, AWP-ODC-SGT. Finally, we will discuss how these enhancements have enabled SCEC to move forward with plans to increase the CyberShake simulation frequency to 1.0 Hz.

Justification of automated decision-making: medical explanations as medical arguments.

PubMed Central

Shankar, R. D.; Musen, M. A.

1999-01-01

People use arguments to justify their claims. Computer systems use explanations to justify their conclusions. We are developing WOZ, an explanation framework that justifies the conclusions of a clinical decision-support system. WOZ's central component is the explanation strategy that decides what information justifies a claim. The strategy uses Toulmin's argument structure to define pieces of information and to orchestrate their presentation. WOZ uses explicit models that abstract the core aspects of the framework such as the explanation strategy. In this paper, we present the use of arguments, the modeling of explanations, and the explanation process used in WOZ. WOZ exploits the wealth of naturally occurring arguments, and thus can generate convincing medical explanations. Images Figure 5 PMID:10566388

GUEST EDITOR'S INTRODUCTION: Guest Editor's introduction

NASA Astrophysics Data System (ADS)

Chrysanthis, Panos K.

1996-12-01

Computer Science Department, University of Pittsburgh, Pittsburgh, PA 15260, USA This special issue focuses on current efforts to represent and support workflows that integrate information systems and human resources within a business or manufacturing enterprise. Workflows may also be viewed as an emerging computational paradigm for effective structuring of cooperative applications involving human users and access to diverse data types not necessarily maintained by traditional database management systems. A workflow is an automated organizational process (also called business process) which consists of a set of activities or tasks that need to be executed in a particular controlled order over a combination of heterogeneous database systems and legacy systems. Within workflows, tasks are performed cooperatively by either human or computational agents in accordance with their roles in the organizational hierarchy. The challenge in facilitating the implementation of workflows lies in developing efficient workflow management systems. A workflow management system (also called workflow server, workflow engine or workflow enactment system) provides the necessary interfaces for coordination and communication among human and computational agents to execute the tasks involved in a workflow and controls the execution orderings of tasks as well as the flow of data that these tasks manipulate. That is, the workflow management system is responsible for correctly and reliably supporting the specification, execution, and monitoring of workflows. The six papers selected (out of the twenty-seven submitted for this special issue of Distributed Systems Engineering) address different aspects of these three functional components of a workflow management system. In the first paper, `Correctness issues in workflow management', Kamath and Ramamritham discuss the important issue of correctness in workflow management that constitutes a prerequisite for the use of workflows in the automation of the critical organizational/business processes. In particular, this paper examines the issues of execution atomicity and failure atomicity, differentiating between correctness requirements of system failures and logical failures, and surveys techniques that can be used to ensure data consistency in workflow management systems. While the first paper is concerned with correctness assuming transactional workflows in which selective transactional properties are associated with individual tasks or the entire workflow, the second paper, `Scheduling workflows by enforcing intertask dependencies' by Attie et al, assumes that the tasks can be either transactions or other activities involving legacy systems. This second paper describes the modelling and specification of conditions involving events and dependencies among tasks within a workflow using temporal logic and finite state automata. It also presents a scheduling algorithm that enforces all stated dependencies by executing at any given time only those events that are allowed by all the dependency automata and in an order as specified by the dependencies. In any system with decentralized control, there is a need to effectively cope with the tension that exists between autonomy and consistency requirements. In `A three-level atomicity model for decentralized workflow management systems', Ben-Shaul and Heineman focus on the specific requirement of enforcing failure atomicity in decentralized, autonomous and interacting workflow management systems. Their paper describes a model in which each workflow manager must be able to specify the sequence of tasks that comprise an atomic unit for the purposes of correctness, and the degrees of local and global atomicity for the purpose of cooperation with other workflow managers. The paper also discusses a realization of this model in which treaties and summits provide an agreement mechanism, while underlying transaction managers are responsible for maintaining failure atomicity. The fourth and fifth papers are experience papers describing a workflow management system and a large scale workflow application, respectively. Schill and Mittasch, in `Workflow management systems on top of OSF DCE and OMG CORBA', describe a decentralized workflow management system and discuss its implementation using two standardized middleware platforms, namely, OSF DCE and OMG CORBA. The system supports a new approach to workflow management, introducing several new concepts such as data type management for integrating various types of data and quality of service for various services provided by servers. A problem common to both database applications and workflows is the handling of missing and incomplete information. This is particularly pervasive in an `electronic market' with a huge number of retail outlets producing and exchanging volumes of data, the application discussed in `Information flow in the DAMA project beyond database managers: information flow managers'. Motivated by the need for a method that allows a task to proceed in a timely manner if not all data produced by other tasks are available by its deadline, Russell et al propose an architectural framework and a language that can be used to detect, approximate and, later on, to adjust missing data if necessary. The final paper, `The evolution towards flexible workflow systems' by Nutt, is complementary to the other papers and is a survey of issues and of work related to both workflow and computer supported collaborative work (CSCW) areas. In particular, the paper provides a model and a categorization of the dimensions which workflow management and CSCW systems share. Besides summarizing the recent advancements towards efficient workflow management, the papers in this special issue suggest areas open to investigation and it is our hope that they will also provide the stimulus for further research and development in the area of workflow management systems.

Standards to support information systems integration in anatomic pathology.

PubMed

Daniel, Christel; García Rojo, Marcial; Bourquard, Karima; Henin, Dominique; Schrader, Thomas; Della Mea, Vincenzo; Gilbertson, John; Beckwith, Bruce A

2009-11-01

Integrating anatomic pathology information- text and images-into electronic health care records is a key challenge for enhancing clinical information exchange between anatomic pathologists and clinicians. The aim of the Integrating the Healthcare Enterprise (IHE) international initiative is precisely to ensure interoperability of clinical information systems by using existing widespread industry standards such as Digital Imaging and Communication in Medicine (DICOM) and Health Level Seven (HL7). To define standard-based informatics transactions to integrate anatomic pathology information to the Healthcare Enterprise. We used the methodology of the IHE initiative. Working groups from IHE, HL7, and DICOM, with special interest in anatomic pathology, defined consensual technical solutions to provide end-users with improved access to consistent information across multiple information systems. The IHE anatomic pathology technical framework describes a first integration profile, "Anatomic Pathology Workflow," dedicated to the diagnostic process including basic image acquisition and reporting solutions. This integration profile relies on 10 transactions based on HL7 or DICOM standards. A common specimen model was defined to consistently identify and describe specimens in both HL7 and DICOM transactions. The IHE anatomic pathology working group has defined standard-based informatics transactions to support the basic diagnostic workflow in anatomic pathology laboratories. In further stages, the technical framework will be completed to manage whole-slide images and semantically rich structured reports in the diagnostic workflow and to integrate systems used for patient care and those used for research activities (such as tissue bank databases or tissue microarrayers).

An intelligent service matching method for mechanical equipment condition monitoring using the fibre Bragg grating sensor network

NASA Astrophysics Data System (ADS)

Zhang, Fan; Zhou, Zude; Liu, Quan; Xu, Wenjun

2017-02-01

Due to the advantages of being able to function under harsh environmental conditions and serving as a distributed condition information source in a networked monitoring system, the fibre Bragg grating (FBG) sensor network has attracted considerable attention for equipment online condition monitoring. To provide an overall conditional view of the mechanical equipment operation, a networked service-oriented condition monitoring framework based on FBG sensing is proposed, together with an intelligent matching method for supporting monitoring service management. In the novel framework, three classes of progressive service matching approaches, including service-chain knowledge database service matching, multi-objective constrained service matching and workflow-driven human-interactive service matching, are developed and integrated with an enhanced particle swarm optimisation (PSO) algorithm as well as a workflow-driven mechanism. Moreover, the manufacturing domain ontology, FBG sensor network structure and monitoring object are considered to facilitate the automatic matching of condition monitoring services to overcome the limitations of traditional service processing methods. The experimental results demonstrate that FBG monitoring services can be selected intelligently, and the developed condition monitoring system can be re-built rapidly as new equipment joins the framework. The effectiveness of the service matching method is also verified by implementing a prototype system together with its performance analysis.

A research and experimentation framework for exploiting VoI-based methods within analyst workflows in tactical operation centers

NASA Astrophysics Data System (ADS)

Sadler, Laurel

2017-05-01

In today's battlefield environments, analysts are inundated with real-time data received from the tactical edge that must be evaluated and used for managing and modifying current missions as well as planning for future missions. This paper describes a framework that facilitates a Value of Information (VoI) based data analytics tool for information object (IO) analysis in a tactical and command and control (C2) environment, which reduces analyst work load by providing automated or analyst assisted applications. It allows the analyst to adjust parameters for data matching of the IOs that will be received and provides agents for further filtering or fusing of the incoming data. It allows for analyst enhancement and markup to be made to and/or comments to be attached to the incoming IOs, which can then be re-disseminated utilizing the VoI based dissemination service. The analyst may also adjust the underlying parameters before re-dissemination of an IO, which will subsequently adjust the value of the IO based on this new/additional information that has been added, possibly increasing the value from the original. The framework is flexible and extendable, providing an easy to use, dynamically changing Command and Control decision aid that focuses and enhances the analyst workflow.

Talkoot Portals: Discover, Tag, Share, and Reuse Collaborative Science Workflows (Invited)

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Ramachandran, R.; Lynnes, C.

2009-12-01

A small but growing number of scientists are beginning to harness Web 2.0 technologies, such as wikis, blogs, and social tagging, as a transformative way of doing science. These technologies provide researchers easy mechanisms to critique, suggest and share ideas, data and algorithms. At the same time, large suites of algorithms for science analysis are being made available as remotely-invokable Web Services, which can be chained together to create analysis workflows. This provides the research community an unprecedented opportunity to collaborate by sharing their workflows with one another, reproducing and analyzing research results, and leveraging colleagues’ expertise to expedite the process of scientific discovery. However, wikis and similar technologies are limited to text, static images and hyperlinks, providing little support for collaborative data analysis. A team of information technology and Earth science researchers from multiple institutions have come together to improve community collaboration in science analysis by developing a customizable “software appliance” to build collaborative portals for Earth Science services and analysis workflows. The critical requirement is that researchers (not just information technologists) be able to build collaborative sites around service workflows within a few hours. We envision online communities coming together, much like Finnish “talkoot” (a barn raising), to build a shared research space. Talkoot extends a freely available, open source content management framework with a series of modules specific to Earth Science for registering, creating, managing, discovering, tagging and sharing Earth Science web services and workflows for science data processing, analysis and visualization. Users will be able to author a “science story” in shareable web notebooks, including plots or animations, backed up by an executable workflow that directly reproduces the science analysis. New services and workflows of interest will be discoverable using tag search, and advertised using “service casts” and “interest casts” (Atom feeds). Multiple science workflow systems will be plugged into the system, with initial support for UAH’s Mining Workflow Composer and the open-source Active BPEL engine, and JPL’s SciFlo engine and the VizFlow visual programming interface. With the ability to share and execute analysis workflows, Talkoot portals can be used to do collaborative science in addition to communicate ideas and results. It will be useful for different science domains, mission teams, research projects and organizations. Thus, it will help to solve the “sociological” problem of bringing together disparate groups of researchers, and the technical problem of advertising, discovering, developing, documenting, and maintaining inter-agency science workflows. The presentation will discuss the goals of and barriers to Science 2.0, the social web technologies employed in the Talkoot software appliance (e.g. CMS, social tagging, personal presence, advertising by feeds, etc.), illustrate the resulting collaborative capabilities, and show early prototypes of the web interfaces (e.g. embedded workflows).

A Web application for the management of clinical workflow in image-guided and adaptive proton therapy for prostate cancer treatments.

PubMed

Yeung, Daniel; Boes, Peter; Ho, Meng Wei; Li, Zuofeng

2015-05-08

Image-guided radiotherapy (IGRT), based on radiopaque markers placed in the prostate gland, was used for proton therapy of prostate patients. Orthogonal X-rays and the IBA Digital Image Positioning System (DIPS) were used for setup correction prior to treatment and were repeated after treatment delivery. Following a rationale for margin estimates similar to that of van Herk,(1) the daily post-treatment DIPS data were analyzed to determine if an adaptive radiotherapy plan was necessary. A Web application using ASP.NET MVC5, Entity Framework, and an SQL database was designed to automate this process. The designed features included state-of-the-art Web technologies, a domain model closely matching the workflow, a database-supporting concurrency and data mining, access to the DIPS database, secured user access and roles management, and graphing and analysis tools. The Model-View-Controller (MVC) paradigm allowed clean domain logic, unit testing, and extensibility. Client-side technologies, such as jQuery, jQuery Plug-ins, and Ajax, were adopted to achieve a rich user environment and fast response. Data models included patients, staff, treatment fields and records, correction vectors, DIPS images, and association logics. Data entry, analysis, workflow logics, and notifications were implemented. The system effectively modeled the clinical workflow and IGRT process.

Provenance for Runtime Workflow Steering and Validation in Computational Seismology

NASA Astrophysics Data System (ADS)

Spinuso, A.; Krischer, L.; Krause, A.; Filgueira, R.; Magnoni, F.; Muraleedharan, V.; David, M.

2014-12-01

Provenance systems may be offered by modern workflow engines to collect metadata about the data transformations at runtime. If combined with effective visualisation and monitoring interfaces, these provenance recordings can speed up the validation process of an experiment, suggesting interactive or automated interventions with immediate effects on the lifecycle of a workflow run. For instance, in the field of computational seismology, if we consider research applications performing long lasting cross correlation analysis and high resolution simulations, the immediate notification of logical errors and the rapid access to intermediate results, can produce reactions which foster a more efficient progress of the research. These applications are often executed in secured and sophisticated HPC and HTC infrastructures, highlighting the need for a comprehensive framework that facilitates the extraction of fine grained provenance and the development of provenance aware components, leveraging the scalability characteristics of the adopted workflow engines, whose enactment can be mapped to different technologies (MPI, Storm clusters, etc). This work looks at the adoption of W3C-PROV concepts and data model within a user driven processing and validation framework for seismic data, supporting also computational and data management steering. Validation needs to balance automation with user intervention, considering the scientist as part of the archiving process. Therefore, the provenance data is enriched with community-specific metadata vocabularies and control messages, making an experiment reproducible and its description consistent with the community understandings. Moreover, it can contain user defined terms and annotations. The current implementation of the system is supported by the EU-Funded VERCE (http://verce.eu). It provides, as well as the provenance generation mechanisms, a prototypal browser-based user interface and a web API built on top of a NoSQL storage technology, experimenting ways to ensure a rapid and flexible access to the lineage traces. It supports the users with the visualisation of graphical products and offers combined operations to access and download the data which may be selectively stored at runtime, into dedicated data archives.

BP-Broker use-cases in the UncertWeb framework

NASA Astrophysics Data System (ADS)

Roncella, Roberto; Bigagli, Lorenzo; Schulz, Michael; Stasch, Christoph; Proß, Benjamin; Jones, Richard; Santoro, Mattia

2013-04-01

The UncertWeb framework is a distributed, Web-based Information and Communication Technology (ICT) system to support scientific data modeling in presence of uncertainty. We designed and prototyped a core component of the UncertWeb framework: the Business Process Broker. The BP-Broker implements several functionalities, such as: discovery of available processes/BPs, preprocessing of a BP into its executable form (EBP), publication of EBPs and their execution through a workflow-engine. According to the Composition-as-a-Service (CaaS) approach, the BP-Broker supports discovery and chaining of modeling resources (and processing resources in general), providing the necessary interoperability services for creating, validating, editing, storing, publishing, and executing scientific workflows. The UncertWeb project targeted several scenarios, which were used to evaluate and test the BP-Broker. The scenarios cover the following environmental application domains: biodiversity and habitat change, land use and policy modeling, local air quality forecasting, and individual activity in the environment. This work reports on the study of a number of use-cases, by means of the BP-Broker, namely: - eHabitat use-case: implements a Monte Carlo simulation performed on a deterministic ecological model; an extended use-case supports inter-comparison of model outputs; - FERA use-case: is composed of a set of models for predicting land-use and crop yield response to climatic and economic change; - NILU use-case: is composed of a Probabilistic Air Quality Forecasting model for predicting concentrations of air pollutants; - Albatross use-case: includes two model services for simulating activity-travel patterns of individuals in time and space; - Overlay use-case: integrates the NILU scenario with the Albatross scenario to calculate the exposure to air pollutants of individuals. Our aim was to prove the feasibility of describing composite modeling processes with a high-level, abstract notation (i.e. BPMN 2.0), and delegating the resolution of technical issues (e.g. I/O matching) as much as possible to an external service. The results of the experimented solution indicate that this approach facilitates the integration of environmental model workflows into the standard geospatial Web Services framework (e.g. the GEOSS Common Infrastructure), mitigating its inherent complexity. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement n° 248488.

REACTOR - a Concept for establishing a System-of-Systems

NASA Astrophysics Data System (ADS)

Haener, Rainer; Hammitzsch, Martin; Wächter, Joachim

2014-05-01

REACTOR is a working title for activities implementing reliable, emergent, adaptive, and concurrent collaboration on the basis of transactional object repositories. It aims at establishing federations of autonomous yet interoperable systems (Systems-of-Systems), which are able to expose emergent behaviour. Following the principles of event-driven service-oriented architectures (SOA 2.0), REACTOR enables adaptive re-organisation by dynamic delegation of responsibilities and novel yet coherent monitoring strategies by combining information from different domains. Thus it allows collaborative decision-processes across system, discipline, and administrative boundaries. Interoperability is based on two approaches that implement interconnection and communication between existing heterogeneous infrastructures and information systems: Coordinated (orchestration-based) communication and publish/subscribe (choreography-based) communication. Choreography-based communication ensures the autonomy of the participating systems to the highest possible degree but requires the implementation of adapters, which provide functional access to information (publishing/consuming events) via a Message Oriented Middleware (MOM). Any interconnection of the systems (composition of service and message cascades) is established on the basis of global conversations that are enacted by choreographies specifying the expected behaviour of the participating systems with respect to agreed Service Level Agreements (SLA) required by e.g. national authorities. The specification of conversations, maintained in commonly available repositories also enables the utilisation of systems for purposes (evolving) other than initially intended. Orchestration-based communication additionally requires a central component that controls the information transfer via service requests or event processing and also takes responsibility of managing business processes. Commonly available transactional object repositories are well suited to establish brokers, which mediate metadata and semantic information about the resources of all involved systems. This concept has been developed within the project Collaborative, Complex, and Critical Decision-Support in Evolving Crises (TRIDEC) on the basis of semantic registries describing all facets of events and services utilisable for crisis management systems. The implementation utilises an operative infrastructure including an Enterprise Service Bus (ESB), adapters to proprietary sensor systems, a workflow engine, and a broker-based MOM. It also applies current technologies like actor-based frameworks for highly concurrent, distributed, and fault tolerant event-driven applications. Therefore REACTOR implementations are well suited to be hosted in a cloud that provides Infrastructure as a Service (IaaS). To provide low entry barriers for legacy and future systems, REACTOR adapts the principles of Design by Contract (DbC) as well as standardised and common information models like the Sensor Web Enablement (SWE) or the JavaScript Object Notation for geographic features (GeoJSON). REACTOR has been applied exemplarily within two different scenarios, Natural Crisis Management and Industrial Subsurface Development.

A BPMN solution for chaining OGC services to quality assure location-based crowdsourced data

NASA Astrophysics Data System (ADS)

Meek, Sam; Jackson, Mike; Leibovici, Didier G.

2016-02-01

The Open Geospatial Consortium (OGC) Web Processing Service (WPS) standard enables access to a centralized repository of processes and services from compliant clients. A crucial part of the standard includes the provision to chain disparate processes and services to form a reusable workflow. To date this has been realized by methods such as embedding XML requests, using Business Process Execution Language (BPEL) engines and other external orchestration engines. Although these allow the user to define tasks and data artifacts as web services, they are often considered inflexible and complicated, often due to vendor specific solutions and inaccessible documentation. This paper introduces a new method of flexible service chaining using the standard Business Process Markup Notation (BPMN). A prototype system has been developed upon an existing open source BPMN suite to illustrate the advantages of the approach. The motivation for the software design is qualification of crowdsourced data for use in policy-making. The software is tested as part of a project that seeks to qualify, assure, and add value to crowdsourced data in a biological monitoring use case.

A framework for interactive visual analysis of heterogeneous marine data in an integrated problem solving environment

NASA Astrophysics Data System (ADS)

Liu, Shuai; Chen, Ge; Yao, Shifeng; Tian, Fenglin; Liu, Wei

2017-07-01

This paper presents a novel integrated marine visualization framework which focuses on processing, analyzing the multi-dimension spatiotemporal marine data in one workflow. Effective marine data visualization is needed in terms of extracting useful patterns, recognizing changes, and understanding physical processes in oceanography researches. However, the multi-source, multi-format, multi-dimension characteristics of marine data pose a challenge for interactive and feasible (timely) marine data analysis and visualization in one workflow. And, global multi-resolution virtual terrain environment is also needed to give oceanographers and the public a real geographic background reference and to help them to identify the geographical variation of ocean phenomena. This paper introduces a data integration and processing method to efficiently visualize and analyze the heterogeneous marine data. Based on the data we processed, several GPU-based visualization methods are explored to interactively demonstrate marine data. GPU-tessellated global terrain rendering using ETOPO1 data is realized and the video memory usage is controlled to ensure high efficiency. A modified ray-casting algorithm for the uneven multi-section Argo volume data is also presented and the transfer function is designed to analyze the 3D structure of ocean phenomena. Based on the framework we designed, an integrated visualization system is realized. The effectiveness and efficiency of the framework is demonstrated. This system is expected to make a significant contribution to the demonstration and understanding of marine physical process in a virtual global environment.

Automated model optimisation using the Cylc workflow engine (Cyclops v1.0)

NASA Astrophysics Data System (ADS)

Gorman, Richard M.; Oliver, Hilary J.

2018-06-01

Most geophysical models include many parameters that are not fully determined by theory, and can be tuned to improve the model's agreement with available data. We might attempt to automate this tuning process in an objective way by employing an optimisation algorithm to find the set of parameters that minimises a cost function derived from comparing model outputs with measurements. A number of algorithms are available for solving optimisation problems, in various programming languages, but interfacing such software to a complex geophysical model simulation presents certain challenges. To tackle this problem, we have developed an optimisation suite (Cyclops) based on the Cylc workflow engine that implements a wide selection of optimisation algorithms from the NLopt Python toolbox (Johnson, 2014). The Cyclops optimisation suite can be used to calibrate any modelling system that has itself been implemented as a (separate) Cylc model suite, provided it includes computation and output of the desired scalar cost function. A growing number of institutions are using Cylc to orchestrate complex distributed suites of interdependent cycling tasks within their operational forecast systems, and in such cases application of the optimisation suite is particularly straightforward. As a test case, we applied the Cyclops to calibrate a global implementation of the WAVEWATCH III (v4.18) third-generation spectral wave model, forced by ERA-Interim input fields. This was calibrated over a 1-year period (1997), before applying the calibrated model to a full (1979-2016) wave hindcast. The chosen error metric was the spatial average of the root mean square error of hindcast significant wave height compared with collocated altimeter records. We describe the results of a calibration in which up to 19 parameters were optimised.

Integrated reservoir characterization for unconventional reservoirs using seismic, microseismic and well log data

NASA Astrophysics Data System (ADS)

Maity, Debotyam

This study is aimed at an improved understanding of unconventional reservoirs which include tight reservoirs (such as shale oil and gas plays), geothermal developments, etc. We provide a framework for improved fracture zone identification and mapping of the subsurface for a geothermal system by integrating data from different sources. The proposed ideas and methods were tested primarily on data obtained from North Brawley geothermal field and the Geysers geothermal field apart from synthetic datasets which were used to test new algorithms before actual application on the real datasets. The study has resulted in novel or improved algorithms for use at specific stages of data acquisition and analysis including improved phase detection technique for passive seismic (and teleseismic) data as well as optimization of passive seismic surveys for best possible processing results. The proposed workflow makes use of novel integration methods as a means of making best use of the available geophysical data for fracture characterization. The methodology incorporates soft computing tools such as hybrid neural networks (neuro-evolutionary algorithms) as well as geostatistical simulation techniques to improve the property estimates as well as overall characterization efficacy. The basic elements of the proposed characterization workflow involves using seismic and microseismic data to characterize structural and geomechanical features within the subsurface. We use passive seismic data to model geomechanical properties which are combined with other properties evaluated from seismic and well logs to derive both qualitative and quantitative fracture zone identifiers. The study has resulted in a broad framework highlighting a new technique for utilizing geophysical data (seismic and microseismic) for unconventional reservoir characterization. It provides an opportunity to optimally develop the resources in question by incorporating data from different sources and using their temporal and spatial variability as a means to better understand the reservoir behavior. As part of this study, we have developed the following elements which are discussed in the subsequent chapters: 1. An integrated characterization framework for unconventional settings with adaptable workflows for all stages of data processing, interpretation and analysis. 2. A novel autopicking workflow for noisy passive seismic data used for improved accuracy in event picking as well as for improved velocity model building. 3. Improved passive seismic survey design optimization framework for better data collection and improved property estimation. 4. Extensive post-stack seismic attribute studies incorporating robust schemes applicable in complex reservoir settings. 5. Uncertainty quantification and analysis to better quantify property estimates over and above the qualitative interpretations made and to validate observations independently with quantified uncertainties to prevent erroneous interpretations. 6. Property mapping from microseismic data including stress and anisotropic weakness estimates for integrated reservoir characterization and analysis. 7. Integration of results (seismic, microseismic and well logs) from analysis of individual data sets for integrated interpretation using predefined integration framework and soft computing tools.

The Artist and Architect: Creativity and Innovation through Role-Based Design

ERIC Educational Resources Information Center

Miller, Charles; Hokanson, Brad

2009-01-01

This article is the second installment in a four-part "Educational Technology" series exploring a contemporary perspective on the process of instructional design. In this article, the authors reintroduce the framework of Role-Based Design (RBD) and describe practical strategies for its integration into design workflow. Next, they examine their…

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

Bush, Brian W; Brunhart-Lupo, Nicholas J; Gruchalla, Kenny M

This brochure describes a system dynamics simulation (SD) framework that supports an end-to-end analysis workflow that is optimized for deployment on ESIF facilities(Peregrine and the Insight Center). It includes (I) parallel and distributed simulation of SD models, (ii) real-time 3D visualization of running simulations, and (iii) comprehensive database-oriented persistence of simulation metadata, inputs, and outputs.

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

Bush, Brian W; Brunhart-Lupo, Nicholas J; Gruchalla, Kenny M

This presentation describes a system dynamics simulation (SD) framework that supports an end-to-end analysis workflow that is optimized for deployment on ESIF facilities(Peregrine and the Insight Center). It includes (I) parallel and distributed simulation of SD models, (ii) real-time 3D visualization of running simulations, and (iii) comprehensive database-oriented persistence of simulation metadata, inputs, and outputs.

Inventory-based landscape-scale simulation of management effectiveness and economic feasibility with BioSum

Treesearch

Jeremy S. Fried; Larry D. Potts; Sara M. Loreno; Glenn A. Christensen; R. Jamie Barbour

2017-01-01

The Forest Inventory and Analysis (FIA)-based BioSum (Bioregional Inventory Originated Simulation Under Management) is a free policy analysis framework and workflow management software solution. It addresses complex management questions concerning forest health and vulnerability for large, multimillion acre, multiowner landscapes using FIA plot data as the initial...

Extending the NIF DISCO framework to automate complex workflow: coordinating the harvest and integration of data from diverse neuroscience information resources

PubMed Central

Marenco, Luis N.; Wang, Rixin; Bandrowski, Anita E.; Grethe, Jeffrey S.; Shepherd, Gordon M.; Miller, Perry L.

2014-01-01

This paper describes how DISCO, the data aggregator that supports the Neuroscience Information Framework (NIF), has been extended to play a central role in automating the complex workflow required to support and coordinate the NIF’s data integration capabilities. The NIF is an NIH Neuroscience Blueprint initiative designed to help researchers access the wealth of data related to the neurosciences available via the Internet. A central component is the NIF Federation, a searchable database that currently contains data from 231 data and information resources regularly harvested, updated, and warehoused in the DISCO system. In the past several years, DISCO has greatly extended its functionality and has evolved to play a central role in automating the complex, ongoing process of harvesting, validating, integrating, and displaying neuroscience data from a growing set of participating resources. This paper provides an overview of DISCO’s current capabilities and discusses a number of the challenges and future directions related to the process of coordinating the integration of neuroscience data within the NIF Federation. PMID:25018728

Extending the NIF DISCO framework to automate complex workflow: coordinating the harvest and integration of data from diverse neuroscience information resources.

PubMed

Marenco, Luis N; Wang, Rixin; Bandrowski, Anita E; Grethe, Jeffrey S; Shepherd, Gordon M; Miller, Perry L

2014-01-01

This paper describes how DISCO, the data aggregator that supports the Neuroscience Information Framework (NIF), has been extended to play a central role in automating the complex workflow required to support and coordinate the NIF's data integration capabilities. The NIF is an NIH Neuroscience Blueprint initiative designed to help researchers access the wealth of data related to the neurosciences available via the Internet. A central component is the NIF Federation, a searchable database that currently contains data from 231 data and information resources regularly harvested, updated, and warehoused in the DISCO system. In the past several years, DISCO has greatly extended its functionality and has evolved to play a central role in automating the complex, ongoing process of harvesting, validating, integrating, and displaying neuroscience data from a growing set of participating resources. This paper provides an overview of DISCO's current capabilities and discusses a number of the challenges and future directions related to the process of coordinating the integration of neuroscience data within the NIF Federation.

The InSAR Scientific Computing Environment (ISCE): An Earth Science SAR Processing Framework, Toolbox, and Foundry

NASA Astrophysics Data System (ADS)

Agram, P. S.; Gurrola, E. M.; Lavalle, M.; Sacco, G. F.; Rosen, P. A.

2016-12-01

The InSAR Scientific Computing Environment (ISCE) provides both a modular, flexible, and extensible framework for building software components and applications that work together seamlessly as well as a toolbox for processing InSAR data into higher level geodetic image products from a diverse array of radar satellites and aircraft. ISCE easily scales to serve as the SAR processing engine at the core of the NASA JPL Advanced Rapid Imaging and Analysis (ARIA) Center for Natural Hazards as well as a software toolbox for individual scientists working with SAR data. ISCE is planned as the foundational element in processing NISAR data, enabling a new class of analyses that take greater advantage of the long time and large spatial scales of these data. ISCE in ARIA is also a SAR Foundry for development of new processing components and workflows to meet the needs of both large processing centers and individual users. The ISCE framework contains object-oriented Python components layered to construct Python InSAR components that manage legacy Fortran/C InSAR programs. The Python user interface enables both command-line deployment of workflows as well as an interactive "sand box" (the Python interpreter) where scientists can "play" with the data. Recent developments in ISCE include the addition of components to ingest Sentinel-1A SAR data (both stripmap and TOPS-mode) and a new workflow for processing the TOPS-mode data. New components are being developed to exploit polarimetric-SAR data to provide the ecosystem and land-cover/land-use change communities with rigorous and efficient tools to perform multi-temporal, polarimetric and tomographic analyses in order to generate calibrated, geocoded and mosaicked Level-2 and Level-3 products (e.g., maps of above-ground biomass or forest disturbance). ISCE has been downloaded by over 200 users by a license for WinSAR members through the Unavco.org website. Others may apply directly to JPL for a license at download.jpl.nasa.gov.

Evidence-informed physical therapy management of performance-related musculoskeletal disorders in musicians

PubMed Central

Chan, Cliffton; Ackermann, Bronwen

2014-01-01

Playing a musical instrument at an elite level is a highly complex motor skill. The regular daily training loads resulting from practice, rehearsals and performances place great demands on the neuromusculoskeletal systems of the body. As a consequence, performance-related musculoskeletal disorders (PRMDs) are globally recognized as common phenomena amongst professional orchestral musicians. These disorders create a significant financial burden to individuals and orchestras as well as lead to serious consequences to the musicians’ performance and ultimately their career. Physical therapists are experts in treating musculoskeletal injuries and are ideally placed to apply their skills to manage PRMDs in this hyper-functioning population, but there is little available evidence to guide specific injury management approaches. An Australia-wide survey of professional orchestral musicians revealed that the musicians attributed excessively high or sudden increase in playing-load as major contributors to their PRMDs. Therefore, facilitating musicians to better manage these loads should be a cornerstone of physical therapy management. The Sound Practice orchestral musicians work health and safety project used formative and process evaluation approaches to develop evidence-informed and clinically applicable physical therapy interventions, ultimately resulting in favorable outcomes. After these methodologies were employed, the intervention studies were conducted with a national cohort of professional musicians including: health education, onsite injury management, cross-training exercise regimes, performance postural analysis, and music performance biomechanics feedback. The outcomes of all these interventions will be discussed alongside a focussed review on the existing literature of these management strategies. Finally, a framework for best-practice physical therapy management of PRMDs in musicians will be provided. PMID:25071671

An open-source job management framework for parameter-space exploration: OACIS

NASA Astrophysics Data System (ADS)

Murase, Y.; Uchitane, T.; Ito, N.

2017-11-01

We present an open-source software framework for parameter-space exporation, named OACIS, which is useful to manage vast amount of simulation jobs and results in a systematic way. Recent development of high-performance computers enabled us to explore parameter spaces comprehensively, however, in such cases, manual management of the workflow is practically impossible. OACIS is developed aiming at reducing the cost of these repetitive tasks when conducting simulations by automating job submissions and data management. In this article, an overview of OACIS as well as a getting started guide are presented.

The Earth Data Analytic Services (EDAS) Framework

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; Duffy, D.

2017-12-01

Faced with unprecedented growth in earth data volume and demand, NASA has developed the Earth Data Analytic Services (EDAS) framework, a high performance big data analytics framework built on Apache Spark. This framework enables scientists to execute data processing workflows combining common analysis operations close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted earth data analysis tools (ESMF, CDAT, NCO, etc.). EDAS utilizes a dynamic caching architecture, a custom distributed array framework, and a streaming parallel in-memory workflow for efficiently processing huge datasets within limited memory spaces with interactive response times. EDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using direct web service calls, a Python script, a Unix-like shell client, or a JavaScript-based web application. New analytic operations can be developed in Python, Java, or Scala (with support for other languages planned). Client packages in Python, Java/Scala, or JavaScript contain everything needed to build and submit EDAS requests. The EDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service enables decision makers to compare multiple reanalysis datasets and investigate trends, variability, and anomalies in earth system dynamics around the globe.

Implementation of a 'lean' cytopathology service: towards routine same-day reporting.

PubMed

Hewer, Ekkehard; Hammer, Caroline; Fricke-Vetsch, Daniela; Baumann, Cinzia; Perren, Aurel; Schmitt, Anja M

2018-05-01

To systematically assess the effects of a Lean management intervention in an academic cytopathology service. We monitored outcomes including specimen turnaround times during stepwise implementation of a lean cytopathology workflow for gynaecological and non-gynaecological cytology. The intervention resulted in a major reduction of turnaround times for both gynaecological (3rd quartile 4.1 vs 2.3 working days) and non-gynaecological cytology (3rd quartile 1.9 vs. 1.2 working days). Introduction of fully electronic reporting had additional effect over continuous staining of slides alone. The rate of non-gynaecological specimens reported the same day increased from 4.5% to 56.5% of specimens received before noon. Lean management principles provide a useful framework for organization of a cytopathology workflow. Stepwise implementation beginning with a simplified gynaecological cytology workflow allowed involved staff to monitor the effects of individual changes and allowed for a smooth transition. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Installation and Testing of ITER Integrated Modeling and Analysis Suite (IMAS) on DIII-D

NASA Astrophysics Data System (ADS)

Lao, L.; Kostuk, M.; Meneghini, O.; Smith, S.; Staebler, G.; Kalling, R.; Pinches, S.

2017-10-01

A critical objective of the ITER Integrated Modeling Program is the development of IMAS to support ITER plasma operation and research activities. An IMAS framework has been established based on the earlier work carried out within the EU. It consists of a physics data model and a workflow engine. The data model is capable of representing both simulation and experimental data and is applicable to ITER and other devices. IMAS has been successfully installed on a local DIII-D server using a flexible installer capable of managing the core data access tools (Access Layer and Data Dictionary) and optionally the Kepler workflow engine and coupling tools. A general adaptor for OMFIT (a workflow engine) is being built for adaptation of any analysis code to IMAS using a new IMAS universal access layer (UAL) interface developed from an existing OMFIT EU Integrated Tokamak Modeling UAL. Ongoing work includes development of a general adaptor for EFIT and TGLF based on this new UAL that can be readily extended for other physics codes within OMFIT. Work supported by US DOE under DE-FC02-04ER54698.

High-Performance Compute Infrastructure in Astronomy: 2020 Is Only Months Away

NASA Astrophysics Data System (ADS)

Berriman, B.; Deelman, E.; Juve, G.; Rynge, M.; Vöckler, J. S.

2012-09-01

By 2020, astronomy will be awash with as much as 60 PB of public data. Full scientific exploitation of such massive volumes of data will require high-performance computing on server farms co-located with the data. Development of this computing model will be a community-wide enterprise that has profound cultural and technical implications. Astronomers must be prepared to develop environment-agnostic applications that support parallel processing. The community must investigate the applicability and cost-benefit of emerging technologies such as cloud computing to astronomy, and must engage the Computer Science community to develop science-driven cyberinfrastructure such as workflow schedulers and optimizers. We report here the results of collaborations between a science center, IPAC, and a Computer Science research institute, ISI. These collaborations may be considered pathfinders in developing a high-performance compute infrastructure in astronomy. These collaborations investigated two exemplar large-scale science-driver workflow applications: 1) Calculation of an infrared atlas of the Galactic Plane at 18 different wavelengths by placing data from multiple surveys on a common plate scale and co-registering all the pixels; 2) Calculation of an atlas of periodicities present in the public Kepler data sets, which currently contain 380,000 light curves. These products have been generated with two workflow applications, written in C for performance and designed to support parallel processing on multiple environments and platforms, but with different compute resource needs: the Montage image mosaic engine is I/O-bound, and the NASA Star and Exoplanet Database periodogram code is CPU-bound. Our presentation will report cost and performance metrics and lessons-learned for continuing development. Applicability of Cloud Computing: Commercial Cloud providers generally charge for all operations, including processing, transfer of input and output data, and for storage of data, and so the costs of running applications vary widely according to how they use resources. The cloud is well suited to processing CPU-bound (and memory bound) workflows such as the periodogram code, given the relatively low cost of processing in comparison with I/O operations. I/O-bound applications such as Montage perform best on high-performance clusters with fast networks and parallel file-systems. Science-driven Cyberinfrastructure: Montage has been widely used as a driver application to develop workflow management services, such as task scheduling in distributed environments, designing fault tolerance techniques for job schedulers, and developing workflow orchestration techniques. Running Parallel Applications Across Distributed Cloud Environments: Data processing will eventually take place in parallel distributed across cyber infrastructure environments having different architectures. We have used the Pegasus Work Management System (WMS) to successfully run applications across three very different environments: TeraGrid, OSG (Open Science Grid), and FutureGrid. Provisioning resources across different grids and clouds (also referred to as Sky Computing), involves establishing a distributed environment, where issues of, e.g, remote job submission, data management, and security need to be addressed. This environment also requires building virtual machine images that can run in different environments. Usually, each cloud provides basic images that can be customized with additional software and services. In most of our work, we provisioned compute resources using a custom application, called Wrangler. Pegasus WMS abstracts the architectures of the compute environments away from the end-user, and can be considered a first-generation tool suitable for scientists to run their applications on disparate environments.

Critical care physician cognitive task analysis: an exploratory study

PubMed Central

Fackler, James C; Watts, Charles; Grome, Anna; Miller, Thomas; Crandall, Beth; Pronovost, Peter

2009-01-01

Introduction For better or worse, the imposition of work-hour limitations on house-staff has imperiled continuity and/or improved decision-making. Regardless, the workflow of every physician team in every academic medical centre has been irrevocably altered. We explored the use of cognitive task analysis (CTA) techniques, most commonly used in other high-stress and time-sensitive environments, to analyse key cognitive activities in critical care medicine. The study objective was to assess the usefulness of CTA as an analytical tool in order that physician cognitive tasks may be understood and redistributed within the work-hour limited medical decision-making teams. Methods After approval from each Institutional Review Board, two intensive care units (ICUs) within major university teaching hospitals served as data collection sites for CTA observations and interviews of critical care providers. Results Five broad categories of cognitive activities were identified: pattern recognition; uncertainty management; strategic vs. tactical thinking; team coordination and maintenance of common ground; and creation and transfer of meaning through stories. Conclusions CTA within the framework of Naturalistic Decision Making is a useful tool to understand the critical care process of decision-making and communication. The separation of strategic and tactical thinking has implications for workflow redesign. Given the global push for work-hour limitations, such workflow redesign is occurring. Further work with CTA techniques will provide important insights toward rational, rather than random, workflow changes. PMID:19265517

Critical care physician cognitive task analysis: an exploratory study.

PubMed

Fackler, James C; Watts, Charles; Grome, Anna; Miller, Thomas; Crandall, Beth; Pronovost, Peter

2009-01-01

For better or worse, the imposition of work-hour limitations on house-staff has imperiled continuity and/or improved decision-making. Regardless, the workflow of every physician team in every academic medical centre has been irrevocably altered. We explored the use of cognitive task analysis (CTA) techniques, most commonly used in other high-stress and time-sensitive environments, to analyse key cognitive activities in critical care medicine. The study objective was to assess the usefulness of CTA as an analytical tool in order that physician cognitive tasks may be understood and redistributed within the work-hour limited medical decision-making teams. After approval from each Institutional Review Board, two intensive care units (ICUs) within major university teaching hospitals served as data collection sites for CTA observations and interviews of critical care providers. Five broad categories of cognitive activities were identified: pattern recognition; uncertainty management; strategic vs. tactical thinking; team coordination and maintenance of common ground; and creation and transfer of meaning through stories. CTA within the framework of Naturalistic Decision Making is a useful tool to understand the critical care process of decision-making and communication. The separation of strategic and tactical thinking has implications for workflow redesign. Given the global push for work-hour limitations, such workflow redesign is occurring. Further work with CTA techniques will provide important insights toward rational, rather than random, workflow changes.

A Web application for the management of clinical workflow in image‐guided and adaptive proton therapy for prostate cancer treatments

PubMed Central

Boes, Peter; Ho, Meng Wei; Li, Zuofeng

2015-01-01

Image‐guided radiotherapy (IGRT), based on radiopaque markers placed in the prostate gland, was used for proton therapy of prostate patients. Orthogonal X‐rays and the IBA Digital Image Positioning System (DIPS) were used for setup correction prior to treatment and were repeated after treatment delivery. Following a rationale for margin estimates similar to that of van Herk,(1) the daily post‐treatment DIPS data were analyzed to determine if an adaptive radiotherapy plan was necessary. A Web application using ASP.NET MVC5, Entity Framework, and an SQL database was designed to automate this process. The designed features included state‐of‐the‐art Web technologies, a domain model closely matching the workflow, a database‐supporting concurrency and data mining, access to the DIPS database, secured user access and roles management, and graphing and analysis tools. The Model‐View‐Controller (MVC) paradigm allowed clean domain logic, unit testing, and extensibility. Client‐side technologies, such as jQuery, jQuery Plug‐ins, and Ajax, were adopted to achieve a rich user environment and fast response. Data models included patients, staff, treatment fields and records, correction vectors, DIPS images, and association logics. Data entry, analysis, workflow logics, and notifications were implemented. The system effectively modeled the clinical workflow and IGRT process. PACS number: 87 PMID:26103504

Integrate Data into Scientific Workflows for Terrestrial Biosphere Model Evaluation through Brokers

NASA Astrophysics Data System (ADS)

Wei, Y.; Cook, R. B.; Du, F.; Dasgupta, A.; Poco, J.; Huntzinger, D. N.; Schwalm, C. R.; Boldrini, E.; Santoro, M.; Pearlman, J.; Pearlman, F.; Nativi, S.; Khalsa, S.

2013-12-01

Terrestrial biosphere models (TBMs) have become integral tools for extrapolating local observations and process-level understanding of land-atmosphere carbon exchange to larger regions. Model-model and model-observation intercomparisons are critical to understand the uncertainties within model outputs, to improve model skill, and to improve our understanding of land-atmosphere carbon exchange. The DataONE Exploration, Visualization, and Analysis (EVA) working group is evaluating TBMs using scientific workflows in UV-CDAT/VisTrails. This workflow-based approach promotes collaboration and improved tracking of evaluation provenance. But challenges still remain. The multi-scale and multi-discipline nature of TBMs makes it necessary to include diverse and distributed data resources in model evaluation. These include, among others, remote sensing data from NASA, flux tower observations from various organizations including DOE, and inventory data from US Forest Service. A key challenge is to make heterogeneous data from different organizations and disciplines discoverable and readily integrated for use in scientific workflows. This presentation introduces the brokering approach taken by the DataONE EVA to fill the gap between TBMs' evaluation scientific workflows and cross-organization and cross-discipline data resources. The DataONE EVA started the development of an Integrated Model Intercomparison Framework (IMIF) that leverages standards-based discovery and access brokers to dynamically discover, access, and transform (e.g. subset and resampling) diverse data products from DataONE, Earth System Grid (ESG), and other data repositories into a format that can be readily used by scientific workflows in UV-CDAT/VisTrails. The discovery and access brokers serve as an independent middleware that bridge existing data repositories and TBMs evaluation scientific workflows but introduce little overhead to either component. In the initial work, an OpenSearch-based discovery broker is leveraged to provide a consistent mechanism for data discovery. Standards-based data services, including Open Geospatial Consortium (OGC) Web Coverage Service (WCS) and THREDDS are leveraged to provide on-demand data access and transformations through the data access broker. To ease the adoption of broker services, a package of broker client VisTrails modules have been developed to be easily plugged into scientific workflows. The initial IMIF has been successfully tested in selected model evaluation scenarios involved in the NASA-funded Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP).

Flexible Early Warning Systems with Workflows and Decision Tables

NASA Astrophysics Data System (ADS)

Riedel, F.; Chaves, F.; Zeiner, H.

2012-04-01

An essential part of early warning systems and systems for crisis management are decision support systems that facilitate communication and collaboration. Often official policies specify how different organizations collaborate and what information is communicated to whom. For early warning systems it is crucial that information is exchanged dynamically in a timely manner and all participants get exactly the information they need to fulfil their role in the crisis management process. Information technology obviously lends itself to automate parts of the process. We have experienced however that in current operational systems the information logistics processes are hard-coded, even though they are subject to change. In addition, systems are tailored to the policies and requirements of a certain organization and changes can require major software refactoring. We seek to develop a system that can be deployed and adapted to multiple organizations with different dynamic runtime policies. A major requirement for such a system is that changes can be applied locally without affecting larger parts of the system. In addition to the flexibility regarding changes in policies and processes, the system needs to be able to evolve; when new information sources become available, it should be possible to integrate and use these in the decision process. In general, this kind of flexibility comes with a significant increase in complexity. This implies that only IT professionals can maintain a system that can be reconfigured and adapted; end-users are unable to utilise the provided flexibility. In the business world similar problems arise and previous work suggested using business process management systems (BPMS) or workflow management systems (WfMS) to guide and automate early warning processes or crisis management plans. However, the usability and flexibility of current WfMS are limited, because current notations and user interfaces are still not suitable for end-users, and workflows are usually only suited for rigid processes. We show how improvements can be achieved by using decision tables and rule-based adaptive workflows. Decision tables have been shown to be an intuitive tool that can be used by domain experts to express rule sets that can be interpreted automatically at runtime. Adaptive workflows use a rule-based approach to increase the flexibility of workflows by providing mechanisms to adapt workflows based on context changes, human intervention and availability of services. The combination of workflows, decision tables and rule-based adaption creates a framework that opens up new possibilities for flexible and adaptable workflows, especially, for use in early warning and crisis management systems.

Management of natural crises with choreography and orchestration of federated warning-systems

NASA Astrophysics Data System (ADS)

Haener, Rainer; Waechter, Joachim; Hammitzsch, Martin

2013-04-01

The project Collaborative, Complex and Critical Decision-Support in Evolving Crises (TRIDEC), co-funded by the European Commission in its Seventh Framework Programme focuses on real-time intelligent information management in earth management. The addressed challenges include the design and implementation of a robust and scalable service infrastructure supporting the integration of existing resources, components and systems. Key challenge for TRIDEC is establishing a network of independent systems, cooperatively interacting as a collective in a system-of-systems (SoS). For this purpose TRIDEC adopts enhancements of service-oriented architecture (SOA) principles in terms of an event-driven architecture (EDA) design (SOA 2.0). In this way TRIDEC establishes large-scale concurrent and intelligent information management of a manifold of crisis types by focusing on the integration of autonomous, task-oriented and geographically distributed systems. To this end TRIDEC adapts both ways SOA 2.0 offers: orchestration and choreography. In orchestration, a central knowledge-based processing framework takes control over the involved services and coordinates their execution. Choreography on the other hand avoids central coordination. Rather, each system involved in the SoS follows a global scenario without a single point of control but specifically defined (enacted, agreed upon) trigger conditions. More than orchestration choreography allows collaborative business processes of various heterogeneous sub-systems (e.g. cooperative decision making) by concurrent Complex Event Processing (CEP) and asynchronous communication. These types of interaction adapt the concept of decoupled relationships between information producers (e.g. sensors and sensor systems) and information consumers (e.g. warning systems and warning dissemination systems). Asynchronous communication is useful if a participant wants to trigger specific actions by delegating the responsibility (separation of concerns) for the action to a dedicated participant. Implementing CEP, none of the participants has to know anything about the others. Information is filtered from a stream of manifold events (triggers) assigned to certain and well-defined topics. Both, orchestration and choreography are based on the specification of conversations, which comprise the information model, the roles and responsibilities of all participants, services and business processes, and interaction scenarios. By the maintenance of conversations in commonly available and semantically enabled registries it is possible to establish a federation of systems that is able to provide dynamic, yet coherent behaviour. TRIDEC establishes a reliable and adaptive SoS (concurrent processing of events and activities) which exposes emergent behaviour (e.g. intelligent and adaptive monitoring strategies, cooperative decision making or dynamic system configuration) even in case of partly system failures. In a process of self-organising (task balancing and dynamic delegation of responsibilities) as SoS is able to secure the reliability and responsiveness for real-time, long running & durable monitoring activities. Concepts like Design by Contract (DbC), service level agreements (SLA), redundancy- and failover-strategies as well as a comprehensive knowledge-based description of all facets of all potential interactions ensure the interoperability, robustness and expected behaviour of the TRIDEC SoS even if it is composed of managerial independent sub-systems. Beyond these features, the adaptability of a SoS offers scalability and virtualization regarding both, systems and domains. Composability and re-use of functionality can be achieved easily even across domain-boundaries.

SISYPHUS: A high performance seismic inversion factory

NASA Astrophysics Data System (ADS)

Gokhberg, Alexey; Simutė, Saulė; Boehm, Christian; Fichtner, Andreas

2016-04-01

In the recent years the massively parallel high performance computers became the standard instruments for solving the forward and inverse problems in seismology. The respective software packages dedicated to forward and inverse waveform modelling specially designed for such computers (SPECFEM3D, SES3D) became mature and widely available. These packages achieve significant computational performance and provide researchers with an opportunity to solve problems of bigger size at higher resolution within a shorter time. However, a typical seismic inversion process contains various activities that are beyond the common solver functionality. They include management of information on seismic events and stations, 3D models, observed and synthetic seismograms, pre-processing of the observed signals, computation of misfits and adjoint sources, minimization of misfits, and process workflow management. These activities are time consuming, seldom sufficiently automated, and therefore represent a bottleneck that can substantially offset performance benefits provided by even the most powerful modern supercomputers. Furthermore, a typical system architecture of modern supercomputing platforms is oriented towards the maximum computational performance and provides limited standard facilities for automation of the supporting activities. We present a prototype solution that automates all aspects of the seismic inversion process and is tuned for the modern massively parallel high performance computing systems. We address several major aspects of the solution architecture, which include (1) design of an inversion state database for tracing all relevant aspects of the entire solution process, (2) design of an extensible workflow management framework, (3) integration with wave propagation solvers, (4) integration with optimization packages, (5) computation of misfits and adjoint sources, and (6) process monitoring. The inversion state database represents a hierarchical structure with branches for the static process setup, inversion iterations, and solver runs, each branch specifying information at the event, station and channel levels. The workflow management framework is based on an embedded scripting engine that allows definition of various workflow scenarios using a high-level scripting language and provides access to all available inversion components represented as standard library functions. At present the SES3D wave propagation solver is integrated in the solution; the work is in progress for interfacing with SPECFEM3D. A separate framework is designed for interoperability with an optimization module; the workflow manager and optimization process run in parallel and cooperate by exchanging messages according to a specially designed protocol. A library of high-performance modules implementing signal pre-processing, misfit and adjoint computations according to established good practices is included. Monitoring is based on information stored in the inversion state database and at present implements a command line interface; design of a graphical user interface is in progress. The software design fits well into the common massively parallel system architecture featuring a large number of computational nodes running distributed applications under control of batch-oriented resource managers. The solution prototype has been implemented on the "Piz Daint" supercomputer provided by the Swiss Supercomputing Centre (CSCS).

Performance Reviews for the Orchestral Musician

ERIC Educational Resources Information Center

Watson, Amanda; Forrest, David

2014-01-01

Musicians are appointed to positions in professional symphony orchestras--both rank and file and section principals--following a blind audition process. They perform set repertoire works and orchestral excerpts behind a screen. In many higher education programs, musicians focus on learning the orchestral excerpts and instrumental repertoire that…

FluxCTTX: A LIMS-based tool for management and analysis of cytotoxicity assays data

PubMed Central

2015-01-01

Background Cytotoxicity assays have been used by researchers to screen for cytotoxicity in compound libraries. Researchers can either look for cytotoxic compounds or screen "hits" from initial high-throughput drug screens for unwanted cytotoxic effects before investing in their development as a pharmaceutical. These assays may be used as an alternative to animal experimentation and are becoming increasingly important in modern laboratories. However, the execution of these assays in large scale and different laboratories requires, among other things, the management of protocols, reagents, cell lines used as well as the data produced, which can be a challenge. The management of all this information is greatly improved by the utilization of computational tools to save time and guarantee quality. However, a tool that performs this task designed specifically for cytotoxicity assays is not yet available. Results In this work, we have used a workflow based LIMS -- the Flux system -- and the Together Workflow Editor as a framework to develop FluxCTTX, a tool for management of data from cytotoxicity assays performed at different laboratories. The main work is the development of a workflow, which represents all stages of the assay and has been developed and uploaded in Flux. This workflow models the activities of cytotoxicity assays performed as described in the OECD 129 Guidance Document. Conclusions FluxCTTX presents a solution for the management of the data produced by cytotoxicity assays performed at Interlaboratory comparisons. Its adoption will contribute to guarantee the quality of activities in the process of cytotoxicity tests and enforce the use of Good Laboratory Practices (GLP). Furthermore, the workflow developed is complete and can be adapted to other contexts and different tests for management of other types of data. PMID:26696462

Model-based Vestibular Afferent Stimulation: Modular Workflow for Analyzing Stimulation Scenarios in Patient Specific and Statistical Vestibular Anatomy.

PubMed

Handler, Michael; Schier, Peter P; Fritscher, Karl D; Raudaschl, Patrik; Johnson Chacko, Lejo; Glueckert, Rudolf; Saba, Rami; Schubert, Rainer; Baumgarten, Daniel; Baumgartner, Christian

2017-01-01

Our sense of balance and spatial orientation strongly depends on the correct functionality of our vestibular system. Vestibular dysfunction can lead to blurred vision and impaired balance and spatial orientation, causing a significant decrease in quality of life. Recent studies have shown that vestibular implants offer a possible treatment for patients with vestibular dysfunction. The close proximity of the vestibular nerve bundles, the facial nerve and the cochlear nerve poses a major challenge to targeted stimulation of the vestibular system. Modeling the electrical stimulation of the vestibular system allows for an efficient analysis of stimulation scenarios previous to time and cost intensive in vivo experiments. Current models are based on animal data or CAD models of human anatomy. In this work, a (semi-)automatic modular workflow is presented for the stepwise transformation of segmented vestibular anatomy data of human vestibular specimens to an electrical model and subsequently analyzed. The steps of this workflow include (i) the transformation of labeled datasets to a tetrahedra mesh, (ii) nerve fiber anisotropy and fiber computation as a basis for neuron models, (iii) inclusion of arbitrary electrode designs, (iv) simulation of quasistationary potential distributions, and (v) analysis of stimulus waveforms on the stimulation outcome. Results obtained by the workflow based on human datasets and the average shape of a statistical model revealed a high qualitative agreement and a quantitatively comparable range compared to data from literature, respectively. Based on our workflow, a detailed analysis of intra- and extra-labyrinthine electrode configurations with various stimulation waveforms and electrode designs can be performed on patient specific anatomy, making this framework a valuable tool for current optimization questions concerning vestibular implants in humans.

An Exploratory Comparison of Novice, Intermediate, and Expert Orchestral Conductors

ERIC Educational Resources Information Center

Bergee, Martin J.

2005-01-01

This study compared novice, "intermediate" (graduate student), and expert orchestral conductors. Two novice conductors, one graduate student in orchestral conducting, and one expert conductor led a university symphony orchestra in part of the first movement of Brahms's Symphony No. 2. Wired for sound, conductors attempted to verbalize their…

Orchestral Performance and the Footprint of Mindfulness

ERIC Educational Resources Information Center

Langer, Ellen; Russell, Timothy; Eisenkraft, Noah

2009-01-01

Two studies were designed to test the hypothesis that actively creating novel distinctions and sonically portraying them during the performance of orchestral music is preferable to attempting to re-create a past performance. The data suggest that orchestral musicians preferred creating music when they were encouraged to mindfully incorporate…

A Young Person's Guide to the Orchestral Profession

ERIC Educational Resources Information Center

Corkhill, David

2005-01-01

Through interviews with ten conservatoire students and ten professional orchestral musicians teaching at conservatoires, this paper seeks to establish whether young people regard the orchestral music profession as a worthwhile ambition. If so, are teachers preparing students sufficiently for their careers and passing on the benefits of their…

Integrated modeling applications for tokamak experiments with OMFIT

NASA Astrophysics Data System (ADS)

Meneghini, O.; Smith, S. P.; Lao, L. L.; Izacard, O.; Ren, Q.; Park, J. M.; Candy, J.; Wang, Z.; Luna, C. J.; Izzo, V. A.; Grierson, B. A.; Snyder, P. B.; Holland, C.; Penna, J.; Lu, G.; Raum, P.; McCubbin, A.; Orlov, D. M.; Belli, E. A.; Ferraro, N. M.; Prater, R.; Osborne, T. H.; Turnbull, A. D.; Staebler, G. M.

2015-08-01

One modeling framework for integrated tasks (OMFIT) is a comprehensive integrated modeling framework which has been developed to enable physics codes to interact in complicated workflows, and support scientists at all stages of the modeling cycle. The OMFIT development follows a unique bottom-up approach, where the framework design and capabilities organically evolve to support progressive integration of the components that are required to accomplish physics goals of increasing complexity. OMFIT provides a workflow for easily generating full kinetic equilibrium reconstructions that are constrained by magnetic and motional Stark effect measurements, and kinetic profile information that includes fast-ion pressure modeled by a transport code. It was found that magnetic measurements can be used to quantify the amount of anomalous fast-ion diffusion that is present in DIII-D discharges, and provide an estimate that is consistent with what would be needed for transport simulations to match the measured neutron rates. OMFIT was used to streamline edge-stability analyses, and evaluate the effect of resonant magnetic perturbation (RMP) on the pedestal stability, which have been found to be consistent with the experimental observations. The development of a five-dimensional numerical fluid model for estimating the effects of the interaction between magnetohydrodynamic (MHD) and microturbulence, and its systematic verification against analytic models was also supported by the framework. OMFIT was used for optimizing an innovative high-harmonic fast wave system proposed for DIII-D. For a parallel refractive index {{n}\\parallel}>3 , the conditions for strong electron-Landau damping were found to be independent of launched {{n}\\parallel} and poloidal angle. OMFIT has been the platform of choice for developing a neural-network based approach to efficiently perform a non-linear multivariate regression of local transport fluxes as a function of local dimensionless parameters. Transport predictions for thousands of DIII-D discharges showed excellent agreement with the power balance calculations across the whole plasma radius and over a broad range of operating regimes. Concerning predictive transport simulations, the framework made possible the design and automation of a workflow that enables self-consistent predictions of kinetic profiles and the plasma equilibrium. It is found that the feedback between the transport fluxes and plasma equilibrium can significantly affect the kinetic profiles predictions. Such a rich set of results provide tangible evidence of how bottom-up approaches can potentially provide a fast track to integrated modeling solutions that are functional, cost-effective, and in sync with the research effort of the community.

GeNNet: an integrated platform for unifying scientific workflows and graph databases for transcriptome data analysis

PubMed Central

Gadelha, Luiz; Ribeiro-Alves, Marcelo; Porto, Fábio

2017-01-01

There are many steps in analyzing transcriptome data, from the acquisition of raw data to the selection of a subset of representative genes that explain a scientific hypothesis. The data produced can be represented as networks of interactions among genes and these may additionally be integrated with other biological databases, such as Protein-Protein Interactions, transcription factors and gene annotation. However, the results of these analyses remain fragmented, imposing difficulties, either for posterior inspection of results, or for meta-analysis by the incorporation of new related data. Integrating databases and tools into scientific workflows, orchestrating their execution, and managing the resulting data and its respective metadata are challenging tasks. Additionally, a great amount of effort is equally required to run in-silico experiments to structure and compose the information as needed for analysis. Different programs may need to be applied and different files are produced during the experiment cycle. In this context, the availability of a platform supporting experiment execution is paramount. We present GeNNet, an integrated transcriptome analysis platform that unifies scientific workflows with graph databases for selecting relevant genes according to the evaluated biological systems. It includes GeNNet-Wf, a scientific workflow that pre-loads biological data, pre-processes raw microarray data and conducts a series of analyses including normalization, differential expression inference, clusterization and gene set enrichment analysis. A user-friendly web interface, GeNNet-Web, allows for setting parameters, executing, and visualizing the results of GeNNet-Wf executions. To demonstrate the features of GeNNet, we performed case studies with data retrieved from GEO, particularly using a single-factor experiment in different analysis scenarios. As a result, we obtained differentially expressed genes for which biological functions were analyzed. The results are integrated into GeNNet-DB, a database about genes, clusters, experiments and their properties and relationships. The resulting graph database is explored with queries that demonstrate the expressiveness of this data model for reasoning about gene interaction networks. GeNNet is the first platform to integrate the analytical process of transcriptome data with graph databases. It provides a comprehensive set of tools that would otherwise be challenging for non-expert users to install and use. Developers can add new functionality to components of GeNNet. The derived data allows for testing previous hypotheses about an experiment and exploring new ones through the interactive graph database environment. It enables the analysis of different data on humans, rhesus, mice and rat coming from Affymetrix platforms. GeNNet is available as an open source platform at https://github.com/raquele/GeNNet and can be retrieved as a software container with the command docker pull quelopes/gennet. PMID:28695067

GeNNet: an integrated platform for unifying scientific workflows and graph databases for transcriptome data analysis.

PubMed

Costa, Raquel L; Gadelha, Luiz; Ribeiro-Alves, Marcelo; Porto, Fábio

2017-01-01

There are many steps in analyzing transcriptome data, from the acquisition of raw data to the selection of a subset of representative genes that explain a scientific hypothesis. The data produced can be represented as networks of interactions among genes and these may additionally be integrated with other biological databases, such as Protein-Protein Interactions, transcription factors and gene annotation. However, the results of these analyses remain fragmented, imposing difficulties, either for posterior inspection of results, or for meta-analysis by the incorporation of new related data. Integrating databases and tools into scientific workflows, orchestrating their execution, and managing the resulting data and its respective metadata are challenging tasks. Additionally, a great amount of effort is equally required to run in-silico experiments to structure and compose the information as needed for analysis. Different programs may need to be applied and different files are produced during the experiment cycle. In this context, the availability of a platform supporting experiment execution is paramount. We present GeNNet, an integrated transcriptome analysis platform that unifies scientific workflows with graph databases for selecting relevant genes according to the evaluated biological systems. It includes GeNNet-Wf, a scientific workflow that pre-loads biological data, pre-processes raw microarray data and conducts a series of analyses including normalization, differential expression inference, clusterization and gene set enrichment analysis. A user-friendly web interface, GeNNet-Web, allows for setting parameters, executing, and visualizing the results of GeNNet-Wf executions. To demonstrate the features of GeNNet, we performed case studies with data retrieved from GEO, particularly using a single-factor experiment in different analysis scenarios. As a result, we obtained differentially expressed genes for which biological functions were analyzed. The results are integrated into GeNNet-DB, a database about genes, clusters, experiments and their properties and relationships. The resulting graph database is explored with queries that demonstrate the expressiveness of this data model for reasoning about gene interaction networks. GeNNet is the first platform to integrate the analytical process of transcriptome data with graph databases. It provides a comprehensive set of tools that would otherwise be challenging for non-expert users to install and use. Developers can add new functionality to components of GeNNet. The derived data allows for testing previous hypotheses about an experiment and exploring new ones through the interactive graph database environment. It enables the analysis of different data on humans, rhesus, mice and rat coming from Affymetrix platforms. GeNNet is available as an open source platform at https://github.com/raquele/GeNNet and can be retrieved as a software container with the command docker pull quelopes/gennet.

Orchid: a novel management, annotation and machine learning framework for analyzing cancer mutations.

PubMed

Cario, Clinton L; Witte, John S

2018-03-15

As whole-genome tumor sequence and biological annotation datasets grow in size, number and content, there is an increasing basic science and clinical need for efficient and accurate data management and analysis software. With the emergence of increasingly sophisticated data stores, execution environments and machine learning algorithms, there is also a need for the integration of functionality across frameworks. We present orchid, a python based software package for the management, annotation and machine learning of cancer mutations. Building on technologies of parallel workflow execution, in-memory database storage and machine learning analytics, orchid efficiently handles millions of mutations and hundreds of features in an easy-to-use manner. We describe the implementation of orchid and demonstrate its ability to distinguish tissue of origin in 12 tumor types based on 339 features using a random forest classifier. Orchid and our annotated tumor mutation database are freely available at https://github.com/wittelab/orchid. Software is implemented in python 2.7, and makes use of MySQL or MemSQL databases. Groovy 2.4.5 is optionally required for parallel workflow execution. JWitte@ucsf.edu. Supplementary data are available at Bioinformatics online.

Designing the safety of healthcare. Participation of ergonomics to the design of cooperative systems in radiotherapy.

PubMed

Munoz, Maria Isabel; Bouldi, Nadia; Barcellini, Flore; Nascimento, Adelaide

2012-01-01

This communication deals with the involvement of ergonomists in a research-action design process of a software platform in radiotherapy. The goal of the design project is to enhance patient safety by designing a workflow software that supports cooperation between professionals producing treatment in radiotherapy. The general framework of our approach is the ergonomics management of a design process, which is based in activity analysis and grounded in participatory design. Two fields are concerned by the present action: a design environment which is a participatory design process that involves software designers, caregivers as future users and ergonomists; and a reference real work setting in radiotherapy. Observations, semi-structured interviews and participatory workshops allow the characterization of activity in radiotherapy dealing with uses of cooperative tools, sources of variability and non-ruled strategies to manage the variability of the situations. This production of knowledge about work searches to enhance the articulation between technocentric and anthropocentric approaches, and helps in clarifying design requirements. An issue of this research-action is to develop a framework to define the parameters of the workflow tool, and the conditions of its deployment.

Reusable Social Networking Capabilities for an Earth Science Collaboratory

NASA Astrophysics Data System (ADS)

Lynnes, C.; Da Silva, D.; Leptoukh, G. G.; Ramachandran, R.

2011-12-01

A vast untapped resource of data, tools, information and knowledge lies within the Earth science community. This is due to the fact that it is difficult to share the full spectrum of these entities, particularly their full context. As a result, most knowledge exchange is through person-to-person contact at meetings, email and journal articles, each of which can support only a limited level of detail. We propose the creation of an Earth Science Collaboratory (ESC): a framework that would enable sharing of data, tools, workflows, results and the contextual knowledge about these information entities. The Drupal platform is well positioned to provide the key social networking capabilities to the ESC. As a proof of concept of a rich collaboration mechanism, we have developed a Drupal-based mechanism for graphically annotating and commenting on results images from analysis workflows in the online Giovanni analysis system for remote sensing data. The annotations can be tagged and shared with others in the community. These capabilities are further supplemented by a Research Notebook capability reused from another online analysis system named Talkoot. The goal is a reusable set of modules that can integrate with variety of other applications either within Drupal web frameworks or at a machine level.

Echo™ User Manual

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

Harvey, Dustin Yewell

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

OPPL-Galaxy, a Galaxy tool for enhancing ontology exploitation as part of bioinformatics workflows

PubMed Central

2013-01-01

Background Biomedical ontologies are key elements for building up the Life Sciences Semantic Web. Reusing and building biomedical ontologies requires flexible and versatile tools to manipulate them efficiently, in particular for enriching their axiomatic content. The Ontology Pre Processor Language (OPPL) is an OWL-based language for automating the changes to be performed in an ontology. OPPL augments the ontologists’ toolbox by providing a more efficient, and less error-prone, mechanism for enriching a biomedical ontology than that obtained by a manual treatment. Results We present OPPL-Galaxy, a wrapper for using OPPL within Galaxy. The functionality delivered by OPPL (i.e. automated ontology manipulation) can be combined with the tools and workflows devised within the Galaxy framework, resulting in an enhancement of OPPL. Use cases are provided in order to demonstrate OPPL-Galaxy’s capability for enriching, modifying and querying biomedical ontologies. Conclusions Coupling OPPL-Galaxy with other bioinformatics tools of the Galaxy framework results in a system that is more than the sum of its parts. OPPL-Galaxy opens a new dimension of analyses and exploitation of biomedical ontologies, including automated reasoning, paving the way towards advanced biological data analyses. PMID:23286517

From data to the decision: A software architecture to integrate predictive modelling in clinical settings.

PubMed

Martinez-Millana, A; Fernandez-Llatas, C; Sacchi, L; Segagni, D; Guillen, S; Bellazzi, R; Traver, V

2015-08-01

The application of statistics and mathematics over large amounts of data is providing healthcare systems with new tools for screening and managing multiple diseases. Nonetheless, these tools have many technical and clinical limitations as they are based on datasets with concrete characteristics. This proposition paper describes a novel architecture focused on providing a validation framework for discrimination and prediction models in the screening of Type 2 diabetes. For that, the architecture has been designed to gather different data sources under a common data structure and, furthermore, to be controlled by a centralized component (Orchestrator) in charge of directing the interaction flows among data sources, models and graphical user interfaces. This innovative approach aims to overcome the data-dependency of the models by providing a validation framework for the models as they are used within clinical settings.

Towards Dynamic Service Level Agreement Negotiation:An Approach Based on WS-Agreement

NASA Astrophysics Data System (ADS)

Pichot, Antoine; Wäldrich, Oliver; Ziegler, Wolfgang; Wieder, Philipp

In Grid, e-Science and e-Business environments, Service Level Agreements are often used to establish frameworks for the delivery of services between service providers and the organisations hosting the researchers. While this high level SLAs define the overall quality of the services, it is desirable for the end-user to have dedicated service quality also for individual services like the orchestration of resources necessary for composed services. Grid level scheduling services typically are responsible for the orchestration and co-ordination of resources in the Grid. Co-allocation e.g. requires the Grid level scheduler to co-ordinate resource management systems located in different domains. As the site autonomy has to be respected negotiation is the only way to achieve the intended co-ordination. SLAs emerged as a new way to negotiate and manage usage of resources in the Grid and are already adopted by a number of management systems. Therefore, it is natural to look for ways to adopt SLAs for Grid level scheduling. In order to do this, efficient and flexible protocols are needed, which support dynamic negotiation and creation of SLAs. In this paper we propose and discuss extensions to the WS-Agreement protocol addressing these issues.

The Effects of Orchestration on Musicians' and Nonmusicians' Perception of Musical Tension

ERIC Educational Resources Information Center

Silvey, Brian A.

2011-01-01

The purpose of this study was to examine the effects of orchestration on musicians' and nonmusicians' (N = 40) perception of musical tension. Participants were asked to register their perceptions of tension using the Continuous Response Digital Interface dial while listening to three orchestrations (full orchestra, brass quintet, and solo piano)…

Technology-Supported Orchestration Matters: Outperforming Paper-Based Scripting in a Jigsaw Classroom

ERIC Educational Resources Information Center

Balestrini, Mara; Hernandez-Leo, Davinia; Nieves, Raul; Blat, Josep

2014-01-01

Under the umbrella of ubiquitous technologies, many computational artifacts have been designed to enhance the learning experience in physical settings such as classrooms or playgrounds, but few of them focus on aiding orchestration. This paper presents a systematic evaluation of the signal orchestration system (SOS) used by students for a jigsaw…

Bridging gaps in handoffs: a continuity of care based approach.

PubMed

Abraham, Joanna; Kannampallil, Thomas G; Patel, Vimla L

2012-04-01

Handoff among healthcare providers has been recognized as a major source of medical errors. Most prior research has often focused on the communication aspects of handoff, with limited emphasis on the overall handoff process, especially from a clinician workflow perspective. Such a workflow perspective that is based on the continuity of care model provides a framework required to identify and support an interconnected trajectory of care events affecting handoff communication. To this end, we propose a new methodology, referred to as the clinician-centered approach that allows us to investigate and represent the entire clinician workflow prior to, during and, after handoff communication. This representation of clinician activities supports a comprehensive analysis of the interdependencies in the handoff process across the care continuum, as opposed to a single discrete, information sharing activity. The clinician-centered approach is supported by multifaceted methods for data collection such as observations, shadowing of clinicians, audio recording of handoff communication, semi-structured interviews and artifact identification and collection. The analysis followed a two-stage mixed inductive-deductive method. The iterative development of clinician-centered approach was realized using a multi-faceted study conducted in the Medical Intensive Care Unit (MICU) of an academic hospital. Using the clinician-centered approach, we (a) identify the nature, inherent characteristics and the interdependencies between three phases of the handoff process and (b) develop a descriptive framework of handoff communication in critical care that captures the non-linear, recursive and interactive nature of collaboration and decision-making. The results reported in this paper serve as a "proof of concept" of our approach, emphasizing the importance of capturing a coordinated and uninterrupted succession of clinician information management and transfer activities in relation to patient care events. Copyright © 2011 Elsevier Inc. All rights reserved.

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

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

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

Digital data acquisition for a CAD/CAM-fabricated titanium framework and zirconium oxide restorations for an implant-supported fixed complete dental prosthesis.

PubMed

Lin, Wei-Shao; Metz, Michael J; Pollini, Adrien; Ntounis, Athanasios; Morton, Dean

2014-12-01

This dental technique report describes a digital workflow with digital data acquisition at the implant level, computer-aided design and computer-aided manufacturing fabricated, tissue-colored, anodized titanium framework, individually luted zirconium oxide restorations, and autopolymerizing injection-molded acrylic resin to fabricate an implant-supported, metal-ceramic-resin fixed complete dental prosthesis in an edentulous mandible. The 1-step computer-aided design and computer-aided manufacturing fabrication of titanium framework and zirconium oxide restorations can provide a cost-effective alternative to the conventional metal-resin fixed complete dental prosthesis. Copyright © 2014 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

DOE PAGES

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek; ...

2017-04-24

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

Barista: A Framework for Concurrent Speech Processing by USC-SAIL

PubMed Central

Can, Doğan; Gibson, James; Vaz, Colin; Georgiou, Panayiotis G.; Narayanan, Shrikanth S.

2016-01-01

We present Barista, an open-source framework for concurrent speech processing based on the Kaldi speech recognition toolkit and the libcppa actor library. With Barista, we aim to provide an easy-to-use, extensible framework for constructing highly customizable concurrent (and/or distributed) networks for a variety of speech processing tasks. Each Barista network specifies a flow of data between simple actors, concurrent entities communicating by message passing, modeled after Kaldi tools. Leveraging the fast and reliable concurrency and distribution mechanisms provided by libcppa, Barista lets demanding speech processing tasks, such as real-time speech recognizers and complex training workflows, to be scheduled and executed on parallel (and/or distributed) hardware. Barista is released under the Apache License v2.0. PMID:27610047

Barista: A Framework for Concurrent Speech Processing by USC-SAIL.

PubMed

Can, Doğan; Gibson, James; Vaz, Colin; Georgiou, Panayiotis G; Narayanan, Shrikanth S

2014-05-01

We present Barista, an open-source framework for concurrent speech processing based on the Kaldi speech recognition toolkit and the libcppa actor library. With Barista, we aim to provide an easy-to-use, extensible framework for constructing highly customizable concurrent (and/or distributed) networks for a variety of speech processing tasks. Each Barista network specifies a flow of data between simple actors, concurrent entities communicating by message passing, modeled after Kaldi tools. Leveraging the fast and reliable concurrency and distribution mechanisms provided by libcppa, Barista lets demanding speech processing tasks, such as real-time speech recognizers and complex training workflows, to be scheduled and executed on parallel (and/or distributed) hardware. Barista is released under the Apache License v2.0.

CMS Configuration Editor: GUI based application for user analysis job

NASA Astrophysics Data System (ADS)

de Cosa, A.

2011-12-01

We present the user interface and the software architecture of the Configuration Editor for the CMS experiment. The analysis workflow is organized in a modular way integrated within the CMS framework that organizes in a flexible way user analysis code. The Python scripting language is adopted to define the job configuration that drives the analysis workflow. It could be a challenging task for users, especially for newcomers, to develop analysis jobs managing the configuration of many required modules. For this reason a graphical tool has been conceived in order to edit and inspect configuration files. A set of common analysis tools defined in the CMS Physics Analysis Toolkit (PAT) can be steered and configured using the Config Editor. A user-defined analysis workflow can be produced starting from a standard configuration file, applying and configuring PAT tools according to the specific user requirements. CMS users can adopt this tool, the Config Editor, to create their analysis visualizing in real time which are the effects of their actions. They can visualize the structure of their configuration, look at the modules included in the workflow, inspect the dependences existing among the modules and check the data flow. They can visualize at which values parameters are set and change them according to what is required by their analysis task. The integration of common tools in the GUI needed to adopt an object-oriented structure in the Python definition of the PAT tools and the definition of a layer of abstraction from which all PAT tools inherit.

A Study of Master's Degrees in Orchestral Conducting in the United States

ERIC Educational Resources Information Center

St. John, Brian Allen

2010-01-01

In order to learn to be an orchestra conductor in the United States of America, students often begins their formal education by seeking to earn a master's degree in orchestral conducting. This project compiled a listing of American universities which offer a master's degree in orchestral conducting and categorized the component parts of their…

Engaging with Mathematics in the Kindergarten. Orchestrating a Fairy Tale through Questioning and Use of Tools

ERIC Educational Resources Information Center

Carlsen, Martin

2013-01-01

The aim of this study is to analyse how a kindergarten teacher orchestrated a mathematical activity involving a fairy tale. Taking a sociocultural perspective on learning and development, naturally occurring talk-in-interaction has been analysed in order to scrutinise the subtleties of the orchestration. The fairy tale "Goldilocks and the…

Big data analytics in immunology: a knowledge-based approach.

PubMed

Zhang, Guang Lan; Sun, Jing; Chitkushev, Lou; Brusic, Vladimir

2014-01-01

With the vast amount of immunological data available, immunology research is entering the big data era. These data vary in granularity, quality, and complexity and are stored in various formats, including publications, technical reports, and databases. The challenge is to make the transition from data to actionable knowledge and wisdom and bridge the knowledge gap and application gap. We report a knowledge-based approach based on a framework called KB-builder that facilitates data mining by enabling fast development and deployment of web-accessible immunological data knowledge warehouses. Immunological knowledge discovery relies heavily on both the availability of accurate, up-to-date, and well-organized data and the proper analytics tools. We propose the use of knowledge-based approaches by developing knowledgebases combining well-annotated data with specialized analytical tools and integrating them into analytical workflow. A set of well-defined workflow types with rich summarization and visualization capacity facilitates the transformation from data to critical information and knowledge. By using KB-builder, we enabled streamlining of normally time-consuming processes of database development. The knowledgebases built using KB-builder will speed up rational vaccine design by providing accurate and well-annotated data coupled with tailored computational analysis tools and workflow.

Executing SADI services in Galaxy.

PubMed

Aranguren, Mikel Egaña; González, Alejandro Rodríguez; Wilkinson, Mark D

2014-01-01

In recent years Galaxy has become a popular workflow management system in bioinformatics, due to its ease of installation, use and extension. The availability of Semantic Web-oriented tools in Galaxy, however, is limited. This is also the case for Semantic Web Services such as those provided by the SADI project, i.e. services that consume and produce RDF. Here we present SADI-Galaxy, a tool generator that deploys selected SADI Services as typical Galaxy tools. SADI-Galaxy is a Galaxy tool generator: through SADI-Galaxy, any SADI-compliant service becomes a Galaxy tool that can participate in other out-standing features of Galaxy such as data storage, history, workflow creation, and publication. Galaxy can also be used to execute and combine SADI services as it does with other Galaxy tools. Finally, we have semi-automated the packing and unpacking of data into RDF such that other Galaxy tools can easily be combined with SADI services, plugging the rich SADI Semantic Web Service environment into the popular Galaxy ecosystem. SADI-Galaxy bridges the gap between Galaxy, an easy to use but "static" workflow system with a wide user-base, and SADI, a sophisticated, semantic, discovery-based framework for Web Services, thus benefiting both user communities.

SensorWeb 3G: Extending On-Orbit Sensor Capabilities to Enable Near Realtime User Configurability

NASA Technical Reports Server (NTRS)

Mandl, Daniel; Cappelaere, Pat; Frye, Stuart; Sohlberg, Rob; Ly, Vuong; Chien, Steve; Tran, Daniel; Davies, Ashley; Sullivan, Don; Ames, Troy;

Injury and the orchestral environment: part II. Organisational culture, behavioural norms, and attitudes to injury.

PubMed

Rickert, Dale Ll; Barrett, Margaret S; Ackermann, Bronwen J

2014-06-01

The organisational culture, behavioural norms, and attitudes of a workplace have a profound influence on levels of injury and illness amongst its workers. While this is well established in Work Health and Safety literature, very little research has attempted to understand the influence of organisational culture on injury risk in the orchestral profession. To address this, the current study aimed to investigate the influence of organisational culture on injury outcomes for orchestral musicians. Using a qualitative case study methodology, in-depth semi-structured interviews were undertaken with 10 professional orchestral cellists (2 freelance and 8 fulltime members) from a single Australian orchestra. After initial data analysis, further interviews were undertaken with a set of 5 orchestral management staff as a means of data triangulation. All data were analysed using a themes-based "analysis of narrative" approach. The findings indicate that an orchestral culture exists in which musicians see injury as a sign of weakness, failure, and poor musicianship. Such negative perceptions of injury influence musicians to play through considerable levels of pain and continue performing with injuries. Because of perceived judgment from the orchestral group, musicians were found to conceal injuries from colleagues and management staff. Freelance musicians felt that disclosing injuries may lead to decreased work opportunities, and both full-time and casual musicians felt that "opening up" about injury may subject them to group judgment about their technique or musicianship. The study suggests education measures which may be effective at influencing individual behaviours and attitudes as well as cultural change initiatives which could lead to long-term positive health outcomes in the orchestral workplace.

The Symbiotic Relationship between Scientific Workflow and Provenance (Invited)

NASA Astrophysics Data System (ADS)

Stephan, E.

2010-12-01

The purpose of this presentation is to describe the symbiotic nature of scientific workflows and provenance. We will also discuss the current trends and real world challenges facing these two distinct research areas. Although motivated differently, the needs of the international science communities are the glue that binds this relationship together. Understanding and articulating the science drivers to these communities is paramount as these technologies evolve and mature. Originally conceived for managing business processes, workflows are now becoming invaluable assets in both computational and experimental sciences. These reconfigurable, automated systems provide essential technology to perform complex analyses by coupling together geographically distributed disparate data sources and applications. As a result, workflows are capable of higher throughput in a shorter amount of time than performing the steps manually. Today many different workflow products exist; these could include Kepler and Taverna or similar products like MeDICI, developed at PNNL, that are standardized on the Business Process Execution Language (BPEL). Provenance, originating from the French term Provenir “to come from”, is used to describe the curation process of artwork as art is passed from owner to owner. The concept of provenance was adopted by digital libraries as a means to track the lineage of documents while standards such as the DublinCore began to emerge. In recent years the systems science community has increasingly expressed the need to expand the concept of provenance to formally articulate the history of scientific data. Communities such as the International Provenance and Annotation Workshop (IPAW) have formalized a provenance data model. The Open Provenance Model, and the W3C is hosting a provenance incubator group featuring the Proof Markup Language. Although both workflows and provenance have risen from different communities and operate independently, their mutual success is tied together, forming a symbiotic relationship where research and development advances in one effort can provide tremendous benefits to the other. For example, automating provenance extraction within scientific applications is still a relatively new concept; the workflow engine provides the framework to capture application specific operations, inputs, and resulting data. It provides a description of the process history and data flow by wrapping workflow components around the applications and data sources. On the other hand, a lack of cooperation between workflows and provenance can inhibit usefulness of both to science. Blindly tracking the execution history without having a true understanding of what kinds of questions end users may have makes the provenance indecipherable to the target users. Over the past nine years PNNL has been actively involved in provenance research in support of computational chemistry, molecular dynamics, biology, hydrology, and climate. PNNL has also been actively involved in efforts by the international community to develop open standards for provenance and the development of architectures to support provenance capture, storage, and querying. This presentation will provide real world use cases of how provenance and workflow can be leveraged and implemented to meet different needs and the challenges that lie ahead.

Optimization of Orchestral Layouts Based on Instrument Directivity Patterns

NASA Astrophysics Data System (ADS)

Stroud, Nathan Paul

The experience of hearing an exceptional symphony orchestra perform in an excel- lent concert hall can be profound and moving, causing a level of excitement not often reached for listeners. Romantic period style orchestral music, recognized for validating the use of intense emotion for aesthetic pleasure, was the last significant development in the history of the orchestra. In an age where orchestral popularity is waning, the possibil- ity of evolving the orchestral sound in our modern era exists through the combination of our current understanding of instrument directivity patterns and their interaction with architectural acoustics. With the aid of wave field synthesis (WFS), newly proposed variations on orchestral layouts are tested virtually using a 64-channel WFS array. Each layout is objectively and subjectively compared for determination of which layout could optimize the sound of the orchestra and revitalize the excitement of the performance.

Multi-purpose presentation techniques for geoscientific data in various media

NASA Astrophysics Data System (ADS)

Rink, Karsten; Bilke, Lars

2014-05-01

The intuitive presentation of the progression of complex geoscientific phenomena is often an underrated part of the modelling- and simulation workflow. Compiling such a presentation allows to easily communicate progress in joint research projects between participants with different backgrounds. Also, adequate 3D visualisations are usually easier to understand when presenting research results to stakeholders as well as the general public and critical information is conveyed in a more comprehensible manner. We established a workflow that is based on integration and preprocessing of multiple geoscientific data sets in a suitable framework such as the OpenGeoSys Data Explorer or ParaView. After choosing an adequate visual representation of the data in these frameworks, custom-made interfaces are employed to export the data to presentation frameworks. For instance, using the Unity 3D Engine allows to implement interaction techniques such as adding camera paths, concentrating on specific subsets of the data or scene, blending multiple data sets, etc. While a general sequence of the presentation can be predefined, interactive navigation is still possible and allows to focus on particular interests of the audience. Established interfaces and frameworks allow to display existing presentations in multiple ways, including virtual reality environments, novel hardware such as head-mounted displays like the Occulus Rift, or even websites presenting 3D content. Furthermore, the content can be redistributed as an executable for use on arbitrary machines. This versatility enables the use of prepared presentations for a multitude of occasions including exchange of intermediary result to partners in cooperate projects, reports at conferences, the defense of research projects, or use in training courses or for tutorials.

Knowledge Discovery, Integration and Communication for Extreme Weather and Flood Resilience Using Artificial Intelligence: Flood AI Alpha

NASA Astrophysics Data System (ADS)

Demir, I.; Sermet, M. Y.

2016-12-01

Nobody is immune from extreme events or natural hazards that can lead to large-scale consequences for the nation and public. One of the solutions to reduce the impacts of extreme events is to invest in improving resilience with the ability to better prepare, plan, recover, and adapt to disasters. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This abstracts presents our project on developing a resilience framework for flooding to improve societal preparedness with objectives; (a) develop a generalized ontology for extreme events with primary focus on flooding; (b) develop a knowledge engine with voice recognition, artificial intelligence, natural language processing, and inference engine. The knowledge engine will utilize the flood ontology and concepts to connect user input to relevant knowledge discovery outputs on flooding; (c) develop a data acquisition and processing framework from existing environmental observations, forecast models, and social networks. The system will utilize the framework, capabilities and user base of the Iowa Flood Information System (IFIS) to populate and test the system; (d) develop a communication framework to support user interaction and delivery of information to users. The interaction and delivery channels will include voice and text input via web-based system (e.g. IFIS), agent-based bots (e.g. Microsoft Skype, Facebook Messenger), smartphone and augmented reality applications (e.g. smart assistant), and automated web workflows (e.g. IFTTT, CloudWork) to open the knowledge discovery for flooding to thousands of community extensible web workflows.

Glocal clinical registries: pacemaker registry design and implementation for global and local integration--methodology and case study.

PubMed

da Silva, Kátia Regina; Costa, Roberto; Crevelari, Elizabeth Sartori; Lacerda, Marianna Sobral; de Moraes Albertini, Caio Marcos; Filho, Martino Martinelli; Santana, José Eduardo; Vissoci, João Ricardo Nickenig; Pietrobon, Ricardo; Barros, Jacson V

2013-01-01

The ability to apply standard and interoperable solutions for implementing and managing medical registries as well as aggregate, reproduce, and access data sets from legacy formats and platforms to advanced standard formats and operating systems are crucial for both clinical healthcare and biomedical research settings. Our study describes a reproducible, highly scalable, standard framework for a device registry implementation addressing both local data quality components and global linking problems. We developed a device registry framework involving the following steps: (1) Data standards definition and representation of the research workflow, (2) Development of electronic case report forms using REDCap (Research Electronic Data Capture), (3) Data collection according to the clinical research workflow and, (4) Data augmentation by enriching the registry database with local electronic health records, governmental database and linked open data collections, (5) Data quality control and (6) Data dissemination through the registry Web site. Our registry adopted all applicable standardized data elements proposed by American College Cardiology / American Heart Association Clinical Data Standards, as well as variables derived from cardiac devices randomized trials and Clinical Data Interchange Standards Consortium. Local interoperability was performed between REDCap and data derived from Electronic Health Record system. The original data set was also augmented by incorporating the reimbursed values paid by the Brazilian government during a hospitalization for pacemaker implantation. By linking our registry to the open data collection repository Linked Clinical Trials (LinkedCT) we found 130 clinical trials which are potentially correlated with our pacemaker registry. This study demonstrates how standard and reproducible solutions can be applied in the implementation of medical registries to constitute a re-usable framework. Such approach has the potential to facilitate data integration between healthcare and research settings, also being a useful framework to be used in other biomedical registries.

Model Diagnostics for the Department of Energy's Accelerated Climate Modeling for Energy (ACME) Project

NASA Astrophysics Data System (ADS)

Smith, B.

2015-12-01

In 2014, eight Department of Energy (DOE) national laboratories, four academic institutions, one company, and the National Centre for Atmospheric Research combined forces in a project called Accelerated Climate Modeling for Energy (ACME) with the goal to speed Earth system model development for climate and energy. Over the planned 10-year span, the project will conduct simulations and modeling on DOE's most powerful high-performance computing systems at Oak Ridge, Argonne, and Lawrence Berkeley Leadership Compute Facilities. A key component of the ACME project is the development of an interactive test bed for the advanced Earth system model. Its execution infrastructure will accelerate model development and testing cycles. The ACME Workflow Group is leading the efforts to automate labor-intensive tasks, provide intelligent support for complex tasks and reduce duplication of effort through collaboration support. As part of this new workflow environment, we have created a diagnostic, metric, and intercomparison Python framework, called UVCMetrics, to aid in the testing-to-production execution of the ACME model. The framework exploits similarities among different diagnostics to compactly support diagnosis of new models. It presently focuses on atmosphere and land but is designed to support ocean and sea ice model components as well. This framework is built on top of the existing open-source software framework known as the Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT). Because of its flexible framework design, scientists and modelers now can generate thousands of possible diagnostic outputs. These diagnostics can compare model runs, compare model vs. observation, or simply verify a model is physically realistic. Additional diagnostics are easily integrated into the framework, and our users have already added several. Diagnostics can be generated, viewed, and manipulated from the UV-CDAT graphical user interface, Python command line scripts and programs, and web browsers. The framework is designed to be scalable to large datasets, yet easy to use and familiar to scientists using previous tools. Integration in the ACME overall user interface facilitates data publication, further analysis, and quick feedback to model developers and scientists making component or coupled model runs.

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

McCaskey, Alexander J.

There is a lack of state-of-the-art HPC simulation tools for simulating general quantum computing. Furthermore, there are no real software tools that integrate current quantum computers into existing classical HPC workflows. This product, the Quantum Virtual Machine (QVM), solves this problem by providing an extensible framework for pluggable virtual, or physical, quantum processing units (QPUs). It enables the execution of low level quantum assembly codes and returns the results of such executions.

Agent-Based Scientific Workflow Composition

NASA Astrophysics Data System (ADS)

Barker, A.; Mann, B.

2006-07-01

Agents are active autonomous entities that interact with one another to achieve their objectives. This paper addresses how these active agents are a natural fit to consume the passive Service Oriented Architecture which is found in Internet and Grid Systems, in order to compose, coordinate and execute e-Science experiments. A framework is introduced which allows an e-Science experiment to be described as a MultiAgent System.

INDIGO-DataCloud solutions for Earth Sciences

NASA Astrophysics Data System (ADS)

Aguilar Gómez, Fernando; de Lucas, Jesús Marco; Fiore, Sandro; Monna, Stephen; Chen, Yin

2017-04-01

INDIGO-DataCloud (https://www.indigo-datacloud.eu/) is a European Commission funded project aiming to develop a data and computing platform targeting scientific communities, deployable on multiple hardware and provisioned over hybrid (private or public) e-infrastructures. The development of INDIGO solutions covers the different layers in cloud computing (IaaS, PaaS, SaaS), and provides tools to exploit resources like HPC or GPGPUs. INDIGO is oriented to support European Scientific research communities, that are well represented in the project. Twelve different Case Studies have been analyzed in detail from different fields: Biological & Medical sciences, Social sciences & Humanities, Environmental and Earth sciences and Physics & Astrophysics. INDIGO-DataCloud provides solutions to emerging challenges in Earth Science like: -Enabling an easy deployment of community services at different cloud sites. Many Earth Science research infrastructures often involve distributed observation stations across countries, and also have distributed data centers to support the corresponding data acquisition and curation. There is a need to easily deploy new data center services while the research infrastructure continuous spans. As an example: LifeWatch (ESFRI, Ecosystems and Biodiversity) uses INDIGO solutions to manage the deployment of services to perform complex hydrodynamics and water quality modelling over a Cloud Computing environment, predicting algae blooms, using the Docker technology: TOSCA requirement description, Docker repository, Orchestrator for deployment, AAI (AuthN, AuthZ) and OneData (Distributed Storage System). -Supporting Big Data Analysis. Nowadays, many Earth Science research communities produce large amounts of data and and are challenged by the difficulties of processing and analysing it. A climate models intercomparison data analysis case study for the European Network for Earth System Modelling (ENES) community has been setup, based on the Ophidia big data analysis framework and the Kepler workflow management system. Such services normally involve a large and distributed set of data and computing resources. In this regard, this case study exploits the INDIGO PaaS for a flexible and dynamic allocation of the resources at the infrastructural level. -Providing Distributed Data Storage Solutions. In order to allow scientific communities to perform heavy computation on huge datasets, INDIGO provides global data access solutions allowing researchers to access data in a distributed environment like fashion regardless of its location, and also to publish and share their research results with public or close communities. INDIGO solutions that support the access to distributed data storage (OneData) are being tested on EMSO infrastructure (Ocean Sciences and Geohazards) data. Another aspect of interest for the EMSO community is in efficient data processing by exploiting INDIGO services like PaaS Orchestrator. Further, for HPC exploitation, a new solution named Udocker has been implemented, enabling users to execute docker containers in supercomputers, without requiring administration privileges. This presentation will overview INDIGO solutions that are interesting and useful for Earth science communities and will show how they can be applied to other Case Studies.

A Descriptive Study of High School and University Students' Focus of Attention in Fast and Slow Orchestral Excerpts

ERIC Educational Resources Information Center

MacLeod, Rebecca B.; Geringer, John M.; Scott, Laurie

2009-01-01

The purpose of this study was to investigate listener discrimination of orchestral performances and to ascertain focus of listener attention to technical and expressive music elements of those performances. High School (n = 84) and University (n = 84) music students listened to four orchestral excerpts: two slow/soft excerpts and two fast/loud…

Challenge of Supporting Vocational Learning: Empowering Collaboration in a Scripted 3D Game--How Does Teachers' Real-Time Orchestration Make a Difference?

ERIC Educational Resources Information Center

Hamalainen, Raija; Oksanen, Kimmo

2012-01-01

Along with the development of new technologies, orchestrating computer-supported collaborative learning (CSCL) has become a topic of discussion because new learning spaces challenge teacher to support collaborative learning in new ways. However, despite the optimistic notions of teachers' orchestration in CSCL situations, there are still no…

Nature of orchestral noise.

PubMed

O'Brien, Ian; Wilson, Wayne; Bradley, Andrew

2008-08-01

Professional orchestral musicians are at risk of exposure to excessive noise when at work. This is an industry-wide problem that threatens not only the hearing of orchestral musicians but also the way orchestras operate. The research described in this paper recorded noise levels within a professional orchestra over three years in order to provide greater insight to the orchestral noise environment; to guide future research into orchestral noise management and hearing conservation strategies; and to provide a basis for the future education of musicians and their managers. Every rehearsal, performance, and recording from May 2004 to May 2007 was monitored, with the woodwind, brass, and percussion sections monitored in greatest detail. The study recorded dBALEQ and dBC peak data, which are presented in graphical form with accompanying summarized data tables. The findings indicate that the principal trumpet, first and third horns, and principal trombone are at greatest risk of exposure to excessive sustained noise levels and that the percussion and timpani are at greatest risk of exposure to excessive peak noise levels. However, the findings also strongly support the notion that the true nature of orchestral noise is a great deal more complex than this simple statement would imply.

Integrating data from an online diabetes prevention program into an electronic health record and clinical workflow, a design phase usability study.

PubMed

Mishuris, Rebecca Grochow; Yoder, Jordan; Wilson, Dan; Mann, Devin

2016-07-11

Health information is increasingly being digitally stored and exchanged. The public is regularly collecting and storing health-related data on their own electronic devices and in the cloud. Diabetes prevention is an increasingly important preventive health measure, and diet and exercise are key components of this. Patients are turning to online programs to help them lose weight. Despite primary care physicians being important in patients' weight loss success, there is no exchange of information between the primary care provider (PCP) and these online weight loss programs. There is an emerging opportunity to integrate this data directly into the electronic health record (EHR), but little is known about what information to share or how to share it most effectively. This study aims to characterize the preferences of providers concerning the integration of externally generated lifestyle modification data into a primary care EHR workflow. We performed a qualitative study using two rounds of semi-structured interviews with primary care providers. We used an iterative design process involving primary care providers, health information technology software developers and health services researchers to develop the interface. Using grounded-theory thematic analysis 4 themes emerged from the interviews: 1) barriers to establishing healthy lifestyles, 2) features of a lifestyle modification program, 3) reporting of outcomes to the primary care provider, and 4) integration with primary care. These themes guided the rapid-cycle agile design process of an interface of data from an online diabetes prevention program into the primary care EHR workflow. The integration of external health-related data into the EHR must be embedded into the provider workflow in order to be useful to the provider and beneficial for the patient. Accomplishing this requires evaluation of that clinical workflow during software design. The development of this novel interface used rapid cycle iterative design, early involvement by providers, and usability testing methodology. This provides a framework for how to integrate external data into provider workflow in efficient and effective ways. There is now the potential to realize the importance of having this data available in the clinical setting for patient engagement and health outcomes.

Leveraging workflow control patterns in the domain of clinical practice guidelines.

PubMed

Kaiser, Katharina; Marcos, Mar

2016-02-10

Clinical practice guidelines (CPGs) include recommendations describing appropriate care for the management of patients with a specific clinical condition. A number of representation languages have been developed to support executable CPGs, with associated authoring/editing tools. Even with tool assistance, authoring of CPG models is a labor-intensive task. We aim at facilitating the early stages of CPG modeling task. In this context, we propose to support the authoring of CPG models based on a set of suitable procedural patterns described in an implementation-independent notation that can be then semi-automatically transformed into one of the alternative executable CPG languages. We have started with the workflow control patterns which have been identified in the fields of workflow systems and business process management. We have analyzed the suitability of these patterns by means of a qualitative analysis of CPG texts. Following our analysis we have implemented a selection of workflow patterns in the Asbru and PROforma CPG languages. As implementation-independent notation for the description of patterns we have chosen BPMN 2.0. Finally, we have developed XSLT transformations to convert the BPMN 2.0 version of the patterns into the Asbru and PROforma languages. We showed that although a significant number of workflow control patterns are suitable to describe CPG procedural knowledge, not all of them are applicable in the context of CPGs due to their focus on single-patient care. Moreover, CPGs may require additional patterns not included in the set of workflow control patterns. We also showed that nearly all the CPG-suitable patterns can be conveniently implemented in the Asbru and PROforma languages. Finally, we demonstrated that individual patterns can be semi-automatically transformed from a process specification in BPMN 2.0 to executable implementations in these languages. We propose a pattern and transformation-based approach for the development of CPG models. Such an approach can form the basis of a valid framework for the authoring of CPG models. The identification of adequate patterns and the implementation of transformations to convert patterns from a process specification into different executable implementations are the first necessary steps for our approach.

MO-D-213-06: Quantitative Image Quality Metrics Are for Physicists, Not Radiologists: How to Communicate to Your Radiologists Using Their Language

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

Szczykutowicz, T; Rubert, N; Ranallo, F

Purpose: A framework for explaining differences in image quality to non-technical audiences in medial imaging is needed. Currently, this task is something that is learned “on the job.” The lack of a formal methodology for communicating optimal acquisition parameters into the clinic effectively mitigates many technological advances. As a community, medical physicists need to be held responsible for not only advancing image science, but also for ensuring its proper use in the clinic. This work outlines a framework that bridges the gap between the results from quantitative image quality metrics like detectability, MTF, and NPS and their effect on specificmore » anatomical structures present in diagnostic imaging tasks. Methods: Specific structures of clinical importance were identified for a body, an extremity, a chest, and a temporal bone protocol. Using these structures, quantitative metrics were used to identify the parameter space that should yield optimal image quality constrained within the confines of clinical logistics and dose considerations. The reading room workflow for presenting the proposed changes for imaging each of these structures is presented. The workflow consists of displaying images for physician review consisting of different combinations of acquisition parameters guided by quantitative metrics. Examples of using detectability index, MTF, NPS, noise and noise non-uniformity are provided. During review, the physician was forced to judge the image quality solely on those features they need for diagnosis, not on the overall “look” of the image. Results: We found that in many cases, use of this framework settled mis-agreements between physicians. Once forced to judge images on the ability to detect specific structures inter reader agreement was obtained. Conclusion: This framework will provide consulting, research/industrial, or in-house physicists with clinically relevant imaging tasks to guide reading room image review. This framework avoids use of the overall “look” or “feel” to dictate acquisition parameter selection. Equipment grants GE Healthcare.« less

AMP: a science-driven web-based application for the TeraGrid

NASA Astrophysics Data System (ADS)

Woitaszek, M.; Metcalfe, T.; Shorrock, I.

The Asteroseismic Modeling Portal (AMP) provides a web-based interface for astronomers to run and view simulations that derive the properties of Sun-like stars from observations of their pulsation frequencies. In this paper, we describe the architecture and implementation of AMP, highlighting the lightweight design principles and tools used to produce a functional fully-custom web-based science application in less than a year. Targeted as a TeraGrid science gateway, AMP's architecture and implementation are intended to simplify its orchestration of TeraGrid computational resources. AMP's web-based interface was developed as a traditional standalone database-backed web application using the Python-based Django web development framework, allowing us to leverage the Django framework's capabilities while cleanly separating the user interface development from the grid interface development. We have found this combination of tools flexible and effective for rapid gateway development and deployment.

Clinical Knowledge Governance Framework for Nationwide Data Infrastructure Projects.

PubMed

Wulff, Antje; Haarbrandt, Birger; Marschollek, Michael

2018-01-01

The availability of semantically-enriched and interoperable clinical information models is crucial for reusing once collected data across institutions like aspired in the German HiGHmed project. Funded by the Federal Ministry of Education and Research, this nationwide data infrastructure project adopts the openEHR approach for semantic modelling. Here, strong governance is required to define high-quality and reusable models. Design of a clinical knowledge governance framework for openEHR modelling in cross-institutional settings like HiGHmed. Analysis of successful practices from international projects, published ideas on archetype governance and own modelling experiences as well as modelling of BPMN processes. We designed a framework by presenting archetype variations, roles and responsibilities, IT support and modelling workflows. Our framework has great potential to make the openEHR modelling efforts manageable. Because practical experiences are rare, prospectively our work will be predestinated to evaluate the benefits of such structured governance approaches.

A Computational Framework for Automation of Point Defect Calculations

NASA Astrophysics Data System (ADS)

Goyal, Anuj; Gorai, Prashun; Peng, Haowei; Lany, Stephan; Stevanovic, Vladan; National Renewable Energy Laboratory, Golden, Colorado 80401 Collaboration

A complete and rigorously validated open-source Python framework to automate point defect calculations using density functional theory has been developed. The framework provides an effective and efficient method for defect structure generation, and creation of simple yet customizable workflows to analyze defect calculations. The package provides the capability to compute widely accepted correction schemes to overcome finite-size effects, including (1) potential alignment, (2) image-charge correction, and (3) band filling correction to shallow defects. Using Si, ZnO and In2O3as test examples, we demonstrate the package capabilities and validate the methodology. We believe that a robust automated tool like this will enable the materials by design community to assess the impact of point defects on materials performance. National Renewable Energy Laboratory, Golden, Colorado 80401.

Integrating UIMA annotators in a web-based text processing framework.

PubMed

Chen, Xiang; Arnold, Corey W

2013-01-01

The Unstructured Information Management Architecture (UIMA) [1] framework is a growing platform for natural language processing (NLP) applications. However, such applications may be difficult for non-technical users deploy. This project presents a web-based framework that wraps UIMA-based annotator systems into a graphical user interface for researchers and clinicians, and a web service for developers. An annotator that extracts data elements from lung cancer radiology reports is presented to illustrate the use of the system. Annotation results from the web system can be exported to multiple formats for users to utilize in other aspects of their research and workflow. This project demonstrates the benefits of a lay-user interface for complex NLP applications. Efforts such as this can lead to increased interest and support for NLP work in the clinical domain.

Meta-learning framework applied in bioinformatics inference system design.

PubMed

Arredondo, Tomás; Ormazábal, Wladimir

2015-01-01

This paper describes a meta-learner inference system development framework which is applied and tested in the implementation of bioinformatic inference systems. These inference systems are used for the systematic classification of the best candidates for inclusion in bacterial metabolic pathway maps. This meta-learner-based approach utilises a workflow where the user provides feedback with final classification decisions which are stored in conjunction with analysed genetic sequences for periodic inference system training. The inference systems were trained and tested with three different data sets related to the bacterial degradation of aromatic compounds. The analysis of the meta-learner-based framework involved contrasting several different optimisation methods with various different parameters. The obtained inference systems were also contrasted with other standard classification methods with accurate prediction capabilities observed.

Salvus: A scalable software suite for full-waveform modelling & inversion

NASA Astrophysics Data System (ADS)

Afanasiev, M.; Boehm, C.; van Driel, M.; Krischer, L.; Fichtner, A.

2017-12-01

Full-waveform inversion (FWI), whether at the lab, exploration, or planetary scale, requires the cooperation of five principal components. (1) The geometry of the domain needs to be properly discretized and an initial guess of the model parameters must be projected onto it; (2) Large volumes of recorded waveform data must be collected, organized, and processed; (3) Synthetic waveform data must be efficiently and accurately computed through complex domains; (4) Suitable misfit functions and optimization techniques must be used to relate discrepancies in data space to perturbations in the model; and (5) Some form of workflow management must be employed to schedule and run (1) - (4) in the correct order. Each one of these components can represent a formidable technical challenge which redirects energy from the true task at hand: using FWI to extract new information about some underlying continuum.In this presentation we give an overview of the current status of the Salvus software suite, which was introduced to address the challenges listed above. Specifically, we touch on (1) salvus_mesher, which eases the discretization of complex Earth models into hexahedral meshes; (2) salvus_seismo, which integrates with LASIF and ObsPy to streamline the processing and preparation of seismic data; (3) salvus_wave, a high-performance and scalable spectral-element solver capable of simulating waveforms through general unstructured 2- and 3-D domains, and (4) salvus_opt, an optimization toolbox specifically designed for full-waveform inverse problems. Tying everything together, we also discuss (5) salvus_flow: a workflow package designed to orchestrate and manage the rest of the suite. It is our hope that these developments represent a step towards the automation of large-scale seismic waveform inversion, while also lowering the barrier of entry for new applications. We include several examples of Salvus' use in (extra-) planetary seismology, non-destructive testing, and medical imaging.

Design Description for Team-Based Execution of Autonomous Missions (TEAM), Spiral 1

DTIC Science & Technology

2008-11-18

TEAM), Spiral 1 Doc. #: Version: 1.0 Date: November 18, 2008 Page 12 of 39 Visualization Framework (WorldWind) Hibernate / Hibernate ...Spatial hibernate -properties XML Mapping WCS WFSWMS Enterprise Service Bus (Mule) Messaging, Data Transformation, Intelligent Routing Workflow Engine...government selected solutions. Neither these nor Mule® are deliverable, but the government may opt to use them if it so chooses. jBPM, java Business

Adaptive Acquisition: An Evolving Framework for Tailoring Engineering and Procurement of Defense Systems

DTIC Science & Technology

2017-01-31

mapping critical business workflows and then optimizing them with appropriate evolutionary technology choices is often called “ Product Line Architecture... technologies , products , services, and processes, and the USG evaluates them against its 360o requirements objectives, and refines them as appropriate, clarity...in rapidly evolving technological domains (e.g. by applying best commercial practices for open standard product line architecture.) An MP might be

The LHCb software and computing upgrade for Run 3: opportunities and challenges

NASA Astrophysics Data System (ADS)

Bozzi, C.; Roiser, S.; LHCb Collaboration

2017-10-01

The LHCb detector will be upgraded for the LHC Run 3 and will be readout at 30 MHz, corresponding to the full inelastic collision rate, with major implications on the full software trigger and offline computing. If the current computing model and software framework are kept, the data storage capacity and computing power required to process data at this rate, and to generate and reconstruct equivalent samples of simulated events, will exceed the current capacity by at least one order of magnitude. A redesign of the software framework, including scheduling, the event model, the detector description and the conditions database, is needed to fully exploit the computing power of multi-, many-core architectures, and coprocessors. Data processing and the analysis model will also change towards an early streaming of different data types, in order to limit storage resources, with further implications for the data analysis workflows. Fast simulation options will allow to obtain a reasonable parameterization of the detector response in considerably less computing time. Finally, the upgrade of LHCb will be a good opportunity to review and implement changes in the domains of software design, test and review, and analysis workflow and preservation. In this contribution, activities and recent results in all the above areas are presented.

Automated Finite State Workflow for Distributed Data Production

NASA Astrophysics Data System (ADS)

Hajdu, L.; Didenko, L.; Lauret, J.; Amol, J.; Betts, W.; Jang, H. J.; Noh, S. Y.

2016-10-01

In statistically hungry science domains, data deluges can be both a blessing and a curse. They allow the narrowing of statistical errors from known measurements, and open the door to new scientific opportunities as research programs mature. They are also a testament to the efficiency of experimental operations. However, growing data samples may need to be processed with little or no opportunity for huge increases in computing capacity. A standard strategy has thus been to share resources across multiple experiments at a given facility. Another has been to use middleware that “glues” resources across the world so they are able to locally run the experimental software stack (either natively or virtually). We describe a framework STAR has successfully used to reconstruct a ~400 TB dataset consisting of over 100,000 jobs submitted to a remote site in Korea from STAR's Tier 0 facility at the Brookhaven National Laboratory. The framework automates the full workflow, taking raw data files from tape and writing Physics-ready output back to tape without operator or remote site intervention. Through hardening we have demonstrated 97(±2)% efficiency, over a period of 7 months of operation. The high efficiency is attributed to finite state checking with retries to encourage resilience in the system over capricious and fallible infrastructure.

Workflow management in large distributed systems

NASA Astrophysics Data System (ADS)

Legrand, I.; Newman, H.; Voicu, R.; Dobre, C.; Grigoras, C.

2011-12-01

The MonALISA (Monitoring Agents using a Large Integrated Services Architecture) framework provides a distributed service system capable of controlling and optimizing large-scale, data-intensive applications. An essential part of managing large-scale, distributed data-processing facilities is a monitoring system for computing facilities, storage, networks, and the very large number of applications running on these systems in near realtime. All this monitoring information gathered for all the subsystems is essential for developing the required higher-level services—the components that provide decision support and some degree of automated decisions—and for maintaining and optimizing workflow in large-scale distributed systems. These management and global optimization functions are performed by higher-level agent-based services. We present several applications of MonALISA's higher-level services including optimized dynamic routing, control, data-transfer scheduling, distributed job scheduling, dynamic allocation of storage resource to running jobs and automated management of remote services among a large set of grid facilities.

Fall TIPS: strategies to promote adoption and use of a fall prevention toolkit.

PubMed

Dykes, Patricia C; Carroll, Diane L; Hurley, Ann; Gersh-Zaremski, Ronna; Kennedy, Ann; Kurowski, Jan; Tierney, Kim; Benoit, Angela; Chang, Frank; Lipsitz, Stuart; Pang, Justine; Tsurkova, Ruslana; Zuyov, Lyubov; Middleton, Blackford

2009-11-14

Patient falls are serious problems in hospitals. Risk factors for falls are well understood and nurses routinely assess for fall risk on all hospitalized patients. However, the link from nursing assessment of fall risk, to identification and communication of tailored interventions to prevent falls is yet to be established. The Fall TIPS (Tailoring Interventions for Patient Safety) Toolkit was developed to leverage existing practices and workflows and to employ information technology to improve fall prevention practices. The purpose of this paper is to describe the Fall TIPS Toolkit and to report on strategies used to drive adoption of the Toolkit in four acute care hospitals. Using the IHI "Framework for Spread" as a conceptual model, the research team describes the "spread" of the Fall TIPS Toolkit as means to integrate effective fall prevention practices into the workflow of interdisciplinary caregivers, patients and family members.

Multi-core processing and scheduling performance in CMS

NASA Astrophysics Data System (ADS)

Hernández, J. M.; Evans, D.; Foulkes, S.

2012-12-01

Commodity hardware is going many-core. We might soon not be able to satisfy the job memory needs per core in the current single-core processing model in High Energy Physics. In addition, an ever increasing number of independent and incoherent jobs running on the same physical hardware not sharing resources might significantly affect processing performance. It will be essential to effectively utilize the multi-core architecture. CMS has incorporated support for multi-core processing in the event processing framework and the workload management system. Multi-core processing jobs share common data in memory, such us the code libraries, detector geometry and conditions data, resulting in a much lower memory usage than standard single-core independent jobs. Exploiting this new processing model requires a new model in computing resource allocation, departing from the standard single-core allocation for a job. The experiment job management system needs to have control over a larger quantum of resource since multi-core aware jobs require the scheduling of multiples cores simultaneously. CMS is exploring the approach of using whole nodes as unit in the workload management system where all cores of a node are allocated to a multi-core job. Whole-node scheduling allows for optimization of the data/workflow management (e.g. I/O caching, local merging) but efficient utilization of all scheduled cores is challenging. Dedicated whole-node queues have been setup at all Tier-1 centers for exploring multi-core processing workflows in CMS. We present the evaluation of the performance scheduling and executing multi-core workflows in whole-node queues compared to the standard single-core processing workflows.

OpenLMD, multimodal monitoring and control of LMD processing

NASA Astrophysics Data System (ADS)

Rodríguez-Araújo, Jorge; García-Díaz, Antón

2017-02-01

This paper presents OpenLMD, a novel open-source solution for on-line multimodal monitoring of Laser Metal Deposition (LMD). The solution is also applicable to a wider range of laser-based applications that require on-line control (e.g. laser welding). OpenLMD is a middleware that enables the orchestration and virtualization of a LMD robot cell, using several open-source frameworks (e.g. ROS, OpenCV, PCL). The solution also allows reconfiguration by easy integration of multiple sensors and processing equipment. As a result, OpenLMD delivers significant advantages over existing monitoring and control approaches, such as improved scalability, and multimodal monitoring and data sharing capabilities.

Epigenetics Mechanisms in Alzheimer’s disease

PubMed Central

Mastroeni, Diego; Grover, Andrew; Delvaux, Elaine; Whiteside, Charisse; Coleman, Paul D.; Rogers, Joseph

2011-01-01

Epigenetic modifications help orchestrate sweeping developmental, aging, and disease-causing changes in phenotype by altering transcriptional activity in multiple genes spanning multiple biologic pathways. Although previous epigenetic research has focused primarily on dividing cells, particularly in cancer, recent studies have shown rapid, dynamic, and persistent epigenetic modifications in neurons that have significant neuroendocrine, neurophysiologic, and neurodegenerative consequences. Here, we provide a review of the major mechanisms for epigenetic modification and how they are reportedly altered in aging and Alzheimer’s disease (AD). Because of their reach across the genome, epigenetic mechanisms may provide a unique integrative framework for the pathologic diversity and complexity of AD. PMID:21482442

a Standardized Approach to Topographic Data Processing and Workflow Management

NASA Astrophysics Data System (ADS)

Wheaton, J. M.; Bailey, P.; Glenn, N. F.; Hensleigh, J.; Hudak, A. T.; Shrestha, R.; Spaete, L.

2013-12-01

An ever-increasing list of options exist for collecting high resolution topographic data, including airborne LIDAR, terrestrial laser scanners, bathymetric SONAR and structure-from-motion. An equally rich, arguably overwhelming, variety of tools exists with which to organize, quality control, filter, analyze and summarize these data. However, scientists are often left to cobble together their analysis as a series of ad hoc steps, often using custom scripts and one-time processes that are poorly documented and rarely shared with the community. Even when literature-cited software tools are used, the input and output parameters differ from tool to tool. These parameters are rarely archived and the steps performed lost, making the analysis virtually impossible to replicate precisely. What is missing is a coherent, robust, framework for combining reliable, well-documented topographic data-processing steps into a workflow that can be repeated and even shared with others. We have taken several popular topographic data processing tools - including point cloud filtering and decimation as well as DEM differencing - and defined a common protocol for passing inputs and outputs between them. This presentation describes a free, public online portal that enables scientists to create custom workflows for processing topographic data using a number of popular topographic processing tools. Users provide the inputs required for each tool and in what sequence they want to combine them. This information is then stored for future reuse (and optionally sharing with others) before the user then downloads a single package that contains all the input and output specifications together with the software tools themselves. The user then launches the included batch file that executes the workflow on their local computer against their topographic data. This ZCloudTools architecture helps standardize, automate and archive topographic data processing. It also represents a forum for discovering and sharing effective topographic processing workflows.

Developing a Collection of Composable Data Translation Software Units to Improve Efficiency and Reproducibility in Ecohydrologic Modeling Workflows

NASA Astrophysics Data System (ADS)

Olschanowsky, C.; Flores, A. N.; FitzGerald, K.; Masarik, M. T.; Rudisill, W. J.; Aguayo, M.

2017-12-01

Dynamic models of the spatiotemporal evolution of water, energy, and nutrient cycling are important tools to assess impacts of climate and other environmental changes on ecohydrologic systems. These models require spatiotemporally varying environmental forcings like precipitation, temperature, humidity, windspeed, and solar radiation. These input data originate from a variety of sources, including global and regional weather and climate models, global and regional reanalysis products, and geostatistically interpolated surface observations. Data translation measures, often subsetting in space and/or time and transforming and converting variable units, represent a seemingly mundane, but critical step in the application workflows. Translation steps can introduce errors, misrepresentations of data, slow execution time, and interrupt data provenance. We leverage a workflow that subsets a large regional dataset derived from the Weather Research and Forecasting (WRF) model and prepares inputs to the Parflow integrated hydrologic model to demonstrate the impact translation tool software quality on scientific workflow results and performance. We propose that such workflows will benefit from a community approved collection of data transformation components. The components should be self-contained composable units of code. This design pattern enables automated parallelization and software verification, improving performance and reliability. Ensuring that individual translation components are self-contained and target minute tasks increases reliability. The small code size of each component enables effective unit and regression testing. The components can be automatically composed for efficient execution. An efficient data translation framework should be written to minimize data movement. Composing components within a single streaming process reduces data movement. Each component will typically have a low arithmetic intensity, meaning that it requires about the same number of bytes to be read as the number of computations it performs. When several components' executions are coordinated the overall arithmetic intensity increases, leading to increased efficiency.

The “Common Solutions” Strategy of the Experiment Support group at CERN for the LHC Experiments

NASA Astrophysics Data System (ADS)

Girone, M.; Andreeva, J.; Barreiro Megino, F. H.; Campana, S.; Cinquilli, M.; Di Girolamo, A.; Dimou, M.; Giordano, D.; Karavakis, E.; Kenyon, M. J.; Kokozkiewicz, L.; Lanciotti, E.; Litmaath, M.; Magini, N.; Negri, G.; Roiser, S.; Saiz, P.; Saiz Santos, M. D.; Schovancova, J.; Sciabà, A.; Spiga, D.; Trentadue, R.; Tuckett, D.; Valassi, A.; Van der Ster, D. C.; Shiers, J. D.

2012-12-01

After two years of LHC data taking, processing and analysis and with numerous changes in computing technology, a number of aspects of the experiments’ computing, as well as WLCG deployment and operations, need to evolve. As part of the activities of the Experiment Support group in CERN's IT department, and reinforced by effort from the EGI-InSPIRE project, we present work aimed at common solutions across all LHC experiments. Such solutions allow us not only to optimize development manpower but also offer lower long-term maintenance and support costs. The main areas cover Distributed Data Management, Data Analysis, Monitoring and the LCG Persistency Framework. Specific tools have been developed including the HammerCloud framework, automated services for data placement, data cleaning and data integrity (such as the data popularity service for CMS, the common Victor cleaning agent for ATLAS and CMS and tools for catalogue/storage consistency), the Dashboard Monitoring framework (job monitoring, data management monitoring, File Transfer monitoring) and the Site Status Board. This talk focuses primarily on the strategic aspects of providing such common solutions and how this relates to the overall goals of long-term sustainability and the relationship to the various WLCG Technical Evolution Groups. The success of the service components has given us confidence in the process, and has developed the trust of the stakeholders. We are now attempting to expand the development of common solutions into the more critical workflows. The first is a feasibility study of common analysis workflow execution elements between ATLAS and CMS. We look forward to additional common development in the future.

Interfaces and Integration of Medical Image Analysis Frameworks: Challenges and Opportunities.

PubMed

Covington, Kelsie; McCreedy, Evan S; Chen, Min; Carass, Aaron; Aucoin, Nicole; Landman, Bennett A

2010-05-25

Clinical research with medical imaging typically involves large-scale data analysis with interdependent software toolsets tied together in a processing workflow. Numerous, complementary platforms are available, but these are not readily compatible in terms of workflows or data formats. Both image scientists and clinical investigators could benefit from using the framework which is a most natural fit to the specific problem at hand, but pragmatic choices often dictate that a compromise platform is used for collaboration. Manual merging of platforms through carefully tuned scripts has been effective, but exceptionally time consuming and is not feasible for large-scale integration efforts. Hence, the benefits of innovation are constrained by platform dependence. Removing this constraint via integration of algorithms from one framework into another is the focus of this work. We propose and demonstrate a light-weight interface system to expose parameters across platforms and provide seamless integration. In this initial effort, we focus on four platforms Medical Image Analysis and Visualization (MIPAV), Java Image Science Toolkit (JIST), command line tools, and 3D Slicer. We explore three case studies: (1) providing a system for MIPAV to expose internal algorithms and utilize these algorithms within JIST, (2) exposing JIST modules through self-documenting command line interface for inclusion in scripting environments, and (3) detecting and using JIST modules in 3D Slicer. We review the challenges and opportunities for light-weight software integration both within development language (e.g., Java in MIPAV and JIST) and across languages (e.g., C/C++ in 3D Slicer and shell in command line tools).

Akuna: An Open Source User Environment for Managing Subsurface Simulation Workflows

NASA Astrophysics Data System (ADS)

Freedman, V. L.; Agarwal, D.; Bensema, K.; Finsterle, S.; Gable, C. W.; Keating, E. H.; Krishnan, H.; Lansing, C.; Moeglein, W.; Pau, G. S. H.; Porter, E.; Scheibe, T. D.

2014-12-01

The U.S. Department of Energy (DOE) is investing in development of a numerical modeling toolset called ASCEM (Advanced Simulation Capability for Environmental Management) to support modeling analyses at legacy waste sites. ASCEM is an open source and modular computing framework that incorporates new advances and tools for predicting contaminant fate and transport in natural and engineered systems. The ASCEM toolset includes both a Platform with Integrated Toolsets (called Akuna) and a High-Performance Computing multi-process simulator (called Amanzi). The focus of this presentation is on Akuna, an open-source user environment that manages subsurface simulation workflows and associated data and metadata. In this presentation, key elements of Akuna are demonstrated, which includes toolsets for model setup, database management, sensitivity analysis, parameter estimation, uncertainty quantification, and visualization of both model setup and simulation results. A key component of the workflow is in the automated job launching and monitoring capabilities, which allow a user to submit and monitor simulation runs on high-performance, parallel computers. Visualization of large outputs can also be performed without moving data back to local resources. These capabilities make high-performance computing accessible to the users who might not be familiar with batch queue systems and usage protocols on different supercomputers and clusters.

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines

PubMed Central

Kurç, Tahsin M.; Taveira, Luís F. R.; Melo, Alba C. M. A.; Gao, Yi; Kong, Jun; Saltz, Joel H.

2017-01-01

Abstract Motivation: Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. Results: The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Conclusions: Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Availability and Implementation: Source code: https://github.com/SBU-BMI/region-templates/. Contact: teodoro@unb.br Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28062445

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines.

PubMed

Teodoro, George; Kurç, Tahsin M; Taveira, Luís F R; Melo, Alba C M A; Gao, Yi; Kong, Jun; Saltz, Joel H

2017-04-01

Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Source code: https://github.com/SBU-BMI/region-templates/ . teodoro@unb.br. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Grid-based platform for training in Earth Observation

NASA Astrophysics Data System (ADS)

Petcu, Dana; Zaharie, Daniela; Panica, Silviu; Frincu, Marc; Neagul, Marian; Gorgan, Dorian; Stefanut, Teodor

2010-05-01

GiSHEO platform [1] providing on-demand services for training and high education in Earth Observation is developed, in the frame of an ESA funded project through its PECS programme, to respond to the needs of powerful education resources in remote sensing field. It intends to be a Grid-based platform of which potential for experimentation and extensibility are the key benefits compared with a desktop software solution. Near-real time applications requiring simultaneous multiple short-time-response data-intensive tasks, as in the case of a short time training event, are the ones that are proved to be ideal for this platform. The platform is based on Globus Toolkit 4 facilities for security and process management, and on the clusters of four academic institutions involved in the project. The authorization uses a VOMS service. The main public services are the followings: the EO processing services (represented through special WSRF-type services); the workflow service exposing a particular workflow engine; the data indexing and discovery service for accessing the data management mechanisms; the processing services, a collection allowing easy access to the processing platform. The WSRF-type services for basic satellite image processing are reusing free image processing tools, OpenCV and GDAL. New algorithms and workflows were develop to tackle with challenging problems like detecting the underground remains of old fortifications, walls or houses. More details can be found in [2]. Composed services can be specified through workflows and are easy to be deployed. The workflow engine, OSyRIS (Orchestration System using a Rule based Inference Solution), is based on DROOLS, and a new rule-based workflow language, SILK (SImple Language for worKflow), has been built. Workflow creation in SILK can be done with or without a visual designing tools. The basics of SILK are the tasks and relations (rules) between them. It is similar with the SCUFL language, but not relying on XML in order to allow the introduction of more workflow specific issues. Moreover, an event-condition-action (ECA) approach allows a greater flexibility when expressing data and task dependencies, as well as the creation of adaptive workflows which can react to changes in the configuration of the Grid or in the workflow itself. Changes inside the grid are handled by creating specific rules which allow resource selection based on various task scheduling criteria. Modifications of the workflow are usually accomplished either by inserting or retracting at runtime rules belonging to it or by modifying the executor of the task in case a better one is found. The former implies changes in its structure while the latter does not necessarily mean changes of the resource but more precisely changes of the algorithm used for solving the task. More details can be found in [3]. Another important platform component is the data indexing and storage service, GDIS, providing features for data storage, indexing data using a specialized RDBMS, finding data by various conditions, querying external services and keeping track of temporary data generated by other components. The data storage component part of GDIS is responsible for storing the data by using available storage backends such as local disk file systems (ext3), local cluster storage (GFS) or distributed file systems (HDFS). A front-end GridFTP service is capable of interacting with the storage domains on behalf of the clients and in a uniform way and also enforces the security restrictions provided by other specialized services and related with data access. The data indexing is performed by PostGIS. An advanced and flexible interface for searching the project's geographical repository is built around a custom query language (LLQL - Lisp Like Query Language) designed to provide fine grained access to the data in the repository and to query external services (e.g. for exploiting the connection with GENESI-DR catalog). More details can be found in [4]. The Workload Management System (WMS) provides two types of resource managers. The first one will be based on Condor HTC and use Condor as a job manager for task dispatching and working nodes (for development purposes) while the second one will use GT4 GRAM (for production purposes). The WMS main component, the Grid Task Dispatcher (GTD), is responsible for the interaction with other internal services as the composition engine in order to facilitate access to the processing platform. Its main responsibilities are to receive tasks from the workflow engine or directly from user interface, to use a task description language (the ClassAd meta language in case of Condor HTC) for job units, to submit and check the status of jobs inside the workload management system and to retrieve job logs for debugging purposes. More details can be found in [4]. A particular component of the platform is eGLE, the eLearning environment. It provides the functionalities necessary to create the visual appearance of the lessons through the usage of visual containers like tools, patterns and templates. The teacher uses the platform for testing the already created lessons, as well as for developing new lesson resources, such as new images and workflows describing graph-based processing. The students execute the lessons or describe and experiment with new workflows or different data. The eGLE database includes several workflow-based lesson descriptions, teaching materials and lesson resources, selected satellite and spatial data. More details can be found in [5]. A first training event of using the platform was organized in September 2009 during 11th SYNASC symposium (links to the demos, testing interface, and exercises are available on project site [1]). The eGLE component was presented at 4th GPC conference in May 2009. Moreover, the functionality of the platform will be presented as demo in April 2010 at 5th EGEE User forum. References: [1] GiSHEO consortium, Project site, http://gisheo.info.uvt.ro [2] D. Petcu, D. Zaharie, M. Neagul, S. Panica, M. Frincu, D. Gorgan, T. Stefanut, V. Bacu, Remote Sensed Image Processing on Grids for Training in Earth Observation. In Image Processing, V. Kordic (ed.), In-Tech, January 2010. [3] M. Neagul, S. Panica, D. Petcu, D. Zaharie, D. Gorgan, Web and Grid Services for Training in Earth Observation, IDAACS 2009, IEEE Computer Press, 241-246 [4] M. Frincu, S. Panica, M. Neagul, D. Petcu, Gisheo: On Demand Grid Service Based Platform for EO Data Processing. HiperGrid 2009, Politehnica Press, 415-422. [5] D. Gorgan, T. Stefanut, V. Bacu, Grid Based Training Environment for Earth Observation, GPC 2009, LNCS 5529, 98-109

SHIWA Services for Workflow Creation and Sharing in Hydrometeorolog

NASA Astrophysics Data System (ADS)

Terstyanszky, Gabor; Kiss, Tamas; Kacsuk, Peter; Sipos, Gergely

2014-05-01

Researchers want to run scientific experiments on Distributed Computing Infrastructures (DCI) to access large pools of resources and services. To run these experiments requires specific expertise that they may not have. Workflows can hide resources and services as a virtualisation layer providing a user interface that researchers can use. There are many scientific workflow systems but they are not interoperable. To learn a workflow system and create workflows may require significant efforts. Considering these efforts it is not reasonable to expect that researchers will learn new workflow systems if they want to run workflows developed in other workflow systems. To overcome it requires creating workflow interoperability solutions to allow workflow sharing. The FP7 'Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs' (SHIWA) project developed the Coarse-Grained Interoperability concept (CGI). It enables recycling and sharing workflows of different workflow systems and executing them on different DCIs. SHIWA developed the SHIWA Simulation Platform (SSP) to implement the CGI concept integrating three major components: the SHIWA Science Gateway, the workflow engines supported by the CGI concept and DCI resources where workflows are executed. The science gateway contains a portal, a submission service, a workflow repository and a proxy server to support the whole workflow life-cycle. The SHIWA Portal allows workflow creation, configuration, execution and monitoring through a Graphical User Interface using the WS-PGRADE workflow system as the host workflow system. The SHIWA Repository stores the formal description of workflows and workflow engines plus executables and data needed to execute them. It offers a wide-range of browse and search operations. To support non-native workflow execution the SHIWA Submission Service imports the workflow and workflow engine from the SHIWA Repository. This service either invokes locally or remotely pre-deployed workflow engines or submits workflow engines with the workflow to local or remote resources to execute workflows. The SHIWA Proxy Server manages certificates needed to execute the workflows on different DCIs. Currently SSP supports sharing of ASKALON, Galaxy, GWES, Kepler, LONI Pipeline, MOTEUR, Pegasus, P-GRADE, ProActive, Triana, Taverna and WS-PGRADE workflows. Further workflow systems can be added to the simulation platform as required by research communities. The FP7 'Building a European Research Community through Interoperable Workflows and Data' (ER-flow) project disseminates the achievements of the SHIWA project to build workflow user communities across Europe. ER-flow provides application supports to research communities within (Astrophysics, Computational Chemistry, Heliophysics and Life Sciences) and beyond (Hydrometeorology and Seismology) to develop, share and run workflows through the simulation platform. The simulation platform supports four usage scenarios: creating and publishing workflows in the repository, searching and selecting workflows in the repository, executing non-native workflows and creating and running meta-workflows. The presentation will outline the CGI concept, the SHIWA Simulation Platform, the ER-flow usage scenarios and how the Hydrometeorology research community runs simulations on SSP.

The orchestration of occupation: the dance of mothers.

PubMed

Larson, E A

2000-01-01

This article describes the relationship of mothers' orchestration of daily occupations, the specialized maternal work of parenting a child with a disability, and the mother's subjective well-being. Mothers' daily occupations and subjective well-being were studied using multiple in-depth interviews, participant observation of a day's round of occupations, and scales of well-being. Data were treated to a recursive analysis, which included theoretical notes generated during transcriptions that identified important themes and additional points of inquiry, line-by-line coding of transcripts, and theoretical sorting of codes and regrouping, recoding. To account for patterns in the data, a relational analysis was conducted that included the generation of metaphors. Emergent findings of this analysis identified the mothers' guiding occupational motif and eight processes of orchestration in their daily routines. The occupational motif, the embrace of paradox, directed the mother's orchestration of daily occupations. The orchestration processes included planning, organizing, balancing, anticipating, interpreting, forecasting, perspective shifting, and meaning making. Examples illustrate the maternally driven and child-sensitive nature of these processes. In their daily rounds, the mothers studied were attentive to the manner and method with which they interacted with their children to produce child-contingent occupations commensurate with their values of being a good mother. Using these orchestration processes, mothers made sense of their past, designed their present, and planned for their future within their daily occupational rounds for themselves and family members.

iTOUGH2: A multiphysics simulation-optimization framework for analyzing subsurface systems

NASA Astrophysics Data System (ADS)

Finsterle, S.; Commer, M.; Edmiston, J. K.; Jung, Y.; Kowalsky, M. B.; Pau, G. S. H.; Wainwright, H. M.; Zhang, Y.

2017-11-01

iTOUGH2 is a simulation-optimization framework for the TOUGH suite of nonisothermal multiphase flow models and related simulators of geophysical, geochemical, and geomechanical processes. After appropriate parameterization of subsurface structures and their properties, iTOUGH2 runs simulations for multiple parameter sets and analyzes the resulting output for parameter estimation through automatic model calibration, local and global sensitivity analyses, data-worth analyses, and uncertainty propagation analyses. Development of iTOUGH2 is driven by scientific challenges and user needs, with new capabilities continually added to both the forward simulator and the optimization framework. This review article provides a summary description of methods and features implemented in iTOUGH2, and discusses the usefulness and limitations of an integrated simulation-optimization workflow in support of the characterization and analysis of complex multiphysics subsurface systems.

Large-scale, high-performance and cloud-enabled multi-model analytics experiments in the context of the Earth System Grid Federation

NASA Astrophysics Data System (ADS)

Fiore, S.; Płóciennik, M.; Doutriaux, C.; Blanquer, I.; Barbera, R.; Williams, D. N.; Anantharaj, V. G.; Evans, B. J. K.; Salomoni, D.; Aloisio, G.

2017-12-01

The increased models resolution in the development of comprehensive Earth System Models is rapidly leading to very large climate simulations output that pose significant scientific data management challenges in terms of data sharing, processing, analysis, visualization, preservation, curation, and archiving.Large scale global experiments for Climate Model Intercomparison Projects (CMIP) have led to the development of the Earth System Grid Federation (ESGF), a federated data infrastructure which has been serving the CMIP5 experiment, providing access to 2PB of data for the IPCC Assessment Reports. In such a context, running a multi-model data analysis experiment is very challenging, as it requires the availability of a large amount of data related to multiple climate models simulations and scientific data management tools for large-scale data analytics. To address these challenges, a case study on climate models intercomparison data analysis has been defined and implemented in the context of the EU H2020 INDIGO-DataCloud project. The case study has been tested and validated on CMIP5 datasets, in the context of a large scale, international testbed involving several ESGF sites (LLNL, ORNL and CMCC), one orchestrator site (PSNC) and one more hosting INDIGO PaaS services (UPV). Additional ESGF sites, such as NCI (Australia) and a couple more in Europe, are also joining the testbed. The added value of the proposed solution is summarized in the following: it implements a server-side paradigm which limits data movement; it relies on a High-Performance Data Analytics (HPDA) stack to address performance; it exploits the INDIGO PaaS layer to support flexible, dynamic and automated deployment of software components; it provides user-friendly web access based on the INDIGO Future Gateway; and finally it integrates, complements and extends the support currently available through ESGF. Overall it provides a new "tool" for climate scientists to run multi-model experiments. At the time this contribution is being written, the proposed testbed represents the first implementation of a distributed large-scale, multi-model experiment in the ESGF/CMIP context, joining together server-side approaches for scientific data analysis, HPDA frameworks, end-to-end workflow management, and cloud computing.

A web service for service composition to aid geospatial modelers

NASA Astrophysics Data System (ADS)

Bigagli, L.; Santoro, M.; Roncella, R.; Mazzetti, P.

2012-04-01

The identification of appropriate mechanisms for process reuse, chaining and composition is considered a key enabler for the effective uptake of a global Earth Observation infrastructure, currently pursued by the international geospatial research community. In the Earth and Space Sciences, such a facility could primarily enable integrated and interoperable modeling, for what several approaches have been proposed and developed, over the last years. In fact, GEOSS is specifically tasked with the development of the so-called "Model Web". At increasing levels of abstraction and generalization, the initial stove-pipe software tools have evolved to community-wide modeling frameworks, to Component-Based Architecture solution, and, more recently, started to embrace Service-Oriented Architectures technologies, such as the OGC WPS specification and the WS-* stack of W3C standards for service composition. However, so far, the level of abstraction seems too low for implementing the Model Web vision, and far too complex technological aspects must still be addressed by both providers and users, resulting in limited usability and, eventually, difficult uptake. As by the recent ICT trend of resource virtualization, it has been suggested that users in need of a particular processing capability, required by a given modeling workflow, may benefit from outsourcing the composition activities into an external first-class service, according to the Composition as a Service (CaaS) approach. A CaaS system provides the necessary interoperability service framework for adaptation, reuse and complementation of existing processing resources (including models and geospatial services in general) in the form of executable workflows. This work introduces the architecture of a CaaS system, as a distributed information system for creating, validating, editing, storing, publishing, and executing geospatial workflows. This way, the users can be freed from the need of a composition infrastructure and alleviated from the technicalities of workflow definitions (type matching, identification of external services endpoints, binding issues, etc.) and focus on their intended application. Moreover, the user may submit an incomplete workflow definition, and leverage CaaS recommendations (that may derive from an aggregated knowledge base of user feedback, underpinned by Web 2.0 technologies) to execute it. This is of particular interest for multidisciplinary scientific contexts, where different communities may benefit of each other knowledge through model chaining. Indeed, the CaaS approach is presented as an attempt to combine the recent advances in service-oriented computing with collaborative research principles, and social network information in general. Arguably, it may be considered a fundamental capability of the Model Web. The CaaS concept is being investigated in several application scenarios identified in the FP7 UncertWeb and EuroGEOSS projects. Key aspects of the described CaaS solution are: it provides a standard WPS interface for invoking Business Processes and allows on the fly recursive compositions of Business Processes into other Composite Processes; it is designed according to the extended SOA (broker-based) and the System-of-Systems approach, to support the reuse and integration of existing resources, in compliance with the GEOSS Model Web architecture. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement n° 248488.

Organizational Implications of the U.S. Army’s Increasing Demand for Explosive Ordnance Disposal Capabilities

DTIC Science & Technology

2008-05-22

Washington D.C: Government Printing Office, 1976), 1-1 to 1-5. 43 Ibid, 2-1 to 2-32. 16 “orchestrated ballet of farm implements.”44 The Army’s...Orchestrated Ballet of Farm Implements”, Engineer Bulletin, August 1996, http://fas.org/man/dod 101/sys/land/docs /960800-greene2.htm (accessed 5 April...An Alternative to the Orchestrated Ballet of Farm Implements” Engineer Bulletin (August 1996), http://fas.org/man/dod_101/sys/land/docs/960800

Enabling a systems biology knowledgebase with gaggle and firegoose

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

Baliga, Nitin S.

The overall goal of this project was to extend the existing Gaggle and Firegoose systems to develop an open-source technology that runs over the web and links desktop applications with many databases and software applications. This technology would enable researchers to incorporate workflows for data analysis that can be executed from this interface to other online applications. The four specific aims were to (1) provide one-click mapping of genes, proteins, and complexes across databases and species; (2) enable multiple simultaneous workflows; (3) expand sophisticated data analysis for online resources; and enhance open-source development of the Gaggle-Firegoose infrastructure. Gaggle is anmore » open-source Java software system that integrates existing bioinformatics programs and data sources into a user-friendly, extensible environment to allow interactive exploration, visualization, and analysis of systems biology data. Firegoose is an extension to the Mozilla Firefox web browser that enables data transfer between websites and desktop tools including Gaggle. In the last phase of this funding period, we have made substantial progress on development and application of the Gaggle integration framework. We implemented the workspace to the Network Portal. Users can capture data from Firegoose and save them to the workspace. Users can create workflows to start multiple software components programmatically and pass data between them. Results of analysis can be saved to the cloud so that they can be easily restored on any machine. We also developed the Gaggle Chrome Goose, a plugin for the Google Chrome browser in tandem with an opencpu server in the Amazon EC2 cloud. This allows users to interactively perform data analysis on a single web page using the R packages deployed on the opencpu server. The cloud-based framework facilitates collaboration between researchers from multiple organizations. We have made a number of enhancements to the cmonkey2 application to enable and improve the integration within different environments, and we have created a new tools pipeline for generating EGRIN2 models in a largely automated way.« less

Designing Collaborative Developmental Standards by Refactoring of the Earth Science Models, Libraries, Workflows and Frameworks.

NASA Astrophysics Data System (ADS)

Mirvis, E.; Iredell, M.

2015-12-01

The operational (OPS) NOAA National Centers for Environmental Prediction (NCEP) suite, traditionally, consist of a large set of multi- scale HPC models, workflows, scripts, tools and utilities, which are very much depending on the variety of the additional components. Namely, this suite utilizes a unique collection of the in-house developed 20+ shared libraries (NCEPLIBS), certain versions of the 3-rd party libraries (like netcdf, HDF, ESMF, jasper, xml etc.), HPC workflow tool within dedicated (sometimes even vendors' customized) HPC system homogeneous environment. This domain and site specific, accompanied with NCEP's product- driven large scale real-time data operations complicates NCEP collaborative development tremendously by reducing chances to replicate this OPS environment anywhere else. The NOAA/NCEP's Environmental Modeling Center (EMC) missions to develop and improve numerical weather, climate, hydrological and ocean prediction through the partnership with the research community. Realizing said difficulties, lately, EMC has been taken an innovative approach to improve flexibility of the HPC environment by building the elements and a foundation for NCEP OPS functionally equivalent environment (FEE), which can be used to ease the external interface constructs as well. Aiming to reduce turnaround time of the community code enhancements via Research-to-Operations (R2O) cycle, EMC developed and deployed several project sub-set standards that already paved the road to NCEP OPS implementation standards. In this topic we will discuss the EMC FEE for O2R requirements and approaches in collaborative standardization, including NCEPLIBS FEE and models code version control paired with the models' derived customized HPC modules and FEE footprints. We will share NCEP/EMC experience and potential in the refactoring of EMC development processes, legacy codes and in securing model source code quality standards by using combination of the Eclipse IDE, integrated with the reverse engineering tools/APIs. We will also inform on collaborative efforts in the restructuring of the NOAA Environmental Modeling System (NEMS) - the multi- model and coupling framework, and transitioning FEE verification methodology.

An Integrated Cyberenvironment for Event-Driven Environmental Observatory Research and Education

NASA Astrophysics Data System (ADS)

Myers, J.; Minsker, B.; Butler, R.

2006-12-01

National environmental observatories will soon provide large-scale data from diverse sensor networks and community models. While much attention is focused on piping data from sensors to archives and users, truly integrating these resources into the everyday research activities of scientists and engineers across the community, and enabling their results and innovations to be brought back into the observatory, also critical to long-term success of the observatories, is often neglected. This talk will give an overview of the Environmental Cyberinfrastructure Demonstrator (ECID) Cyberenvironment for observatory-centric environmental research and education, under development at the National Center for Supercomputing Applications (NCSA), which is designed to address these issues. Cyberenvironments incorporate collaboratory and grid technologies, web services, and other cyberinfrastructure into an overall framework that balances needs for efficient coordination and the ability to innovate. They are designed to support the full scientific lifecycle both in terms of individual experiments moving from data to workflows to publication and at the macro level where new discoveries lead to additional data, models, tools, and conceptual frameworks that augment and evolve community-scale systems such as observatories. The ECID cyberenvironment currently integrates five major components a collaborative portal, workflow engine, event manager, metadata repository, and social network personalization capabilities - that have novel features inspired by the Cyberenvironment concept and enabling powerful environmental research scenarios. A summary of these components and the overall cyberenvironment will be given in this talk, while other posters will give details on several of the components. The summary will be presented within the context of environmental use case scenarios created in collaboration with researchers from the WATERS (WATer and Environmental Research Systems) Network, a joint National Science Foundation-funded initiative of the hydrology and environmental engineering communities. The use case scenarios include identifying sensor anomalies in point- and streaming sensor data and notifying data managers in near-real time; and referring users of data or data products (e.g., workflows, publications) to related data or data products.

An Implementation-Focused Bio/Algorithmic Workflow for Synthetic Biology.

PubMed

Goñi-Moreno, Angel; Carcajona, Marta; Kim, Juhyun; Martínez-García, Esteban; Amos, Martyn; de Lorenzo, Víctor

2016-10-21

As synthetic biology moves away from trial and error and embraces more formal processes, workflows have emerged that cover the roadmap from conceptualization of a genetic device to its construction and measurement. This latter aspect (i.e., characterization and measurement of synthetic genetic constructs) has received relatively little attention to date, but it is crucial for their outcome. An end-to-end use case for engineering a simple synthetic device is presented, which is supported by information standards and computational methods and focuses on such characterization/measurement. This workflow captures the main stages of genetic device design and description and offers standardized tools for both population-based measurement and single-cell analysis. To this end, three separate aspects are addressed. First, the specific vector features are discussed. Although device/circuit design has been successfully automated, important structural information is usually overlooked, as in the case of plasmid vectors. The use of the Standard European Vector Architecture (SEVA) is advocated for selecting the optimal carrier of a design and its thorough description in order to unequivocally correlate digital definitions and molecular devices. A digital version of this plasmid format was developed with the Synthetic Biology Open Language (SBOL) along with a software tool that allows users to embed genetic parts in vector cargoes. This enables annotation of a mathematical model of the device's kinetic reactions formatted with the Systems Biology Markup Language (SBML). From that point onward, the experimental results and their in silico counterparts proceed alongside, with constant feedback to preserve consistency between them. A second aspect involves a framework for the calibration of fluorescence-based measurements. One of the most challenging endeavors in standardization, metrology, is tackled by reinterpreting the experimental output in light of simulation results, allowing us to turn arbitrary fluorescence units into relative measurements. Finally, integration of single-cell methods into a framework for multicellular simulation and measurement is addressed, allowing standardized inspection of the interplay between the carrier chassis and the culture conditions.

Dispel4py: An Open-Source Python library for Data-Intensive Seismology

NASA Astrophysics Data System (ADS)

Filgueira, Rosa; Krause, Amrey; Spinuso, Alessandro; Klampanos, Iraklis; Danecek, Peter; Atkinson, Malcolm

2015-04-01

Scientific workflows are a necessary tool for many scientific communities as they enable easy composition and execution of applications on computing resources while scientists can focus on their research without being distracted by the computation management. Nowadays, scientific communities (e.g. Seismology) have access to a large variety of computing resources and their computational problems are best addressed using parallel computing technology. However, successful use of these technologies requires a lot of additional machinery whose use is not straightforward for non-experts: different parallel frameworks (MPI, Storm, multiprocessing, etc.) must be used depending on the computing resources (local machines, grids, clouds, clusters) where applications are run. This implies that for achieving the best applications' performance, users usually have to change their codes depending on the features of the platform selected for running them. This work presents dispel4py, a new open-source Python library for describing abstract stream-based workflows for distributed data-intensive applications. Special care has been taken to provide dispel4py with the ability to map abstract workflows to different platforms dynamically at run-time. Currently dispel4py has four mappings: Apache Storm, MPI, multi-threading and sequential. The main goal of dispel4py is to provide an easy-to-use tool to develop and test workflows in local resources by using the sequential mode with a small dataset. Later, once a workflow is ready for long runs, it can be automatically executed on different parallel resources. dispel4py takes care of the underlying mappings by performing an efficient parallelisation. Processing Elements (PE) represent the basic computational activities of any dispel4Py workflow, which can be a seismologic algorithm, or a data transformation process. For creating a dispel4py workflow, users only have to write very few lines of code to describe their PEs and how they are connected by using Python, which is widely supported on many platforms and is popular in many scientific domains, such as in geosciences. Once, a dispel4py workflow is written, a user only has to select which mapping they would like to use, and everything else (parallelisation, distribution of data) is carried on by dispel4py without any cost to the user. Among all dispel4py features we would like to highlight the following: * The PEs are connected by streams and not by writing to and reading from intermediate files, avoiding many IO operations. * The PEs can be stored into a registry. Therefore, different users can recombine PEs in many different workflows. * dispel4py has been enriched with a provenance mechanism to support runtime provenance analysis. We have adopted the W3C-PROV data model, which is accessible via a prototypal browser-based user interface and a web API. It supports the users with the visualisation of graphical products and offers combined operations to access and download the data, which may be selectively stored at runtime, into dedicated data archives. dispel4py has been already used by seismologists in the VERCE project to develop different seismic workflows. One of them is the Seismic Ambient Noise Cross-Correlation workflow, which preprocesses and cross-correlates traces from several stations. First, this workflow was tested on a local machine by using a small number of stations as input data. Later, it was executed on different parallel platforms (SuperMUC cluster, and Terracorrelator machine), automatically scaling up by using MPI and multiprocessing mappings and up to 1000 stations as input data. The results show that the dispel4py achieves scalable performance in both mappings tested on different parallel platforms.

Agile parallel bioinformatics workflow management using Pwrake.

PubMed

Mishima, Hiroyuki; Sasaki, Kensaku; Tanaka, Masahiro; Tatebe, Osamu; Yoshiura, Koh-Ichiro

2011-09-08

In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error.Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability and maintainability of rakefiles may facilitate sharing workflows among the scientific community. Workflows for GATK and Dindel are available at http://github.com/misshie/Workflows.

Agile parallel bioinformatics workflow management using Pwrake

PubMed Central

2011-01-01

Background In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error. Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. Findings We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Conclusions Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability and maintainability of rakefiles may facilitate sharing workflows among the scientific community. Workflows for GATK and Dindel are available at http://github.com/misshie/Workflows. PMID:21899774

Using telephony data to facilitate discovery of clinical workflows.

PubMed

Rucker, Donald W

2017-04-19

Discovery of clinical workflows to target for redesign using methods such as Lean and Six Sigma is difficult. VoIP telephone call pattern analysis may complement direct observation and EMR-based tools in understanding clinical workflows at the enterprise level by allowing visualization of institutional telecommunications activity. To build an analytic framework mapping repetitive and high-volume telephone call patterns in a large medical center to their associated clinical units using an enterprise unified communications server log file and to support visualization of specific call patterns using graphical networks. Consecutive call detail records from the medical center's unified communications server were parsed to cross-correlate telephone call patterns and map associated phone numbers to a cost center dictionary. Hashed data structures were built to allow construction of edge and node files representing high volume call patterns for display with an open source graph network tool. Summary statistics for an analysis of exactly one week's call detail records at a large academic medical center showed that 912,386 calls were placed with a total duration of 23,186 hours. Approximately half of all calling called number pairs had an average call duration under 60 seconds and of these the average call duration was 27 seconds. Cross-correlation of phone calls identified by clinical cost center can be used to generate graphical displays of clinical enterprise communications. Many calls are short. The compact data transfers within short calls may serve as automation or re-design targets. The large absolute amount of time medical center employees were engaged in VoIP telecommunications suggests that analysis of telephone call patterns may offer additional insights into core clinical workflows.

Multi-core processing and scheduling performance in CMS

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

Hernandez, J. M.; Evans, D.; Foulkes, S.

2012-01-01

Commodity hardware is going many-core. We might soon not be able to satisfy the job memory needs per core in the current single-core processing model in High Energy Physics. In addition, an ever increasing number of independent and incoherent jobs running on the same physical hardware not sharing resources might significantly affect processing performance. It will be essential to effectively utilize the multi-core architecture. CMS has incorporated support for multi-core processing in the event processing framework and the workload management system. Multi-core processing jobs share common data in memory, such us the code libraries, detector geometry and conditions data, resultingmore » in a much lower memory usage than standard single-core independent jobs. Exploiting this new processing model requires a new model in computing resource allocation, departing from the standard single-core allocation for a job. The experiment job management system needs to have control over a larger quantum of resource since multi-core aware jobs require the scheduling of multiples cores simultaneously. CMS is exploring the approach of using whole nodes as unit in the workload management system where all cores of a node are allocated to a multi-core job. Whole-node scheduling allows for optimization of the data/workflow management (e.g. I/O caching, local merging) but efficient utilization of all scheduled cores is challenging. Dedicated whole-node queues have been setup at all Tier-1 centers for exploring multi-core processing workflows in CMS. We present the evaluation of the performance scheduling and executing multi-core workflows in whole-node queues compared to the standard single-core processing workflows.« less

An Efficient Workflow Environment to Support the Collaborative Development of Actionable Climate Information Using the NCAR Climate Risk Management Engine (CRMe)

NASA Astrophysics Data System (ADS)

Ammann, C. M.; Vigh, J. L.; Lee, J. A.

2016-12-01

Society's growing needs for robust and relevant climate information have fostered an explosion in tools and frameworks for processing climate projections. Many top-down workflows might be employed to generate sets of pre-computed data and plots, frequently served in a "loading-dock style" through a metadata-enabled search and discovery engine. Despite these increasing resources, the diverse needs of applications-driven projects often result in data processing workflow requirements that cannot be fully satisfied using past approaches. In parallel to the data processing challenges, the provision of climate information to users in a form that is also usable represents a formidable challenge of its own. Finally, many users do not have the time nor the desire to synthesize and distill massive volumes of climate information to find the relevant information for their particular application. All of these considerations call for new approaches to developing actionable climate information. CRMe seeks to bridge the gap between the diversity and richness of bottom-up needs of practitioners, with discrete, structured top-down workflows typically implemented for rapid delivery. Additionally, CRMe has implemented web-based data services capable of providing focused climate information in usable form for a given location, or as spatially aggregated information for entire regions or countries following the needs of users and sectors. Making climate data actionable also involves summarizing and presenting it in concise and approachable ways. CRMe is developing the concept of dashboards, co-developed with the users, to condense the key information into a quick summary of the most relevant, curated climate data for a given discipline, application, or location, while still enabling users to efficiently conduct deeper discovery into rich datasets on an as-needed basis.

Frameworks for change in healthcare organisations: a formative evaluation of the NHS Change Model.

PubMed

Martin, Graham P; Sutton, Elizabeth; Willars, Janet; Dixon-Woods, Mary

2013-08-01

Organisational change in complex healthcare systems is a multifaceted process. The English National Health Service recently introduced a 'Change Model' that seeks to offer an evidence-based framework for guiding change. We report findings from a formative evaluation of the NHS Change Model and make recommendations for those developing the Model and its users. The evaluation involved 28 interviews with managers and clinicians making use of the Change Model in relation to a variety of projects. Interviews were fully transcribed and were analysed using an approach based on the Framework method. Participants saw the Change Model as valuable and practically useful. Fidelity to core principles of the Model was variable: participants often altered the Model, especially when using it to orchestrate the work of others. In challenging organisational contexts, the Change Model was sometimes used to delegitimise opposition rather than identify shared purpose among different interest groups. Those guiding change may benefit from frameworks, guidance and toolkits to structure and inform their planning and activities. Participants' experiences suggested the Change Model has much potential. Further work on its design and on supporting materials may optimise the approach, but its utility rests in particular on organisational cultures that support faithful application. © The Author(s) 2013 Reprints and permissions:]br]sagepub.co.uk/journalsPermissions.nav.

Glocal Clinical Registries: Pacemaker Registry Design and Implementation for Global and Local Integration – Methodology and Case Study

PubMed Central

da Silva, Kátia Regina; Costa, Roberto; Crevelari, Elizabeth Sartori; Lacerda, Marianna Sobral; de Moraes Albertini, Caio Marcos; Filho, Martino Martinelli; Santana, José Eduardo; Vissoci, João Ricardo Nickenig; Pietrobon, Ricardo; Barros, Jacson V.

2013-01-01

Background The ability to apply standard and interoperable solutions for implementing and managing medical registries as well as aggregate, reproduce, and access data sets from legacy formats and platforms to advanced standard formats and operating systems are crucial for both clinical healthcare and biomedical research settings. Purpose Our study describes a reproducible, highly scalable, standard framework for a device registry implementation addressing both local data quality components and global linking problems. Methods and Results We developed a device registry framework involving the following steps: (1) Data standards definition and representation of the research workflow, (2) Development of electronic case report forms using REDCap (Research Electronic Data Capture), (3) Data collection according to the clinical research workflow and, (4) Data augmentation by enriching the registry database with local electronic health records, governmental database and linked open data collections, (5) Data quality control and (6) Data dissemination through the registry Web site. Our registry adopted all applicable standardized data elements proposed by American College Cardiology / American Heart Association Clinical Data Standards, as well as variables derived from cardiac devices randomized trials and Clinical Data Interchange Standards Consortium. Local interoperability was performed between REDCap and data derived from Electronic Health Record system. The original data set was also augmented by incorporating the reimbursed values paid by the Brazilian government during a hospitalization for pacemaker implantation. By linking our registry to the open data collection repository Linked Clinical Trials (LinkedCT) we found 130 clinical trials which are potentially correlated with our pacemaker registry. Conclusion This study demonstrates how standard and reproducible solutions can be applied in the implementation of medical registries to constitute a re-usable framework. Such approach has the potential to facilitate data integration between healthcare and research settings, also being a useful framework to be used in other biomedical registries. PMID:23936257

A standardised graphic method for describing data privacy frameworks in primary care research using a flexible zone model.

PubMed

Kuchinke, Wolfgang; Ohmann, Christian; Verheij, Robert A; van Veen, Evert-Ben; Arvanitis, Theodoros N; Taweel, Adel; Delaney, Brendan C

2014-12-01

To develop a model describing core concepts and principles of data flow, data privacy and confidentiality, in a simple and flexible way, using concise process descriptions and a diagrammatic notation applied to research workflow processes. The model should help to generate robust data privacy frameworks for research done with patient data. Based on an exploration of EU legal requirements for data protection and privacy, data access policies, and existing privacy frameworks of research projects, basic concepts and common processes were extracted, described and incorporated into a model with a formal graphical representation and a standardised notation. The Unified Modelling Language (UML) notation was enriched by workflow and own symbols to enable the representation of extended data flow requirements, data privacy and data security requirements, privacy enhancing techniques (PET) and to allow privacy threat analysis for research scenarios. Our model is built upon the concept of three privacy zones (Care Zone, Non-care Zone and Research Zone) containing databases, data transformation operators, such as data linkers and privacy filters. Using these model components, a risk gradient for moving data from a zone of high risk for patient identification to a zone of low risk can be described. The model was applied to the analysis of data flows in several general clinical research use cases and two research scenarios from the TRANSFoRm project (e.g., finding patients for clinical research and linkage of databases). The model was validated by representing research done with the NIVEL Primary Care Database in the Netherlands. The model allows analysis of data privacy and confidentiality issues for research with patient data in a structured way and provides a framework to specify a privacy compliant data flow, to communicate privacy requirements and to identify weak points for an adequate implementation of data privacy. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Interprofessional Health Team Communication About Hospital Discharge: An Implementation Science Evaluation Study.

PubMed

Bahr, Sarah J; Siclovan, Danielle M; Opper, Kristi; Beiler, Joseph; Bobay, Kathleen L; Weiss, Marianne E

The Consolidated Framework for Implementation Research guided formative evaluation of the implementation of a redesigned interprofessional team rounding process. The purpose of the redesigned process was to improve health team communication about hospital discharge. Themes emerging from interviews of patients, nurses, and providers revealed the inherent value and positive characteristics of the new process, but also workflow, team hierarchy, and process challenges to successful implementation. The evaluation identified actionable recommendations for modifying the implementation process.

GoFFish: Graph-Oriented Framework for Foresight and Insight Using Scalable Heuristics

DTIC Science & Technology

2015-09-01

series of research challenges that arise from the above and related to: scalability, data partitioning, memory representation and storage, exe - cution...job with varied deadlines in Jan, 2013. Further, we also build an SPSP model using Jan, 2013 data post facto as an ideal case. Fig. 7 reports the...Advanced Studies on Collaborative Research . Riverton, NJ, USA: IBM Corp., 2009, pp. 101–111. [42] G. J. Nutt, “The evolution towards flexible workflow

MRI-guided stereotactic neurosurgical procedures in a diagnostic MRI suite: Background and safe practice recommendations.

PubMed

Larson, Paul S; Willie, Jon T; Vadivelu, Sudhakar; Azmi-Ghadimi, Hooman; Nichols, Amy; Fauerbach, Loretta Litz; Johnson, Helen Boehm; Graham, Denise

2017-07-01

The development of navigation technology facilitating MRI-guided stereotactic neurosurgery has enabled neurosurgeons to perform a variety of procedures ranging from deep brain stimulation to laser ablation entirely within an intraoperative or diagnostic MRI suite while having real-time visualization of brain anatomy. Prior to this technology, some of these procedures required multisite workflow patterns that presented significant risk to the patient during transport. For those facilities with access to this technology, safe practice guidelines exist only for procedures performed within an intraoperative MRI. There are currently no safe practice guidelines or parameters available for facilities looking to integrate this technology into practice in conventional MRI suites. Performing neurosurgical procedures in a diagnostic MRI suite does require precautionary measures. The relative novelty of technology and workflows for direct MRI-guided procedures requires consideration of safe practice recommendations, including those pertaining to infection control and magnet safety issues. This article proposes a framework of safe practice recommendations designed for assessing readiness and optimization of MRI-guided neurosurgical interventions in the diagnostic MRI suite in an effort to mitigate patient risk. The framework is based on existing clinical evidence, recommendations, and guidelines related to infection control and prevention, health care-associated infections, and magnet safety, as well as the clinical and practical experience of neurosurgeons utilizing this technology. © 2017 American Society for Healthcare Risk Management of the American Hospital Association.

About a method for compressing x-ray computed microtomography data

NASA Astrophysics Data System (ADS)

Mancini, Lucia; Kourousias, George; Billè, Fulvio; De Carlo, Francesco; Fidler, Aleš

2018-04-01

The management of scientific data is of high importance especially for experimental techniques that produce big data volumes. Such a technique is x-ray computed tomography (CT) and its community has introduced advanced data formats which allow for better management of experimental data. Rather than the organization of the data and the associated meta-data, the main topic on this work is data compression and its applicability to experimental data collected from a synchrotron-based CT beamline at the Elettra-Sincrotrone Trieste facility (Italy) and studies images acquired from various types of samples. This study covers parallel beam geometry, but it could be easily extended to a cone-beam one. The reconstruction workflow used is the one currently in operation at the beamline. Contrary to standard image compression studies, this manuscript proposes a systematic framework and workflow for the critical examination of different compression techniques and does so by applying it to experimental data. Beyond the methodology framework, this study presents and examines the use of JPEG-XR in combination with HDF5 and TIFF formats providing insights and strategies on data compression and image quality issues that can be used and implemented at other synchrotron facilities and laboratory systems. In conclusion, projection data compression using JPEG-XR appears as a promising, efficient method to reduce data file size and thus to facilitate data handling and image reconstruction.

SIERRA Code Coupling Module: Arpeggio User Manual Version 4.44

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

Subia, Samuel R.; Overfelt, James R.; Baur, David G.

2017-04-01

The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested inmore » coupled applications via simple examples of its usage.« less

Service composition towards increasing end-user accessibility.

PubMed

Kaklanis, Nikolaos; Votis, Konstantinos; Tzovaras, Dimitrios

2015-01-01

This paper presents the Cloud4all Service Synthesizer Tool, a framework that enables efficient orchestration of accessibility services, as well as their combination into complex forms, providing more advanced functionalities towards increasing the accessibility of end-users with various types of functional limitations. The supported services are described formally within an ontology, enabling, thus, semantic service composition. The proposed service composition approach is based on semantic matching between services specifications on the one hand and user needs/preferences and current context of use on the other hand. The use of automatic composition of accessibility services can significantly enhance end-users' accessibility, especially in cases where assistive solutions are not available in their device.

A Framework for Sharing and Integrating Remote Sensing and GIS Models Based on Web Service

PubMed Central

Chen, Zeqiang; Lin, Hui; Chen, Min; Liu, Deer; Bao, Ying; Ding, Yulin

2014-01-01

Sharing and integrating Remote Sensing (RS) and Geographic Information System/Science (GIS) models are critical for developing practical application systems. Facilitating model sharing and model integration is a problem for model publishers and model users, respectively. To address this problem, a framework based on a Web service for sharing and integrating RS and GIS models is proposed in this paper. The fundamental idea of the framework is to publish heterogeneous RS and GIS models into standard Web services for sharing and interoperation and then to integrate the RS and GIS models using Web services. For the former, a “black box” and a visual method are employed to facilitate the publishing of the models as Web services. For the latter, model integration based on the geospatial workflow and semantic supported marching method is introduced. Under this framework, model sharing and integration is applied for developing the Pearl River Delta water environment monitoring system. The results show that the framework can facilitate model sharing and model integration for model publishers and model users. PMID:24901016

A framework for sharing and integrating remote sensing and GIS models based on Web service.

PubMed

Chen, Zeqiang; Lin, Hui; Chen, Min; Liu, Deer; Bao, Ying; Ding, Yulin

2014-01-01

Sharing and integrating Remote Sensing (RS) and Geographic Information System/Science (GIS) models are critical for developing practical application systems. Facilitating model sharing and model integration is a problem for model publishers and model users, respectively. To address this problem, a framework based on a Web service for sharing and integrating RS and GIS models is proposed in this paper. The fundamental idea of the framework is to publish heterogeneous RS and GIS models into standard Web services for sharing and interoperation and then to integrate the RS and GIS models using Web services. For the former, a "black box" and a visual method are employed to facilitate the publishing of the models as Web services. For the latter, model integration based on the geospatial workflow and semantic supported marching method is introduced. Under this framework, model sharing and integration is applied for developing the Pearl River Delta water environment monitoring system. The results show that the framework can facilitate model sharing and model integration for model publishers and model users.

SQL Collaborative Learning Framework Based on SOA

NASA Astrophysics Data System (ADS)

Armiati, S.; Awangga, RM

2018-04-01

The research is focused on designing collaborative learning-oriented framework fulfilment service in teaching SQL Oracle 10g. Framework built a foundation of academic fulfilment service performed by a layer of the working unit in collaboration with Program Studi Manajemen Informatika. In the design phase defined what form of collaboration models and information technology proposed for Program Studi Manajemen Informatika by using a framework of collaboration inspired by the stages of modelling a Service Oriented Architecture (SOA). Stages begin with analyzing subsystems, this activity is used to determine subsystem involved and reliance as well as workflow between the subsystems. After the service can be identified, the second phase is designing the component specifications, which details the components that are implemented in the service to include the data, rules, services, profiles can be configured, and variations. The third stage is to allocate service, set the service to the subsystems that have been identified, and its components. Implementation framework contributes to the teaching guides and application architecture that can be used as a landing realize an increase in service by applying information technology.

Analysis of Business Connections Utilizing Theory of Topology of Random Graphs

NASA Astrophysics Data System (ADS)

Trelewicz, Jennifer Q.; Volovich, Igor V.

2006-03-01

A business ecosystem is a system that describes interactions between organizations. In this paper, we build a theoretical framework that defines a model which can be used to analyze the business ecosystem. The basic concepts within the framework are organizations, business connections, and market, that are all defined in the paper. Many researchers analyze the performance and structure of business using the workflow of the business. Our work in business connections answers a different set of questions, concerning the monetary value in the business ecosystem, rather than the task-interaction view that is provided by workflow analysis. We apply methods for analysis of the topology of complex networks, characterized by the concepts of small path length, clustering, and scale-free degree distributions. To model the dynamics of the business ecosystem we analyze the notion of the state of an organization at a given instant of time. We point out that the notion of state in this case is fundamentally different from the concept of state of the system which is used in classical or quantum physics. To describe the state of the organization at a given time one has to know the probability of payments to contracts which in fact depend on the future behavior of the agents on the market. Therefore methods of p-adic analysis are appropriate to explore such a behavior. Microeconomic and macroeconomic factors are indivisible and moreover the actual state of the organization depends on the future. In this framework some simple models are analyzed in detail. Company strategy can be influenced by analysis of models, which can provide a probabilistic understanding of the market, giving degrees of predictability.

Marginal discrepancy of noble metal-ceramic fixed dental prosthesis frameworks fabricated by conventional and digital technologies.

PubMed

Afify, Ahmed; Haney, Stephan; Verrett, Ronald; Mansueto, Michael; Cray, James; Johnson, Russell

2018-02-01

Studies evaluating the marginal adaptation of available computer-aided design and computer-aided manufacturing (CAD-CAM) noble alloys for metal-ceramic prostheses are lacking. The purpose of this in vitro study was to evaluate the vertical marginal adaptation of cast, milled, and direct metal laser sintered (DMLS) noble metal-ceramic 3-unit fixed partial denture (FDP) frameworks before and after fit adjustments. Two typodont teeth were prepared for metal-ceramic FDP abutments. An acrylic resin pattern of the prepared teeth was fabricated and cast in nickel-chromium (Ni-Cr) alloy. Each specimen group (cast, milled, DMLS) was composed of 12 casts made from 12 impressions (n=12). A single design for the FDP substructure was created on a laboratory scanner and used for designing the specimens in the 3 groups. Each specimen was fitted to its corresponding cast by using up to 5 adjustment cycles, and marginal discrepancies were measured on the master Ni-Cr model before and after laboratory fit adjustments. The milled and DMLS groups had smaller marginal discrepancy measurements than those of the cast group (P<.001). Significant differences were found in the number of adjustments among the groups, with the milled group requiring the minimum number of adjustments, followed by the DMLS and cast groups (F=30.643, P<.001). Metal-ceramic noble alloy frameworks fabricated by using a CAD-CAM workflow had significantly smaller marginal discrepancies compared with those with a traditional cast workflow, with the milled group demonstrating the best marginal fit among the 3 test groups. Manual refining significantly enhanced the marginal fit of all groups. All 3 groups demonstrated marginal discrepancies within the range of clinical acceptability. Copyright © 2017 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Integration of prior CT into CBCT reconstruction for improved image quality via reconstruction of difference: first patient studies

NASA Astrophysics Data System (ADS)

Zhang, Hao; Gang, Grace J.; Lee, Junghoon; Wong, John; Stayman, J. Webster

2017-03-01

Purpose: There are many clinical situations where diagnostic CT is used for an initial diagnosis or treatment planning, followed by one or more CBCT scans that are part of an image-guided intervention. Because the high-quality diagnostic CT scan is a rich source of patient-specific anatomical knowledge, this provides an opportunity to incorporate the prior CT image into subsequent CBCT reconstruction for improved image quality. We propose a penalized-likelihood method called reconstruction of difference (RoD), to directly reconstruct differences between the CBCT scan and the CT prior. In this work, we demonstrate the efficacy of RoD with clinical patient datasets. Methods: We introduce a data processing workflow using the RoD framework to reconstruct anatomical changes between the prior CT and current CBCT. This workflow includes processing steps to account for non-anatomical differences between the two scans including 1) scatter correction for CBCT datasets due to increased scatter fractions in CBCT data; 2) histogram matching for attenuation variations between CT and CBCT; and 3) registration for different patient positioning. CBCT projection data and CT planning volumes for two radiotherapy patients - one abdominal study and one head-and-neck study - were investigated. Results: In comparisons between the proposed RoD framework and more traditional FDK and penalized-likelihood reconstructions, we find a significant improvement in image quality when prior CT information is incorporated into the reconstruction. RoD is able to provide additional low-contrast details while correctly incorporating actual physical changes in patient anatomy. Conclusions: The proposed framework provides an opportunity to either improve image quality or relax data fidelity constraints for CBCT imaging when prior CT studies of the same patient are available. Possible clinical targets include CBCT image-guided radiotherapy and CBCT image-guided surgeries.

Active Provenance in Data-intensive Research

NASA Astrophysics Data System (ADS)

Spinuso, Alessandro; Mihajlovski, Andrej; Filgueira, Rosa; Atkinson, Malcolm

2017-04-01

Scientific communities are building platforms where the usage of data-intensive workflows is crucial to conduct their research campaigns. However managing and effectively support the understanding of the 'live' processes, fostering computational steering, sharing and re-use of data and methods, present several bottlenecks. These are often caused by the poor level of documentation on the methods and the data and how users interact with it. This work wants to explore how in such systems, flexibility in the management of the provenance and its adaptation to the different users and application contexts can lead to new opportunities for its exploitation, improving productivity. In particular, this work illustrates a conceptual and technical framework enabling tunable and actionable provenance in data-intensive workflow systems in support of reproducible science. It introduces the concept of Agile data-intensive systems to define the characteristic of our target platform. It shows a novel approach to the integration of provenance mechanisms, offering flexibility in the scale and in the precision of the provenance data collected, ensuring its relevance to the domain of the data-intensive task, fostering its rapid exploitation. The contributions address aspects of the scale of the provenance records, their usability and active role in the research life-cycle. We will discuss the use of dynamically generated provenance types as the approach for the integration of provenance mechanisms into a data-intensive workflow system. Enabling provenance can be transparent to the workflow user and developer, as well as fully controllable and customisable, depending from their expertise and the application's reproducibility, monitoring and validation requirements. The API that allows the realisation and adoption of a provenance type is presented, especially for what concerns the support of provenance profiling, contextualisation and precision. An actionable approach to provenance management will be also discussed, enabling provenance-driven operations at runtime, regardless of the enactment technologies and connectivity impediments. We proposes a framework based on concepts such as provenance clusters and provenance sensors, envisaging new potential for exploiting large quantities of provenance traces at runtime. Finally the work will also introduce how the underlying provenance model can be explored with big-data visualization techniques, aiming at producing comprehensive and interactive views on top of large and heterogeneous provenance data. We will demonstrate the adoption of alternative visualisation methods, from detailed and localised interactive graphs to radial-views, serving different purposes and expertise. Combining provenance types, selective rules, extensible metadata with reactive clustering opens a new and more versatile role of the lineage information in the research life-cycle, thanks to its improved usability. The flexible profiling of the proposed framework offers aid to the human analysis of the process, with the support of advanced and intuitive interactive graphical tools. The Active provenance methods are discussed in the context of a real implementation for a data-intensive library (dispel4py) and its adoption within use cases for computational seismology, climate studies and generic correlation analysis.

Leveraging advances in biology to design biomaterials

NASA Astrophysics Data System (ADS)

Darnell, Max; Mooney, David J.

2017-12-01

Biomaterials have dramatically increased in functionality and complexity, allowing unprecedented control over the cells that interact with them. From these engineering advances arises the prospect of improved biomaterial-based therapies, yet practical constraints favour simplicity. Tools from the biology community are enabling high-resolution and high-throughput bioassays that, if incorporated into a biomaterial design framework, could help achieve unprecedented functionality while minimizing the complexity of designs by identifying the most important material parameters and biological outputs. However, to avoid data explosions and to effectively match the information content of an assay with the goal of the experiment, material screens and bioassays must be arranged in specific ways. By borrowing methods to design experiments and workflows from the bioprocess engineering community, we outline a framework for the incorporation of next-generation bioassays into biomaterials design to effectively optimize function while minimizing complexity. This framework can inspire biomaterials designs that maximize functionality and translatability.

Proposal for fulfilling strategic objectives of the U.S. Roadmap for national action on clinical decision support through a service-oriented architecture leveraging HL7 services.

PubMed

Kawamoto, Kensaku; Lobach, David F

2007-01-01

Despite their demonstrated effectiveness, clinical decision support (CDS) systems are not widely used within the U.S. The Roadmap for National Action on Clinical Decision Support, published in June 2006 by the American Medical Informatics Association, identifies six strategic objectives for achieving widespread adoption of effective CDS capabilities. In this manuscript, we propose a Service-Oriented Architecture (SOA) for CDS that facilitates achievement of these six objectives. Within the proposed framework, CDS capabilities are implemented through the orchestration of independent software services whose interfaces are being standardized by Health Level 7 and the Object Management Group through their joint Healthcare Services Specification Project (HSSP). Core services within this framework include the HSSP Decision Support Service, the HSSP Common Terminology Service, and the HSSP Retrieve, Locate, and Update Service. Our experiences, and those of others, indicate that the proposed SOA approach to CDS could enable the widespread adoption of effective CDS within the U.S. health care system.

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.

Software Architecture for a Virtual Environment for Nano Scale Assembly (VENSA).

PubMed

Lee, Yong-Gu; Lyons, Kevin W; Feng, Shaw C

2004-01-01

A Virtual Environment (VE) uses multiple computer-generated media to let a user experience situations that are temporally and spatially prohibiting. The information flow between the user and the VE is bidirectional and the user can influence the environment. The software development of a VE requires orchestrating multiple peripherals and computers in a synchronized way in real time. Although a multitude of useful software components for VEs exists, many of these are packaged within a complex framework and can not be used separately. In this paper, an architecture is presented which is designed to let multiple frameworks work together while being shielded from the application program. This architecture, which is called the Virtual Environment for Nano Scale Assembly (VENSA), has been constructed for interfacing with an optical tweezers instrument for nanotechnology development. However, this approach can be generalized for most virtual environments. Through the use of VENSA, the programmer can rely on existing solutions and concentrate more on the application software design.

Software Architecture for a Virtual Environment for Nano Scale Assembly (VENSA)

PubMed Central

Lee, Yong-Gu; Lyons, Kevin W.; Feng, Shaw C.

2004-01-01

A Virtual Environment (VE) uses multiple computer-generated media to let a user experience situations that are temporally and spatially prohibiting. The information flow between the user and the VE is bidirectional and the user can influence the environment. The software development of a VE requires orchestrating multiple peripherals and computers in a synchronized way in real time. Although a multitude of useful software components for VEs exists, many of these are packaged within a complex framework and can not be used separately. In this paper, an architecture is presented which is designed to let multiple frameworks work together while being shielded from the application program. This architecture, which is called the Virtual Environment for Nano Scale Assembly (VENSA), has been constructed for interfacing with an optical tweezers instrument for nanotechnology development. However, this approach can be generalized for most virtual environments. Through the use of VENSA, the programmer can rely on existing solutions and concentrate more on the application software design. PMID:27366610

Framework for the Integration of Multi-Instrument Pipelines in the BepiColombo Science Operations Control System

NASA Astrophysics Data System (ADS)

Pérez-López, F.; Vallejo, J. C.; Martínez, S.; Ortiz, I.; Macfarlane, A.; Osuna, P.; Gill, R.; Casale, M.

2015-09-01

BepiColombo is an interdisciplinary ESA mission to explore the planet Mercury in cooperation with JAXA. The mission consists of two separate orbiters: ESA's Mercury Planetary Orbiter (MPO) and JAXA's Mercury Magnetospheric Orbiter (MMO), which are dedicated to the detailed study of the planet and its magnetosphere. The MPO scientific payload comprises eleven instruments packages covering different disciplines developed by several European teams. This paper describes the design and development approach of the framework required to support the operation of the distributed BepiColombo MPO instruments pipelines, developed and operated from different locations, but designed as a single entity. An architecture based on primary-redundant configuration, fully integrated into the BepiColombo Science Operations Control System (BSCS), has been selected, where some instrument pipelines will be operated from the instrument team's data processing centres, having a pipeline replica that can be run from the Science Ground Segment (SGS), while others will be executed as primary pipelines from the SGS, adopting the SGS the pipeline orchestration role.

Partnership For Edge Physics Simulation

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

Parashar, Manish

In this effort, we will extend our prior work as part of CPES (i.e., DART and DataSpaces) to support in-situ tight coupling between application codes that exploits data locality and core-level parallelism to maximize on-chip data exchange and reuse. This will be accomplished by mapping coupled simulations so that the data exchanges are more localized within the nodes. Coupled simulation workflows can more effectively utilize the resources available on emerging HEC platforms if they can be mapped and executed to exploit data locality as well as the communication patterns between application components. Scheduling and running such workflows requires an extendedmore » framework that should provide a unified hybrid abstraction to enable coordination and data sharing across computation tasks that run on the heterogeneous multi-core-based systems, and develop a data-locality based dynamic tasks scheduling approach to increase on-chip or intra-node data exchanges and in-situ execution. This effort will extend our prior work as part of CPES (i.e., DART and DataSpaces), which provided a simple virtual shared-space abstraction hosted at the staging nodes, to support application coordination, data sharing and active data processing services. Moreover, it will transparently manage the low-level operations associated with the inter-application data exchange, such as data redistributions, and will enable running coupled simulation workflow on multi-cores computing platforms.« less

SADI, SHARE, and the in silico scientific method

PubMed Central

2010-01-01

Background The emergence and uptake of Semantic Web technologies by the Life Sciences provides exciting opportunities for exploring novel ways to conduct in silico science. Web Service Workflows are already becoming first-class objects in “the new way”, and serve as explicit, shareable, referenceable representations of how an experiment was done. In turn, Semantic Web Service projects aim to facilitate workflow construction by biological domain-experts such that workflows can be edited, re-purposed, and re-published by non-informaticians. However the aspects of the scientific method relating to explicit discourse, disagreement, and hypothesis generation have remained relatively impervious to new technologies. Results Here we present SADI and SHARE - a novel Semantic Web Service framework, and a reference implementation of its client libraries. Together, SADI and SHARE allow the semi- or fully-automatic discovery and pipelining of Semantic Web Services in response to ad hoc user queries. Conclusions The semantic behaviours exhibited by SADI and SHARE extend the functionalities provided by Description Logic Reasoners such that novel assertions can be automatically added to a data-set without logical reasoning, but rather by analytical or annotative services. This behaviour might be applied to achieve the “semantification” of those aspects of the in silico scientific method that are not yet supported by Semantic Web technologies. We support this suggestion using an example in the clinical research space. PMID:21210986

Orchestrating Distributed Resource Ensembles for Petascale Science

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

Baldin, Ilya; Mandal, Anirban; Ruth, Paul

2014-04-24

Distributed, data-intensive computational science applications of interest to DOE scientific com- munities move large amounts of data for experiment data management, distributed analysis steps, remote visualization, and accessing scientific instruments. These applications need to orchestrate ensembles of resources from multiple resource pools and interconnect them with high-capacity multi- layered networks across multiple domains. It is highly desirable that mechanisms are designed that provide this type of resource provisioning capability to a broad class of applications. It is also important to have coherent monitoring capabilities for such complex distributed environments. In this project, we addressed these problems by designing an abstractmore » API, enabled by novel semantic resource descriptions, for provisioning complex and heterogeneous resources from multiple providers using their native provisioning mechanisms and control planes: computational, storage, and multi-layered high-speed network domains. We used an extensible resource representation based on semantic web technologies to afford maximum flexibility to applications in specifying their needs. We evaluated the effectiveness of provisioning using representative data-intensive ap- plications. We also developed mechanisms for providing feedback about resource performance to the application, to enable closed-loop feedback control and dynamic adjustments to resource allo- cations (elasticity). This was enabled through development of a novel persistent query framework that consumes disparate sources of monitoring data, including perfSONAR, and provides scalable distribution of asynchronous notifications.« less

Predictive assimilation framework to support contaminated site understanding and remediation

NASA Astrophysics Data System (ADS)

Versteeg, R. J.; Bianchi, M.; Hubbard, S. S.

2014-12-01

Subsurface system behavior at contaminated sites is driven and controlled by the interplay of physical, chemical, and biological processes occurring at multiple temporal and spatial scales. Effective remediation and monitoring planning requires an understanding of this complexity that is current, predictive (with some level of confidence) and actionable. We present and demonstrate a predictive assimilation framework (PAF). This framework automatically ingests, quality controls and stores near real-time environmental data and processes these data using different inversion and modeling codes to provide information on the current state and evolution of the subsurface system. PAF is implemented as a cloud based software application which has five components: (1) data acquisition, (2) data management, (3) data assimilation and processing, (4) visualization and result deliver and (5) orchestration. Access to and interaction with PAF is done through a standard browser. PAF is designed to be modular so that it can ingest and process different data streams dependent on the site. We will present an implementation of PAF which uses data from a highly instrumented site (the DOE Rifle Subsurface Biogeochemistry Field Observatory in Rifle, Colorado) for which PAF automatically ingests hydrological data and forward models groundwater flow in the saturated zone.

Systematic Refinement of a Health Information Technology Time and Motion Workflow Instrument for Inpatient Nursing Care using a Standardized Interface Terminology

PubMed Central

Zhang, Yi; Monsen, Karen A; Adam, Terrence J; Pieczkiewicz, David S; Daman, Megan; Melton, Genevieve B

2011-01-01

Time and motion (T&M) studies provide an objective method to measure the expenditure of time by clinicians. While some instruments for T&M studies have been designed to evaluate health information technology (HIT), these instruments have not been designed for nursing workflow. We took an existing open source HIT T&M study application designed to evaluate physicians in the ambulatory setting and rationally adapted it through empiric observations to record nursing activities in the inpatient setting and linked this instrument to an existing interface terminology, the Omaha System. Nursing activities involved several dimensions and could include multiple activities occurring simultaneously, requiring significant instrument redesign. 94% of the activities from the study instrument mapped adequately to the Omaha System. T&M study instruments require customization in design optimize them for different environments, such as inpatient nursing, to enable optimal data collection. Interface terminologies show promise as a framework for recording and analyzing T&M study data. PMID:22195228

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

Bowen, Benjamin; Ruebel, Oliver; Fischer, Curt Fischer R.

BASTet is an advanced software library written in Python. BASTet serves as the analysis and storage library for the OpenMSI project. BASTet is an integrate framework for: i) storage of spectral imaging data, ii) storage of derived analysis data, iii) provenance of analyses, iv) integration and execution of analyses via complex workflows. BASTet implements the API for the HDF5 storage format used by OpenMSI. Analyses that are developed using BASTet benefit from direct integration with storage format, automatic tracking of provenance, and direct integration with command-line and workflow execution tools. BASTet also defines interfaces to enable developers to directly integratemore » their analysis with OpenMSI's web-based viewing infrastruture without having to know OpenMSI. BASTet also provides numerous helper classes and tools to assist with the conversion of data files, ease parallel implementation of analysis algorithms, ease interaction with web-based functions, description methods for data reduction. BASTet also includes detailed developer documentation, user tutorials, iPython notebooks, and other supporting documents.« less

A Workflow for Global Sensitivity Analysis of PBPK Models

PubMed Central

McNally, Kevin; Cotton, Richard; Loizou, George D.

2011-01-01

Physiologically based pharmacokinetic (PBPK) models have a potentially significant role in the development of a reliable predictive toxicity testing strategy. The structure of PBPK models are ideal frameworks into which disparate in vitro and in vivo data can be integrated and utilized to translate information generated, using alternative to animal measures of toxicity and human biological monitoring data, into plausible corresponding exposures. However, these models invariably include the description of well known non-linear biological processes such as, enzyme saturation and interactions between parameters such as, organ mass and body mass. Therefore, an appropriate sensitivity analysis (SA) technique is required which can quantify the influences associated with individual parameters, interactions between parameters and any non-linear processes. In this report we have defined the elements of a workflow for SA of PBPK models that is computationally feasible, accounts for interactions between parameters, and can be displayed in the form of a bar chart and cumulative sum line (Lowry plot), which we believe is intuitive and appropriate for toxicologists, risk assessors, and regulators. PMID:21772819

Maximum unbiased validation (MUV) data sets for virtual screening based on PubChem bioactivity data.

PubMed

Rohrer, Sebastian G; Baumann, Knut

2009-02-01

Refined nearest neighbor analysis was recently introduced for the analysis of virtual screening benchmark data sets. It constitutes a technique from the field of spatial statistics and provides a mathematical framework for the nonparametric analysis of mapped point patterns. Here, refined nearest neighbor analysis is used to design benchmark data sets for virtual screening based on PubChem bioactivity data. A workflow is devised that purges data sets of compounds active against pharmaceutically relevant targets from unselective hits. Topological optimization using experimental design strategies monitored by refined nearest neighbor analysis functions is applied to generate corresponding data sets of actives and decoys that are unbiased with regard to analogue bias and artificial enrichment. These data sets provide a tool for Maximum Unbiased Validation (MUV) of virtual screening methods. The data sets and a software package implementing the MUV design workflow are freely available at http://www.pharmchem.tu-bs.de/lehre/baumann/MUV.html.

Building a Semantic Framework for eScience

NASA Astrophysics Data System (ADS)

Movva, S.; Ramachandran, R.; Maskey, M.; Li, X.

2009-12-01

The e-Science vision focuses on the use of advanced computing technologies to support scientists. Recent research efforts in this area have focused primarily on “enabling” use of infrastructure resources for both data and computational access especially in Geosciences. One of the existing gaps in the existing e-Science efforts has been the failure to incorporate stable semantic technologies within the design process itself. In this presentation, we describe our effort in designing a framework for e-Science built using Service Oriented Architecture. Our framework provides users capabilities to create science workflows and mine distributed data. Our e-Science framework is being designed around a mass market tool to promote reusability across many projects. Semantics is an integral part of this framework and our design goal is to leverage the latest stable semantic technologies. The use of these stable semantic technologies will provide the users of our framework the useful features such as: allow search engines to find their content with RDFa tags; create RDF triple data store for their content; create RDF end points to share with others; and semantically mash their content with other online content available as RDF end point.

Usability testing of Avoiding Diabetes Thru Action Plan Targeting (ADAPT) decision support for integrating care-based counseling of pre-diabetes in an electronic health record

PubMed Central

Chrimes, Dillon; Kushniruk, Andre; Kitos, Nicole R.

2014-01-01

Purpose Usability testing can be used to evaluate human computer interaction (HCI) and communication in shared decision making (SDM) for patient-provider behavioral change and behavioral contracting. Traditional evaluations of usability using scripted or mock patient scenarios with think-aloud protocol analysis provide a to identify HCI issues. In this paper we describe the application of these methods in the evaluation of the Avoiding Diabetes Thru Action Plan Targeting (ADAPT) tool, and test the usability of the tool to support the ADAPT framework for integrated care counseling of pre-diabetes. The think-aloud protocol analysis typically does not provide an assessment of how patient-provider interactions are effected in “live” clinical workflow or whether a tool is successful. Therefore, “Near-live” clinical simulations involving applied simulation methods were used to compliment the think-aloud results. This complementary usability technique was used to test the end-user HCI and tool performance by more closely mimicking the clinical workflow and capturing interaction sequences along with assessing the functionality of computer module prototypes on clinician workflow. We expected this method to further complement and provide different usability findings as compared to think-aloud analysis. Together, this mixed method evaluation provided comprehensive and realistic feedback for iterative refinement of the ADAPT system prior to implementation. Methods The study employed two phases of testing of a new interactive ADAPT tool that embedded an evidence-based shared goal setting component into primary care workflow for dealing with pre-diabetes counseling within a commercial physician office electronic health record (EHR). Phase I applied usability testing that involved “think-aloud” protocol analysis of 8 primary care providers interacting with several scripted clinical scenarios. Phase II used “near-live” clinical simulations of 5 providers interacting with standardized trained patient actors enacting the clinical scenario of counseling for pre-diabetes, each of whom had a pedometer that recorded the number of steps taken over a week. In both phases, all sessions were audio-taped and motion screen-capture software was activated for onscreen recordings. Transcripts were coded using iterative qualitative content analysis methods. Results In Phase I, the impact of the components and layout of ADAPT on user’s Navigation, Understandability, and Workflow were associated with the largest volume of negative comments (i.e. approximately 80% of end-user commentary), while Usability and Content of ADAPT were representative of more positive than negative user commentary. The heuristic category of Usability had a positive-to-negative comment ratio of 2.1, reflecting positive perception of the usability of the tool, its functionality, and overall co-productive utilization of ADAPT. However, there were mixed perceptions about content (i.e., how the information was displayed, organized and described in the tool). In Phase II, the duration of patient encounters was approximately 10 minutes with all of the Patient Instructions (prescriptions) and behavioral contracting being activated at the end of each visit. Upon activation, providers accepted the pathway prescribed by the tool 100% of the time and completed all the fields in the tool in the simulation cases. Only 14% of encounter time was spent using the functionality of the ADAPT tool in terms of keystrokes and entering relevant data. The rest of the time was spent on communication and dialogue to populate the patient instructions. In all cases, the interaction sequence of reviewing and discussing exercise and diet of the patient was linked to the functionality of the ADAPT tool in terms of monitoring, response-efficacy, self-efficacy, and negotiation in the patient-provider dialogue. There was a change from one-way dialogue to two-way dialogue and negotiation that ended in a behavioral contract. This change demonstrated the tool’s sequence, which supported recording current exercise and diet followed by a diet and exercise goal setting procedure to reduce the risk of diabetes onset. Conclusions This study demonstrated that “think-aloud” protocol analysis with “near-live” clinical simulations provided a successful usability evaluation of a new primary care pre-diabetes shared goal setting tool. Each phase of the study provided complementary observations on problems with the new onscreen tool and was used to show the influence of the ADAPT framework on the usability, workflow integration, and communication between the patient and provider. The think-aloud tests with the provider showed the tool can be used according to the ADAPT framework (exercise-to-diet behavior change and tool utilization), while the clinical simulations revealed the ADAPT framework to realistically support patient-provider communication to obtain behavioral change contract. SDM interactions and mechanisms affecting protocol-based care can be more completely captured by combining “near-live” clinical simulations with traditional “think-aloud analysis” which augments clinician utilization. More analysis is required to verify if the rich communication actions found in Phase II compliment clinical workflows. PMID:24981988

Usability testing of Avoiding Diabetes Thru Action Plan Targeting (ADAPT) decision support for integrating care-based counseling of pre-diabetes in an electronic health record.

PubMed

Chrimes, Dillon; Kitos, Nicole R; Kushniruk, Andre; Mann, Devin M

2014-09-01

Usability testing can be used to evaluate human-computer interaction (HCI) and communication in shared decision making (SDM) for patient-provider behavioral change and behavioral contracting. Traditional evaluations of usability using scripted or mock patient scenarios with think-aloud protocol analysis provide a way to identify HCI issues. In this paper we describe the application of these methods in the evaluation of the Avoiding Diabetes Thru Action Plan Targeting (ADAPT) tool, and test the usability of the tool to support the ADAPT framework for integrated care counseling of pre-diabetes. The think-aloud protocol analysis typically does not provide an assessment of how patient-provider interactions are effected in "live" clinical workflow or whether a tool is successful. Therefore, "Near-live" clinical simulations involving applied simulation methods were used to compliment the think-aloud results. This complementary usability technique was used to test the end-user HCI and tool performance by more closely mimicking the clinical workflow and capturing interaction sequences along with assessing the functionality of computer module prototypes on clinician workflow. We expected this method to further complement and provide different usability findings as compared to think-aloud analysis. Together, this mixed method evaluation provided comprehensive and realistic feedback for iterative refinement of the ADAPT system prior to implementation. The study employed two phases of testing of a new interactive ADAPT tool that embedded an evidence-based shared goal setting component into primary care workflow for dealing with pre-diabetes counseling within a commercial physician office electronic health record (EHR). Phase I applied usability testing that involved "think-aloud" protocol analysis of eight primary care providers interacting with several scripted clinical scenarios. Phase II used "near-live" clinical simulations of five providers interacting with standardized trained patient actors enacting the clinical scenario of counseling for pre-diabetes, each of whom had a pedometer that recorded the number of steps taken over a week. In both phases, all sessions were audio-taped and motion screen-capture software was activated for onscreen recordings. Transcripts were coded using iterative qualitative content analysis methods. In Phase I, the impact of the components and layout of ADAPT on user's Navigation, Understandability, and Workflow were associated with the largest volume of negative comments (i.e. approximately 80% of end-user commentary), while Usability and Content of ADAPT were representative of more positive than negative user commentary. The heuristic category of Usability had a positive-to-negative comment ratio of 2.1, reflecting positive perception of the usability of the tool, its functionality, and overall co-productive utilization of ADAPT. However, there were mixed perceptions about content (i.e., how the information was displayed, organized and described in the tool). In Phase II, the duration of patient encounters was approximately 10 min with all of the Patient Instructions (prescriptions) and behavioral contracting being activated at the end of each visit. Upon activation, providers accepted the pathway prescribed by the tool 100% of the time and completed all the fields in the tool in the simulation cases. Only 14% of encounter time was spent using the functionality of the ADAPT tool in terms of keystrokes and entering relevant data. The rest of the time was spent on communication and dialog to populate the patient instructions. In all cases, the interaction sequence of reviewing and discussing exercise and diet of the patient was linked to the functionality of the ADAPT tool in terms of monitoring, response-efficacy, self-efficacy, and negotiation in the patient-provider dialog. There was a change from one-way dialog to two-way dialog and negotiation that ended in a behavioral contract. This change demonstrated the tool's sequence, which supported recording current exercise and diet followed by a diet and exercise goal setting procedure to reduce the risk of diabetes onset. This study demonstrated that "think-aloud" protocol analysis with "near-live" clinical simulations provided a successful usability evaluation of a new primary care pre-diabetes shared goal setting tool. Each phase of the study provided complementary observations on problems with the new onscreen tool and was used to show the influence of the ADAPT framework on the usability, workflow integration, and communication between the patient and provider. The think-aloud tests with the provider showed the tool can be used according to the ADAPT framework (exercise-to-diet behavior change and tool utilization), while the clinical simulations revealed the ADAPT framework to realistically support patient-provider communication to obtain behavioral change contract. SDM interactions and mechanisms affecting protocol-based care can be more completely captured by combining "near-live" clinical simulations with traditional "think-aloud analysis" which augments clinician utilization. More analysis is required to verify if the rich communication actions found in Phase II compliment clinical workflows. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Combining patient journey modelling and visual multi-agent computer simulation: a framework to improving knowledge translation in a healthcare environment.

PubMed

Curry, Joanne; Fitzgerald, Anneke; Prodan, Ante; Dadich, Ann; Sloan, Terry

2014-01-01

This article focuses on a framework that will investigate the integration of two disparate methodologies: patient journey modelling and visual multi-agent simulation, and its impact on the speed and quality of knowledge translation to healthcare stakeholders. Literature describes patient journey modelling and visual simulation as discrete activities. This paper suggests that their combination and their impact on translating knowledge to practitioners are greater than the sum of the two technologies. The test-bed is ambulatory care and the goal is to determine if this approach can improve health services delivery, workflow, and patient outcomes and satisfaction. The multidisciplinary research team is comprised of expertise in patient journey modelling, simulation, and knowledge translation.

nmsBuilder: Freeware to create subject-specific musculoskeletal models for OpenSim.

PubMed

Valente, Giordano; Crimi, Gianluigi; Vanella, Nicola; Schileo, Enrico; Taddei, Fulvia

2017-12-01

Musculoskeletal modeling and simulations of movement have been increasingly used in orthopedic and neurological scenarios, with increased attention to subject-specific applications. In general, musculoskeletal modeling applications have been facilitated by the development of dedicated software tools; however, subject-specific studies have been limited also by time-consuming modeling workflows and high skilled expertise required. In addition, no reference tools exist to standardize the process of musculoskeletal model creation and make it more efficient. Here we present a freely available software application, nmsBuilder 2.0, to create musculoskeletal models in the file format of OpenSim, a widely-used open-source platform for musculoskeletal modeling and simulation. nmsBuilder 2.0 is the result of a major refactoring of a previous implementation that moved a first step toward an efficient workflow for subject-specific model creation. nmsBuilder includes a graphical user interface that provides access to all functionalities, based on a framework for computer-aided medicine written in C++. The operations implemented can be used in a workflow to create OpenSim musculoskeletal models from 3D surfaces. A first step includes data processing to create supporting objects necessary to create models, e.g. surfaces, anatomical landmarks, reference systems; and a second step includes the creation of OpenSim objects, e.g. bodies, joints, muscles, and the corresponding model. We present a case study using nmsBuilder 2.0: the creation of an MRI-based musculoskeletal model of the lower limb. The model included four rigid bodies, five degrees of freedom and 43 musculotendon actuators, and was created from 3D surfaces of the segmented images of a healthy subject through the modeling workflow implemented in the software application. We have presented nmsBuilder 2.0 for the creation of musculoskeletal OpenSim models from image-based data, and made it freely available via nmsbuilder.org. This application provides an efficient workflow for model creation and helps standardize the process. We hope this would help promote personalized applications in musculoskeletal biomechanics, including larger sample size studies, and might also represent a basis for future developments for specific applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Toward a geoinformatics framework for understanding the social and biophysical influences on urban nutrient pollution due to residential impervious service connectivity

NASA Astrophysics Data System (ADS)

Miles, B.; Band, L. E.

2012-12-01

Water sustainability has been recognized as a fundamental problem of science whose solution relies in part on high-performance computing. Stormwater management is a major concern of urban sustainability. Understanding interactions between urban landcover and stormwater nutrient pollution requires consideration of fine-scale residential stormwater management, which in turn requires high-resolution LIDAR and landcover data not provided through national spatial data infrastructure, as well as field observation at the household scale. The objectives of my research are twofold: (1) advance understanding of the relationship between residential stormwater management practices and the export of nutrient pollution from stormwater in urbanized ecosystems; and (2) improve the informatics workflows used in community ecohydrology modeling as applied to heterogeneous urbanized ecosystems. In support of these objectives, I present preliminary results from initial work to: (1) develop an ecohydrology workflow platform that automates data preparation while maintaining data provenance and model metadata to yield reproducible workflows and support model benchmarking; (2) perform field observation of existing patterns of residential rooftop impervious surface connectivity to stormwater networks; and (3) develop Regional Hydro-Ecological Simulation System (RHESSys) models for watersheds in Baltimore, MD (as part of the Baltimore Ecosystem Study (BES) NSF Long-Term Ecological Research (LTER) site) and Durham, NC (as part of the NSF Urban Long-Term Research Area (ULTRA) program); these models will be used to simulate nitrogen loading resulting from both baseline residential rooftop impervious connectivity and for disconnection scenarios (e.g. roof drainage to lawn v. engineered rain garden, upslope v. riparian). This research builds on work done as part of the NSF EarthCube Layered Architecture Concept Award where a RHESSys workflow is being implemented in an iRODS (integrated Rule-Oriented Data System) environment. Modeling the ecohydrology of urban ecosystems in a reliable and reproducible manner requires a flexible scientific workflow platform that allows rapid prototyping with large-scale spatial datasets and model refinement integrating expert knowledge with local datasets and household surveys.

Data Integration Tool: From Permafrost Data Translation Research Tool to A Robust Research Application

NASA Astrophysics Data System (ADS)

Wilcox, H.; Schaefer, K. M.; Jafarov, E. E.; Strawhacker, C.; Pulsifer, P. L.; Thurmes, N.

2016-12-01

The United States National Science Foundation funded PermaData project led by the National Snow and Ice Data Center (NSIDC) with a team from the Global Terrestrial Network for Permafrost (GTN-P) aimed to improve permafrost data access and discovery. We developed a Data Integration Tool (DIT) to significantly speed up the time of manual processing needed to translate inconsistent, scattered historical permafrost data into files ready to ingest directly into the GTN-P. We leverage this data to support science research and policy decisions. DIT is a workflow manager that divides data preparation and analysis into a series of steps or operations called widgets. Each widget does a specific operation, such as read, multiply by a constant, sort, plot, and write data. DIT allows the user to select and order the widgets as desired to meet their specific needs. Originally it was written to capture a scientist's personal, iterative, data manipulation and quality control process of visually and programmatically iterating through inconsistent input data, examining it to find problems, adding operations to address the problems, and rerunning until the data could be translated into the GTN-P standard format. Iterative development of this tool led to a Fortran/Python hybrid then, with consideration of users, licensing, version control, packaging, and workflow, to a publically available, robust, usable application. Transitioning to Python allowed the use of open source frameworks for the workflow core and integration with a javascript graphical workflow interface. DIT is targeted to automatically handle 90% of the data processing for field scientists, modelers, and non-discipline scientists. It is available as an open source tool in GitHub packaged for a subset of Mac, Windows, and UNIX systems as a desktop application with a graphical workflow manager. DIT was used to completely translate one dataset (133 sites) that was successfully added to GTN-P, nearly translate three datasets (270 sites), and is scheduled to translate 10 more datasets ( 1000 sites) from the legacy inactive site data holdings of the Frozen Ground Data Center (FGDC). Iterative development has provided the permafrost and wider scientific community with an extendable tool designed specifically for the iterative process of translating unruly data.

Building a Culture of Continuous Improvement and Employee Engagement Using a Daily Management System Part 1: Overview.

PubMed

Maurer, Marsha; Canacari, Elena; Eng, Kimberly; Foley, Jane; Phelan, Cynthia; Sulmonte, Kimberlyann; Wandel, Jane

2018-03-01

A daily management system (DMS) can be used to implement continuous quality improvement and advance employee engagement. It can empower staff to identify problems in the care environment that impact quality or workflow and to address them on a daily basis. Through DMS, improvement becomes the work of everyone, every day. The authors of this 2-part series describe their work to develop a DMS. Part 1 describes the background and organizing framework of the program.

What Not To Do: Anti-patterns for Developing Scientific Workflow Software Components

NASA Astrophysics Data System (ADS)

Futrelle, J.; Maffei, A. R.; Sosik, H. M.; Gallager, S. M.; York, A.

2013-12-01

Scientific workflows promise to enable efficient scaling-up of researcher code to handle large datasets and workloads, as well as documentation of scientific processing via standardized provenance records, etc. Workflow systems and related frameworks for coordinating the execution of otherwise separate components are limited, however, in their ability to overcome software engineering design problems commonly encountered in pre-existing components, such as scripts developed externally by scientists in their laboratories. In practice, this often means that components must be rewritten or replaced in a time-consuming, expensive process. In the course of an extensive workflow development project involving large-scale oceanographic image processing, we have begun to identify and codify 'anti-patterns'--problematic design characteristics of software--that make components fit poorly into complex automated workflows. We have gone on to develop and document low-effort solutions and best practices that efficiently address the anti-patterns we have identified. The issues, solutions, and best practices can be used to evaluate and improve existing code, as well as guiding the development of new components. For example, we have identified a common anti-pattern we call 'batch-itis' in which a script fails and then cannot perform more work, even if that work is not precluded by the failure. The solution we have identified--removing unnecessary looping over independent units of work--is often easier to code than the anti-pattern, as it eliminates the need for complex control flow logic in the component. Other anti-patterns we have identified are similarly easy to identify and often easy to fix. We have drawn upon experience working with three science teams at Woods Hole Oceanographic Institution, each of which has designed novel imaging instruments and associated image analysis code. By developing use cases and prototypes within these teams, we have undertaken formal evaluations of software components developed by programmers with widely varying levels of expertise, and have been able to discover and characterize a number of anti-patterns. Our evaluation methodology and testbed have also enabled us to assess the efficacy of strategies to address these anti-patterns according to scientifically relevant metrics, such as ability of algorithms to perform faster than the rate of data acquisition and the accuracy of workflow component output relative to ground truth. The set of anti-patterns and solutions we have identified augments of the body of more well-known software engineering anti-patterns by addressing additional concerns that obtain when a software component has to function as part of a workflow assembled out of independently-developed codebases. Our experience shows that identifying and resolving these anti-patterns reduces development time and improves performance without reducing component reusability.

Scientist-Centered Workflow Abstractions via Generic Actors, Workflow Templates, and Context-Awareness for Groundwater Modeling and Analysis

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

Chin, George; Sivaramakrishnan, Chandrika; Critchlow, Terence J.

2011-07-04

A drawback of existing scientific workflow systems is the lack of support to domain scientists in designing and executing their own scientific workflows. Many domain scientists avoid developing and using workflows because the basic objects of workflows are too low-level and high-level tools and mechanisms to aid in workflow construction and use are largely unavailable. In our research, we are prototyping higher-level abstractions and tools to better support scientists in their workflow activities. Specifically, we are developing generic actors that provide abstract interfaces to specific functionality, workflow templates that encapsulate workflow and data patterns that can be reused and adaptedmore » by scientists, and context-awareness mechanisms to gather contextual information from the workflow environment on behalf of the scientist. To evaluate these scientist-centered abstractions on real problems, we apply them to construct and execute scientific workflows in the specific domain area of groundwater modeling and analysis.« less

DEWEY: the DICOM-enabled workflow engine system.

PubMed

Erickson, Bradley J; Langer, Steve G; Blezek, Daniel J; Ryan, William J; French, Todd L

2014-06-01

Workflow is a widely used term to describe the sequence of steps to accomplish a task. The use of workflow technology in medicine and medical imaging in particular is limited. In this article, we describe the application of a workflow engine to improve workflow in a radiology department. We implemented a DICOM-enabled workflow engine system in our department. We designed it in a way to allow for scalability, reliability, and flexibility. We implemented several workflows, including one that replaced an existing manual workflow and measured the number of examinations prepared in time without and with the workflow system. The system significantly increased the number of examinations prepared in time for clinical review compared to human effort. It also met the design goals defined at its outset. Workflow engines appear to have value as ways to efficiently assure that complex workflows are completed in a timely fashion.

Tavaxy: integrating Taverna and Galaxy workflows with cloud computing support.

PubMed

Abouelhoda, Mohamed; Issa, Shadi Alaa; Ghanem, Moustafa

2012-05-04

Over the past decade the workflow system paradigm has evolved as an efficient and user-friendly approach for developing complex bioinformatics applications. Two popular workflow systems that have gained acceptance by the bioinformatics community are Taverna and Galaxy. Each system has a large user-base and supports an ever-growing repository of application workflows. However, workflows developed for one system cannot be imported and executed easily on the other. The lack of interoperability is due to differences in the models of computation, workflow languages, and architectures of both systems. This lack of interoperability limits sharing of workflows between the user communities and leads to duplication of development efforts. In this paper, we present Tavaxy, a stand-alone system for creating and executing workflows based on using an extensible set of re-usable workflow patterns. Tavaxy offers a set of new features that simplify and enhance the development of sequence analysis applications: It allows the integration of existing Taverna and Galaxy workflows in a single environment, and supports the use of cloud computing capabilities. The integration of existing Taverna and Galaxy workflows is supported seamlessly at both run-time and design-time levels, based on the concepts of hierarchical workflows and workflow patterns. The use of cloud computing in Tavaxy is flexible, where the users can either instantiate the whole system on the cloud, or delegate the execution of certain sub-workflows to the cloud infrastructure. Tavaxy reduces the workflow development cycle by introducing the use of workflow patterns to simplify workflow creation. It enables the re-use and integration of existing (sub-) workflows from Taverna and Galaxy, and allows the creation of hybrid workflows. Its additional features exploit recent advances in high performance cloud computing to cope with the increasing data size and complexity of analysis.The system can be accessed either through a cloud-enabled web-interface or downloaded and installed to run within the user's local environment. All resources related to Tavaxy are available at http://www.tavaxy.org.

Implications of Metaphors in Defining Technical Communication.

ERIC Educational Resources Information Center

Beck, Charles E.

1991-01-01

Identifies four metaphors that appear dominant in current studies in the field of technical communication: transmitter, channel, balance, and bridge. Suggests limitations upon each of the metaphors. Discusses the alternative metaphors of lock, translator, transformer, synthesizer, conductor, and orchestrator. Proposes orchestration as a fruitful…

The complete digital workflow in fixed prosthodontics: a systematic review.

PubMed

Joda, Tim; Zarone, Fernando; Ferrari, Marco

2017-09-19

The continuous development in dental processing ensures new opportunities in the field of fixed prosthodontics in a complete virtual environment without any physical model situations. The aim was to compare fully digitalized workflows to conventional and/or mixed analog-digital workflows for the treatment with tooth-borne or implant-supported fixed reconstructions. A PICO strategy was executed using an electronic (MEDLINE, EMBASE, Google Scholar) plus manual search up to 2016-09-16 focusing on RCTs investigating complete digital workflows in fixed prosthodontics with regard to economics or esthetics or patient-centered outcomes with or without follow-up or survival/success rate analysis as well as complication assessment of at least 1 year under function. The search strategy was assembled from MeSH-Terms and unspecific free-text words: {(("Dental Prosthesis" [MeSH]) OR ("Crowns" [MeSH]) OR ("Dental Prosthesis, Implant-Supported" [MeSH])) OR ((crown) OR (fixed dental prosthesis) OR (fixed reconstruction) OR (dental bridge) OR (implant crown) OR (implant prosthesis) OR (implant restoration) OR (implant reconstruction))} AND {("Computer-Aided Design" [MeSH]) OR ((digital workflow) OR (digital technology) OR (computerized dentistry) OR (intraoral scan) OR (digital impression) OR (scanbody) OR (virtual design) OR (digital design) OR (cad/cam) OR (rapid prototyping) OR (monolithic) OR (full-contour))} AND {("Dental Technology" [MeSH) OR ((conventional workflow) OR (lost-wax-technique) OR (porcelain-fused-to-metal) OR (PFM) OR (implant impression) OR (hand-layering) OR (veneering) OR (framework))} AND {(("Study, Feasibility" [MeSH]) OR ("Survival" [MeSH]) OR ("Success" [MeSH]) OR ("Economics" [MeSH]) OR ("Costs, Cost Analysis" [MeSH]) OR ("Esthetics, Dental" [MeSH]) OR ("Patient Satisfaction" [MeSH])) OR ((feasibility) OR (efficiency) OR (patient-centered outcome))}. Assessment of risk of bias in selected studies was done at a 'trial level' including random sequence generation, allocation concealment, blinding, completeness of outcome data, selective reporting, and other bias using the Cochrane Collaboration tool. A judgment of risk of bias was assigned if one or more key domains had a high or unclear risk of bias. An official registration of the systematic review was not performed. The systematic search identified 67 titles, 32 abstracts thereof were screened, and subsequently, three full-texts included for data extraction. Analysed RCTs were heterogeneous without follow-up. One study demonstrated that fully digitally produced dental crowns revealed the feasibility of the process itself; however, the marginal precision was lower for lithium disilicate (LS2) restorations (113.8 μm) compared to conventional metal-ceramic (92.4 μm) and zirconium dioxide (ZrO2) crowns (68.5 μm) (p < 0.05). Another study showed that leucite-reinforced glass ceramic crowns were esthetically favoured by the patients (8/2 crowns) and clinicians (7/3 crowns) (p < 0.05). The third study investigated implant crowns. The complete digital workflow was more than twofold faster (75.3 min) in comparison to the mixed analog-digital workflow (156.6 min) (p < 0.05). No RCTs could be found investigating multi-unit fixed dental prostheses (FDP). The number of RCTs testing complete digital workflows in fixed prosthodontics is low. Scientifically proven recommendations for clinical routine cannot be given at this time. Research with high-quality trials seems to be slower than the industrial progress of available digital applications. Future research with well-designed RCTs including follow-up observation is compellingly necessary in the field of complete digital processing.

Workflow management systems in radiology

NASA Astrophysics Data System (ADS)

Wendler, Thomas; Meetz, Kirsten; Schmidt, Joachim

1998-07-01

In a situation of shrinking health care budgets, increasing cost pressure and growing demands to increase the efficiency and the quality of medical services, health care enterprises are forced to optimize or complete re-design their processes. Although information technology is agreed to potentially contribute to cost reduction and efficiency improvement, the real success factors are the re-definition and automation of processes: Business Process Re-engineering and Workflow Management. In this paper we discuss architectures for the use of workflow management systems in radiology. We propose to move forward from information systems in radiology (RIS, PACS) to Radiology Management Systems, in which workflow functionality (process definitions and process automation) is implemented through autonomous workflow management systems (WfMS). In a workflow oriented architecture, an autonomous workflow enactment service communicates with workflow client applications via standardized interfaces. In this paper, we discuss the need for and the benefits of such an approach. The separation of workflow management system and application systems is emphasized, and the consequences that arise for the architecture of workflow oriented information systems. This includes an appropriate workflow terminology, and the definition of standard interfaces for workflow aware application systems. Workflow studies in various institutions have shown that most of the processes in radiology are well structured and suited for a workflow management approach. Numerous commercially available Workflow Management Systems (WfMS) were investigated, and some of them, which are process- oriented and application independent, appear suitable for use in radiology.

Bioinformatics workflows and web services in systems biology made easy for experimentalists.

PubMed

Jimenez, Rafael C; Corpas, Manuel

2013-01-01

Workflows are useful to perform data analysis and integration in systems biology. Workflow management systems can help users create workflows without any previous knowledge in programming and web services. However the computational skills required to build such workflows are usually above the level most biological experimentalists are comfortable with. In this chapter we introduce workflow management systems that reuse existing workflows instead of creating them, making it easier for experimentalists to perform computational tasks.

WWWinda Orchestrator: a mechanism for coordinating distributed flocks of Java Applets

NASA Astrophysics Data System (ADS)

Gutfreund, Yechezkal-Shimon; Nicol, John R.

1997-01-01

The WWWinda Orchestrator is a simple but powerful tool for coordinating distributed Java applets. Loosely derived from the Linda programming language developed by David Gelernter and Nicholas Carriero of Yale, WWWinda implements a distributed shared object space called TupleSpace where applets can post, read, or permanently store arbitrary Java objects. In this manner, applets can easily share information without being aware of the underlying communication mechanisms. WWWinda is a very useful for orchestrating flocks of distributed Java applets. Coordination event scan be posted to WWWinda TupleSpace and used to orchestrate the actions of remote applets. Applets can easily share information via the TupleSpace. The technology combines several functions in one simple metaphor: distributed web objects, remote messaging between applets, distributed synchronization mechanisms, object- oriented database, and a distributed event signaling mechanisms. WWWinda can be used a s platform for implementing shared VRML environments, shared groupware environments, controlling remote devices such as cameras, distributed Karaoke, distributed gaming, and shared audio and video experiences.

DDA3 associates with microtubule plus ends and orchestrates microtubule dynamics and directional cell migration

PubMed Central

Zhang, Liangyu; Shao, Hengyi; Zhu, Tongge; Xia, Peng; Wang, Zhikai; Liu, Lifang; Yan, Maomao; Hill, Donald L.; Fang, Guowei; Chen, Zhengjun; Wang, Dongmei; Yao, Xuebiao

2013-01-01

Cell motility and adhesion involve orchestrated interaction of microtubules (MTs) with their plus-end tracking proteins (+TIPs). However, the mechanisms underlying regulations of MT dynamics and directional cell migration are still elusive. Here, we show that DDA3-EB1 interaction orchestrates MT plus-end dynamics and facilitates directional cell migration. Biochemical characterizations reveal that DDA3 interacts with EB1 via its SxIP motif within the C-terminal Pro/Ser-rich region. Time-lapse and total internal reflection fluorescence (TIRF) microscopic assays demonstrate that DDA3 exhibits EB1-dependent, MT plus-end loading and tracking. The EB1-based loading of DDA3 is responsible for MT plus-ends stabilization at the cell cortex, which in turn orchestrates directional cell migration. Interestingly, the DDA3-EB1 interaction is potentially regulated by EB1 acetylation, which may account for physiological regulation underlying EGF-elicited cell migration. Thus, the EB1-based function of DDA3 links MT dynamics to directional cell migration. PMID:23652583

Tavaxy: Integrating Taverna and Galaxy workflows with cloud computing support

PubMed Central

2012-01-01

Background Over the past decade the workflow system paradigm has evolved as an efficient and user-friendly approach for developing complex bioinformatics applications. Two popular workflow systems that have gained acceptance by the bioinformatics community are Taverna and Galaxy. Each system has a large user-base and supports an ever-growing repository of application workflows. However, workflows developed for one system cannot be imported and executed easily on the other. The lack of interoperability is due to differences in the models of computation, workflow languages, and architectures of both systems. This lack of interoperability limits sharing of workflows between the user communities and leads to duplication of development efforts. Results In this paper, we present Tavaxy, a stand-alone system for creating and executing workflows based on using an extensible set of re-usable workflow patterns. Tavaxy offers a set of new features that simplify and enhance the development of sequence analysis applications: It allows the integration of existing Taverna and Galaxy workflows in a single environment, and supports the use of cloud computing capabilities. The integration of existing Taverna and Galaxy workflows is supported seamlessly at both run-time and design-time levels, based on the concepts of hierarchical workflows and workflow patterns. The use of cloud computing in Tavaxy is flexible, where the users can either instantiate the whole system on the cloud, or delegate the execution of certain sub-workflows to the cloud infrastructure. Conclusions Tavaxy reduces the workflow development cycle by introducing the use of workflow patterns to simplify workflow creation. It enables the re-use and integration of existing (sub-) workflows from Taverna and Galaxy, and allows the creation of hybrid workflows. Its additional features exploit recent advances in high performance cloud computing to cope with the increasing data size and complexity of analysis. The system can be accessed either through a cloud-enabled web-interface or downloaded and installed to run within the user's local environment. All resources related to Tavaxy are available at http://www.tavaxy.org. PMID:22559942

Intelligent earthquake data processing for global adjoint tomography

NASA Astrophysics Data System (ADS)

Chen, Y.; Hill, J.; Li, T.; Lei, W.; Ruan, Y.; Lefebvre, M. P.; Tromp, J.

2016-12-01

Due to the increased computational capability afforded by modern and future computing architectures, the seismology community is demanding a more comprehensive understanding of the full waveform information from the recorded earthquake seismograms. Global waveform tomography is a complex workflow that matches observed seismic data with synthesized seismograms by iteratively updating the earth model parameters based on the adjoint state method. This methodology allows us to compute a very accurate model of the earth's interior. The synthetic data is simulated by solving the wave equation in the entire globe using a spectral-element method. In order to ensure the inversion accuracy and stability, both the synthesized and observed seismograms must be carefully pre-processed. Because the scale of the inversion problem is extremely large and there is a very large volume of data to both be read and written, an efficient and reliable pre-processing workflow must be developed. We are investigating intelligent algorithms based on a machine-learning (ML) framework that will automatically tune parameters for the data processing chain. One straightforward application of ML in data processing is to classify all possible misfit calculation windows into usable and unusable ones, based on some intelligent ML models such as neural network, support vector machine or principle component analysis. The intelligent earthquake data processing framework will enable the seismology community to compute the global waveform tomography using seismic data from an arbitrarily large number of earthquake events in the fastest, most efficient way.

A collaborative framework for contributing DICOM RT PHI (Protected Health Information) to augment data mining in clinical decision support

NASA Astrophysics Data System (ADS)

Deshpande, Ruchi; Thuptimdang, Wanwara; DeMarco, John; Liu, Brent J.

2014-03-01

We have built a decision support system that provides recommendations for customizing radiation therapy treatment plans, based on patient models generated from a database of retrospective planning data. This database consists of relevant metadata and information derived from the following DICOM objects - CT images, RT Structure Set, RT Dose and RT Plan. The usefulness and accuracy of such patient models partly depends on the sample size of the learning data set. Our current goal is to increase this sample size by expanding our decision support system into a collaborative framework to include contributions from multiple collaborators. Potential collaborators are often reluctant to upload even anonymized patient files to repositories outside their local organizational network in order to avoid any conflicts with HIPAA Privacy and Security Rules. We have circumvented this problem by developing a tool that can parse DICOM files on the client's side and extract de-identified numeric and text data from DICOM RT headers for uploading to a centralized system. As a result, the DICOM files containing PHI remain local to the client side. This is a novel workflow that results in adding only relevant yet valuable data from DICOM files to the centralized decision support knowledge base in such a way that the DICOM files never leave the contributor's local workstation in a cloud-based environment. Such a workflow serves to encourage clinicians to contribute data for research endeavors by ensuring protection of electronic patient data.

Combining the AFLOW GIBBS and elastic libraries to efficiently and robustly screen thermomechanical properties of solids

NASA Astrophysics Data System (ADS)

Toher, Cormac; Oses, Corey; Plata, Jose J.; Hicks, David; Rose, Frisco; Levy, Ohad; de Jong, Maarten; Asta, Mark; Fornari, Marco; Buongiorno Nardelli, Marco; Curtarolo, Stefano

2017-06-01

Thorough characterization of the thermomechanical properties of materials requires difficult and time-consuming experiments. This severely limits the availability of data and is one of the main obstacles for the development of effective accelerated materials design strategies. The rapid screening of new potential materials requires highly integrated, sophisticated, and robust computational approaches. We tackled the challenge by developing an automated, integrated workflow with robust error-correction within the AFLOW framework which combines the newly developed "Automatic Elasticity Library" with the previously implemented GIBBS method. The first extracts the mechanical properties from automatic self-consistent stress-strain calculations, while the latter employs those mechanical properties to evaluate the thermodynamics within the Debye model. This new thermoelastic workflow is benchmarked against a set of 74 experimentally characterized systems to pinpoint a robust computational methodology for the evaluation of bulk and shear moduli, Poisson ratios, Debye temperatures, Grüneisen parameters, and thermal conductivities of a wide variety of materials. The effect of different choices of equations of state and exchange-correlation functionals is examined and the optimum combination of properties for the Leibfried-Schlömann prediction of thermal conductivity is identified, leading to improved agreement with experimental results than the GIBBS-only approach. The framework has been applied to the AFLOW.org data repositories to compute the thermoelastic properties of over 3500 unique materials. The results are now available online by using an expanded version of the REST-API described in the Appendix.

Toward a Proof of Concept Cloud Framework for Physics Applications on Blue Gene Supercomputers

NASA Astrophysics Data System (ADS)

Dreher, Patrick; Scullin, William; Vouk, Mladen

2015-09-01

Traditional high performance supercomputers are capable of delivering large sustained state-of-the-art computational resources to physics applications over extended periods of time using batch processing mode operating environments. However, today there is an increasing demand for more complex workflows that involve large fluctuations in the levels of HPC physics computational requirements during the simulations. Some of the workflow components may also require a richer set of operating system features and schedulers than normally found in a batch oriented HPC environment. This paper reports on progress toward a proof of concept design that implements a cloud framework onto BG/P and BG/Q platforms at the Argonne Leadership Computing Facility. The BG/P implementation utilizes the Kittyhawk utility and the BG/Q platform uses an experimental heterogeneous FusedOS operating system environment. Both platforms use the Virtual Computing Laboratory as the cloud computing system embedded within the supercomputer. This proof of concept design allows a cloud to be configured so that it can capitalize on the specialized infrastructure capabilities of a supercomputer and the flexible cloud configurations without resorting to virtualization. Initial testing of the proof of concept system is done using the lattice QCD MILC code. These types of user reconfigurable environments have the potential to deliver experimental schedulers and operating systems within a working HPC environment for physics computations that may be different from the native OS and schedulers on production HPC supercomputers.

TAMU: Blueprint for A New Space Mission Operations System Paradigm

NASA Technical Reports Server (NTRS)

Ruszkowski, James T.; Meshkat, Leila; Haensly, Jean; Pennington, Al; Hogle, Charles

2011-01-01

The Transferable, Adaptable, Modular and Upgradeable (TAMU) Flight Production Process (FPP) is a System of System (SOS) framework which cuts across multiple organizations and their associated facilities, that are, in the most general case, in geographically disperse locations, to develop the architecture and associated workflow processes of products for a broad range of flight projects. Further, TAMU FPP provides for the automatic execution and re-planning of the workflow processes as they become operational. This paper provides the blueprint for the TAMU FPP paradigm. This blueprint presents a complete, coherent technique, process and tool set that results in an infrastructure that can be used for full lifecycle design and decision making during the flight production process. Based on the many years of experience with the Space Shuttle Program (SSP) and the International Space Station (ISS), the currently cancelled Constellation Program which aimed on returning humans to the moon as a starting point, has been building a modern model-based Systems Engineering infrastructure to Re-engineer the FPP. This infrastructure uses a structured modeling and architecture development approach to optimize the system design thereby reducing the sustaining costs and increasing system efficiency, reliability, robustness and maintainability metrics. With the advent of the new vision for human space exploration, it is now necessary to further generalize this framework to take into consideration a broad range of missions and the participation of multiple organizations outside of the MOD; hence the Transferable, Adaptable, Modular and Upgradeable (TAMU) concept.

Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

PubMed Central

Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.

2014-01-01

Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891

Using CAD/CAM technology to create a 10-unit zirconia fixed partial denture--a UTHSCSA dental school case report.

PubMed

Zimmermann, Richard; Seitz, Stefanie; Magness, Brent; Wieck, Blaine

2013-10-01

From diagnosis and treatment planning to the materials being used, technology is changing dentistry. New materials are providing dentists greater options for treatment, while technology is streamlining the workflow in the office and dental laboratory. Traditionally the creation of a long-span fixed partial denture was a labor intense project--from waxing up the prosthesis--to stacking of the porecelain. For larger frameworks, it was recommended for the dentist to bring in the patient in for a framework try-in. However, advances in both CAD/CAM technology and dental materials are revolutionizing the way dentistry is being done. The following describes the fabrication of a 10-unit full contour zirconia fixed partial denture completed in the pre-doctorate program at UTHSCSA Dental School.

Evolving Frameworks for Different Communities of Scientists and End Users

NASA Astrophysics Data System (ADS)

Graves, S. J.; Keiser, K.

2016-12-01

Two evolving frameworks for interdisciplinary science will be described in the context of the Common Data Framework for Earth-Observation Data and the importance of standards and protocols. The Event Data Driven Delivery (ED3) Framework, funded by NASA Applied Sciences, provides the delivery of data based on predetermined subscriptions and associated workflows to various communities of end users. ED3's capabilities are used by scientists, as well as policy and resource managers, when event alerts are triggered to respond to their needs. The EarthCube Integration and Testing Environment (ECITE) Assessment Framework for Technology Interoperability and Integration is being developed to facilitate the EarthCube community's assessment of NSF funded technologies addressing Earth science problems. ECITE is addressing the translation of geoscience researchers' use cases into technology use case that apply EarthCube-funded building block technologies (and other existing technologies) for solving science problems. EarthCube criteria for technology assessment include the use of data, metadata and service standards to improve interoperability and integration across program components. The long-range benefit will be the growth of a cyberinfrastructure with technology components that have been shown to work together to solve known science objectives.

SECIMTools: a suite of metabolomics data analysis tools.

PubMed

Kirpich, Alexander S; Ibarra, Miguel; Moskalenko, Oleksandr; Fear, Justin M; Gerken, Joseph; Mi, Xinlei; Ashrafi, Ali; Morse, Alison M; McIntyre, Lauren M

2018-04-20

Metabolomics has the promise to transform the area of personalized medicine with the rapid development of high throughput technology for untargeted analysis of metabolites. Open access, easy to use, analytic tools that are broadly accessible to the biological community need to be developed. While technology used in metabolomics varies, most metabolomics studies have a set of features identified. Galaxy is an open access platform that enables scientists at all levels to interact with big data. Galaxy promotes reproducibility by saving histories and enabling the sharing workflows among scientists. SECIMTools (SouthEast Center for Integrated Metabolomics) is a set of Python applications that are available both as standalone tools and wrapped for use in Galaxy. The suite includes a comprehensive set of quality control metrics (retention time window evaluation and various peak evaluation tools), visualization techniques (hierarchical cluster heatmap, principal component analysis, modular modularity clustering), basic statistical analysis methods (partial least squares - discriminant analysis, analysis of variance, t-test, Kruskal-Wallis non-parametric test), advanced classification methods (random forest, support vector machines), and advanced variable selection tools (least absolute shrinkage and selection operator LASSO and Elastic Net). SECIMTools leverages the Galaxy platform and enables integrated workflows for metabolomics data analysis made from building blocks designed for easy use and interpretability. Standard data formats and a set of utilities allow arbitrary linkages between tools to encourage novel workflow designs. The Galaxy framework enables future data integration for metabolomics studies with other omics data.

MALDI-TOF-MS with PLS Modeling Enables Strain Typing of the Bacterial Plant Pathogen Xanthomonas axonopodis

NASA Astrophysics Data System (ADS)

Sindt, Nathan M.; Robison, Faith; Brick, Mark A.; Schwartz, Howard F.; Heuberger, Adam L.; Prenni, Jessica E.

2018-02-01

Matrix-assisted desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) is a fast and effective tool for microbial species identification. However, current approaches are limited to species-level identification even when genetic differences are known. Here, we present a novel workflow that applies the statistical method of partial least squares discriminant analysis (PLS-DA) to MALDI-TOF-MS protein fingerprint data of Xanthomonas axonopodis, an important bacterial plant pathogen of fruit and vegetable crops. Mass spectra of 32 X. axonopodis strains were used to create a mass spectral library and PLS-DA was employed to model the closely related strains. A robust workflow was designed to optimize the PLS-DA model by assessing the model performance over a range of signal-to-noise ratios (s/n) and mass filter (MF) thresholds. The optimized parameters were observed to be s/n = 3 and MF = 0.7. The model correctly classified 83% of spectra withheld from the model as a test set. A new decision rule was developed, termed the rolled-up Maximum Decision Rule (ruMDR), and this method improved identification rates to 92%. These results demonstrate that MALDI-TOF-MS protein fingerprints of bacterial isolates can be utilized to enable identification at the strain level. Furthermore, the open-source framework of this workflow allows for broad implementation across various instrument platforms as well as integration with alternative modeling and classification algorithms.

Virtual Sensors in a Web 2.0 Digital Watershed

NASA Astrophysics Data System (ADS)

Liu, Y.; Hill, D. J.; Marini, L.; Kooper, R.; Rodriguez, A.; Myers, J. D.

2008-12-01

The lack of rainfall data in many watersheds is one of the major barriers for modeling and studying many environmental and hydrological processes and supporting decision making. There are just not enough rain gages on the ground. To overcome this data scarcity issue, a Web 2.0 digital watershed is developed at NCSA(National Center for Supercomputing Applications), where users can point-and-click on a web-based google map interface and create new precipitation virtual sensors at any location within the same coverage region as a NEXRAD station. A set of scientific workflows are implemented to perform spatial, temporal and thematic transformations to the near-real-time NEXRAD Level II data. Such workflows can be triggered by the users' actions and generate either rainfall rate or rainfall accumulation streaming data at a user-specified time interval. We will discuss some underlying components of this digital watershed, which consists of a semantic content management middleware, a semantically enhanced streaming data toolkit, virtual sensor management functionality, and RESTful (REpresentational State Transfer) web service that can trigger the workflow execution. Such loosely coupled architecture presents a generic framework for constructing a Web 2.0 style digital watershed. An implementation of this architecture at the Upper Illinois Rive Basin will be presented. We will also discuss the implications of the virtual sensor concept for the broad environmental observatory community and how such concept will help us move towards a participatory digital watershed.

Bridging the guideline implementation gap: a systematic, document-centered approach to guideline implementation.

PubMed

Shiffman, Richard N; Michel, George; Essaihi, Abdelwaheb; Thornquist, Elizabeth

2004-01-01

A gap exists between the information contained in published clinical practice guidelines and the knowledge and information that are necessary to implement them. This work describes a process to systematize and make explicit the translation of document-based knowledge into workflow-integrated clinical decision support systems. This approach uses the Guideline Elements Model (GEM) to represent the guideline knowledge. Implementation requires a number of steps to translate the knowledge contained in guideline text into a computable format and to integrate the information into clinical workflow. The steps include: (1) selection of a guideline and specific recommendations for implementation, (2) markup of the guideline text, (3) atomization, (4) deabstraction and (5) disambiguation of recommendation concepts, (6) verification of rule set completeness, (7) addition of explanations, (8) building executable statements, (9) specification of origins of decision variables and insertions of recommended actions, (10) definition of action types and selection of associated beneficial services, (11) choice of interface components, and (12) creation of requirement specification. The authors illustrate these component processes using examples drawn from recent experience translating recommendations from the National Heart, Lung, and Blood Institute's guideline on management of chronic asthma into a workflow-integrated decision support system that operates within the Logician electronic health record system. Using the guideline document as a knowledge source promotes authentic translation of domain knowledge and reduces the overall complexity of the implementation task. From this framework, we believe that a better understanding of activities involved in guideline implementation will emerge.

Clinical data miner: an electronic case report form system with integrated data preprocessing and machine-learning libraries supporting clinical diagnostic model research.

PubMed

Installé, Arnaud Jf; Van den Bosch, Thierry; De Moor, Bart; Timmerman, Dirk

2014-10-20

Using machine-learning techniques, clinical diagnostic model research extracts diagnostic models from patient data. Traditionally, patient data are often collected using electronic Case Report Form (eCRF) systems, while mathematical software is used for analyzing these data using machine-learning techniques. Due to the lack of integration between eCRF systems and mathematical software, extracting diagnostic models is a complex, error-prone process. Moreover, due to the complexity of this process, it is usually only performed once, after a predetermined number of data points have been collected, without insight into the predictive performance of the resulting models. The objective of the study of Clinical Data Miner (CDM) software framework is to offer an eCRF system with integrated data preprocessing and machine-learning libraries, improving efficiency of the clinical diagnostic model research workflow, and to enable optimization of patient inclusion numbers through study performance monitoring. The CDM software framework was developed using a test-driven development (TDD) approach, to ensure high software quality. Architecturally, CDM's design is split over a number of modules, to ensure future extendability. The TDD approach has enabled us to deliver high software quality. CDM's eCRF Web interface is in active use by the studies of the International Endometrial Tumor Analysis consortium, with over 4000 enrolled patients, and more studies planned. Additionally, a derived user interface has been used in six separate interrater agreement studies. CDM's integrated data preprocessing and machine-learning libraries simplify some otherwise manual and error-prone steps in the clinical diagnostic model research workflow. Furthermore, CDM's libraries provide study coordinators with a method to monitor a study's predictive performance as patient inclusions increase. To our knowledge, CDM is the only eCRF system integrating data preprocessing and machine-learning libraries. This integration improves the efficiency of the clinical diagnostic model research workflow. Moreover, by simplifying the generation of learning curves, CDM enables study coordinators to assess more accurately when data collection can be terminated, resulting in better models or lower patient recruitment costs.

The Surface Ocean CO2 Atlas: Stewarding Underway Carbon Data from Collection to Archival

NASA Astrophysics Data System (ADS)

O'Brien, K.; Smith, K. M.; Pfeil, B.; Landa, C.; Bakker, D. C. E.; Olsen, A.; Jones, S.; Shrestha, B.; Kozyr, A.; Manke, A. B.; Schweitzer, R.; Burger, E. F.

2016-02-01

The Surface Ocean CO2 Atlas (SOCAT, www.socat.info) is a quality controlled, global surface ocean carbon dioxide (CO2) data set gathered on research vessels, SOOP and buoys. To the degree feasible SOCAT is comprehensive; it draws together and applies uniform QC procedures to all such observations made across the international community. The first version of SOCAT (version 1.5) was publicly released September 2011(Bakker et al., 2011) with 6.3 million observations. This was followed by the release of SOCAT version 2, expanded to over 10 million observations, in June 2013 (Bakker et al., 2013). Most recently, in September 2015 SOCAT version 3 was released containing over 14 millions observations spanning almost 60 years! The process of assembling, QC'ing and publishing V1.5 and V2 of SOCAT required an unsustainable level of manual effort. To ease the burden on data managers and data providers, the SOCAT community agreed to embark an automated data ingestion process which would create a streamlined workflow to improve data stewardship from ingestion to quality control and from publishing to archival. To that end, for version 3 and beyond, the SOCAT automation team created a framework which was based upon standards and conventions, yet at the same time allows scientists to work in the data formats they felt most comfortable with (ie, csv files). This automated workflow provides several advantages: 1) data ingestion into uniform and standards-based file formats; 2) ease of data integration into standard quality control system; 3) data ingestion and quality control can be performed in parallel; 4) provides uniform method of archiving carbon data and generation of digital object identifiers (DOI).In this presentation, we will discuss and demonstrate the SOCAT data ingestion dashboard and the quality control system. We will also discuss the standards, conventions, and tools that were leveraged to create a workflow that allows scientists to work in their own formats, yet provides a framework for creating high quality data products on an annual basis, while meeting or exceeding data requirements for access, documentation and archival.

Long-Term Teacher Orchestration of Technology-Mediated Collaborative Inquiry

ERIC Educational Resources Information Center

Viilo, Marjut; Seitamaa-Hakkarainen, Pirita; Hakkarainen, Kai

2018-01-01

This explorative case study longitudinally examines teacher orchestration of an inquiry learning process in a technology-enhanced elementary classroom. A 13-month investigative study on cultural artifacts was conducted on 32 fourth grade students who progressed to the fifth grade during the project. The activities were mediated and documented…

Secure NFV Orchestration Over an SDN-Controlled Optical Network With Time-Shared Quantum Key Distribution Resources

NASA Astrophysics Data System (ADS)

Aguado, Alejandro; Hugues-Salas, Emilio; Haigh, Paul Anthony; Marhuenda, Jaume; Price, Alasdair B.; Sibson, Philip; Kennard, Jake E.; Erven, Chris; Rarity, John G.; Thompson, Mark Gerard; Lord, Andrew; Nejabati, Reza; Simeonidou, Dimitra

2017-04-01

We demonstrate, for the first time, a secure optical network architecture that combines NFV orchestration and SDN control with quantum key distribution (QKD) technology. A novel time-shared QKD network design is presented as a cost-effective solution for practical networks.

Incorporating Wind Excerpts in the School Band Curriculum

ERIC Educational Resources Information Center

Bruns, Robert

2010-01-01

Professional musicians and college students commonly study orchestral excerpts, but a similar practice has yet to be implemented in the band field. Due to their widespread use in orchestral auditions, excerpts have been incorporated as a tool for musical development. Many college professors regularly assign excerpt study as part of their…

Orchestration of Social Modes in E-Learning

ERIC Educational Resources Information Center

Weinberger, Armin; Papadopoulos, Pantelis M.

2016-01-01

The concept of orchestration has recently emerged as a useful metaphor in technology-enhanced learning research communities, because of its explanatory power and appeal in describing how different learning activities, tools, and arrangements could be combined to promote learning. More than a buffet of tools offering possibilities to the teachers,…

Webbing and Orchestration. Two Interrelated Views on Digital Tools in Mathematics Education

ERIC Educational Resources Information Center

Trouche, Luc; Drijvers, Paul

2014-01-01

The integration of digital tools in mathematics education is considered both promising and problematic. To deal with this issue, notions of "webbing" and "instrumental orchestration" are developed. However, the two seemed to be disconnected, and having different cultural and theoretical roots. In this article, we investigate…

The Principal as Orchestral Conductor.

ERIC Educational Resources Information Center

Luce, David R.

1992-01-01

A new way of viewing the principal is to think of the principal as an orchestral conductor. Insights gained from this perspective may help in progressing toward more healthy and productive school organizations. Both the conductor and the principal are highly visible by virtue of their positions and function as intermediaries in their respective…

Roles of Teachers in Orchestrating Learning in Elementary Science Classrooms

ERIC Educational Resources Information Center

Zhai, Junqing; Tan, Aik-Ling

2015-01-01

This study delves into the different roles that elementary science teachers play in the classroom to orchestrate science learning opportunities for students. Examining the classroom practices of three elementary science teachers in Singapore, we found that teachers shuttle between four key roles in enabling student learning in science. Teachers…

Developing a Cloud-Based Online Geospatial Information Sharing and Geoprocessing Platform to Facilitate Collaborative Education and Research

NASA Astrophysics Data System (ADS)

Yang, Z. L.; Cao, J.; Hu, K.; Gui, Z. P.; Wu, H. Y.; You, L.

2016-06-01

Efficient online discovering and applying geospatial information resources (GIRs) is critical in Earth Science domain as while for cross-disciplinary applications. However, to achieve it is challenging due to the heterogeneity, complexity and privacy of online GIRs. In this article, GeoSquare, a collaborative online geospatial information sharing and geoprocessing platform, was developed to tackle this problem. Specifically, (1) GIRs registration and multi-view query functions allow users to publish and discover GIRs more effectively. (2) Online geoprocessing and real-time execution status checking help users process data and conduct analysis without pre-installation of cumbersome professional tools on their own machines. (3) A service chain orchestration function enables domain experts to contribute and share their domain knowledge with community members through workflow modeling. (4) User inventory management allows registered users to collect and manage their own GIRs, monitor their execution status, and track their own geoprocessing histories. Besides, to enhance the flexibility and capacity of GeoSquare, distributed storage and cloud computing technologies are employed. To support interactive teaching and training, GeoSquare adopts the rich internet application (RIA) technology to create user-friendly graphical user interface (GUI). Results show that GeoSquare can integrate and foster collaboration between dispersed GIRs, computing resources and people. Subsequently, educators and researchers can share and exchange resources in an efficient and harmonious way.

Successful Completion of FY18/Q1 ASC L2 Milestone 6355: Electrical Analysis Calibration Workflow Capability Demonstration.

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

Copps, Kevin D.

The Sandia Analysis Workbench (SAW) project has developed and deployed a production capability for SIERRA computational mechanics analysis workflows. However, the electrical analysis workflow capability requirements have only been demonstrated in early prototype states, with no real capability deployed for analysts’ use. This milestone aims to improve the electrical analysis workflow capability (via SAW and related tools) and deploy it for ongoing use. We propose to focus on a QASPR electrical analysis calibration workflow use case. We will include a number of new capabilities (versus today’s SAW), such as: 1) support for the XYCE code workflow component, 2) data managementmore » coupled to electrical workflow, 3) human-in-theloop workflow capability, and 4) electrical analysis workflow capability deployed on the restricted (and possibly classified) network at Sandia. While far from the complete set of capabilities required for electrical analysis workflow over the long term, this is a substantial first step toward full production support for the electrical analysts.« less

Developing integrated workflows for the digitisation of herbarium specimens using a modular and scalable approach.

PubMed

Haston, Elspeth; Cubey, Robert; Pullan, Martin; Atkins, Hannah; Harris, David J

2012-01-01

Digitisation programmes in many institutes frequently involve disparate and irregular funding, diverse selection criteria and scope, with different members of staff managing and operating the processes. These factors have influenced the decision at the Royal Botanic Garden Edinburgh to develop an integrated workflow for the digitisation of herbarium specimens which is modular and scalable to enable a single overall workflow to be used for all digitisation projects. This integrated workflow is comprised of three principal elements: a specimen workflow, a data workflow and an image workflow.The specimen workflow is strongly linked to curatorial processes which will impact on the prioritisation, selection and preparation of the specimens. The importance of including a conservation element within the digitisation workflow is highlighted. The data workflow includes the concept of three main categories of collection data: label data, curatorial data and supplementary data. It is shown that each category of data has its own properties which influence the timing of data capture within the workflow. Development of software has been carried out for the rapid capture of curatorial data, and optical character recognition (OCR) software is being used to increase the efficiency of capturing label data and supplementary data. The large number and size of the images has necessitated the inclusion of automated systems within the image workflow.

Dawn: A Simulation Model for Evaluating Costs and Tradeoffs of Big Data Science Architectures

NASA Astrophysics Data System (ADS)

Cinquini, L.; Crichton, D. J.; Braverman, A. J.; Kyo, L.; Fuchs, T.; Turmon, M.

2014-12-01

In many scientific disciplines, scientists and data managers are bracing for an upcoming deluge of big data volumes, which will increase the size of current data archives by a factor of 10-100 times. For example, the next Climate Model Inter-comparison Project (CMIP6) will generate a global archive of model output of approximately 10-20 Peta-bytes, while the upcoming next generation of NASA decadal Earth Observing instruments are expected to collect tens of Giga-bytes/day. In radio-astronomy, the Square Kilometre Array (SKA) will collect data in the Exa-bytes/day range, of which (after reduction and processing) around 1.5 Exa-bytes/year will be stored. The effective and timely processing of these enormous data streams will require the design of new data reduction and processing algorithms, new system architectures, and new techniques for evaluating computation uncertainty. Yet at present no general software tool or framework exists that will allow system architects to model their expected data processing workflow, and determine the network, computational and storage resources needed to prepare their data for scientific analysis. In order to fill this gap, at NASA/JPL we have been developing a preliminary model named DAWN (Distributed Analytics, Workflows and Numerics) for simulating arbitrary complex workflows composed of any number of data processing and movement tasks. The model can be configured with a representation of the problem at hand (the data volumes, the processing algorithms, the available computing and network resources), and is able to evaluate tradeoffs between different possible workflows based on several estimators: overall elapsed time, separate computation and transfer times, resulting uncertainty, and others. So far, we have been applying DAWN to analyze architectural solutions for 4 different use cases from distinct science disciplines: climate science, astronomy, hydrology and a generic cloud computing use case. This talk will present preliminary results and discuss how DAWN can be evolved into a powerful tool for designing system architectures for data intensive science.

Shiny FHIR: An Integrated Framework Leveraging Shiny R and HL7 FHIR to Empower Standards-Based Clinical Data Applications.

PubMed

Hong, Na; Prodduturi, Naresh; Wang, Chen; Jiang, Guoqian

2017-01-01

In this study, we describe our efforts in building a clinical statistics and analysis application platform using an emerging clinical data standard, HL7 FHIR, and an open source web application framework, Shiny. We designed two primary workflows that integrate a series of R packages to enable both patient-centered and cohort-based interactive analyses. We leveraged Shiny with R to develop interactive interfaces on FHIR-based data and used ovarian cancer study datasets as a use case to implement a prototype. Specifically, we implemented patient index, patient-centered data report and analysis, and cohort analysis. The evaluation of our study was performed by testing the adaptability of the framework on two public FHIR servers. We identify common research requirements and current outstanding issues, and discuss future enhancement work of the current studies. Overall, our study demonstrated that it is feasible to use Shiny for implementing interactive analysis on FHIR-based standardized clinical data.

RESTFul based heterogeneous Geoprocessing workflow interoperation for Sensor Web Service

NASA Astrophysics Data System (ADS)

Yang, Chao; Chen, Nengcheng; Di, Liping

2012-10-01

Advanced sensors on board satellites offer detailed Earth observations. A workflow is one approach for designing, implementing and constructing a flexible and live link between these sensors' resources and users. It can coordinate, organize and aggregate the distributed sensor Web services to meet the requirement of a complex Earth observation scenario. A RESTFul based workflow interoperation method is proposed to integrate heterogeneous workflows into an interoperable unit. The Atom protocols are applied to describe and manage workflow resources. The XML Process Definition Language (XPDL) and Business Process Execution Language (BPEL) workflow standards are applied to structure a workflow that accesses sensor information and one that processes it separately. Then, a scenario for nitrogen dioxide (NO2) from a volcanic eruption is used to investigate the feasibility of the proposed method. The RESTFul based workflows interoperation system can describe, publish, discover, access and coordinate heterogeneous Geoprocessing workflows.

Scientific Data Management (SDM) Center for Enabling Technologies. 2007-2012

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

Ludascher, Bertram; Altintas, Ilkay

Over the past five years, our activities have both established Kepler as a viable scientific workflow environment and demonstrated its value across multiple science applications. We have published numerous peer-reviewed papers on the technologies highlighted in this short paper and have given Kepler tutorials at SC06,SC07,SC08,and SciDAC 2007. Our outreach activities have allowed scientists to learn best practices and better utilize Kepler to address their individual workflow problems. Our contributions to advancing the state-of-the-art in scientific workflows have focused on the following areas. Progress in each of these areas is described in subsequent sections. Workflow development. The development of amore » deeper understanding of scientific workflows "in the wild" and of the requirements for support tools that allow easy construction of complex scientific workflows; Generic workflow components and templates. The development of generic actors (i.e.workflow components and processes) which can be broadly applied to scientific problems; Provenance collection and analysis. The design of a flexible provenance collection and analysis infrastructure within the workflow environment; and, Workflow reliability and fault tolerance. The improvement of the reliability and fault-tolerance of workflow environments.« less

Distributed information system architecture for Primary Health Care.

PubMed

Grammatikou, M; Stamatelopoulos, F; Maglaris, B

2000-01-01

We present a distributed architectural framework for Primary Health Care (PHC) Centres. Distribution is handled through the introduction of the Roaming Electronic Health Care Record (R-EHCR) and the use of local caching and incremental update of a global index. The proposed architecture is designed to accommodate a specific PHC workflow model. Finally, we discuss a pilot implementation in progress, which is based on CORBA and web-based user interfaces. However, the conceptual architecture is generic and open to other middleware approaches like the DHE or HL7.

Quality: performance improvement, teamwork, information technology and protocols.

PubMed

Coleman, Nana E; Pon, Steven

2013-04-01

Using the Institute of Medicine framework that outlines the domains of quality, this article considers four key aspects of health care delivery which have the potential to significantly affect the quality of health care within the pediatric intensive care unit. The discussion covers: performance improvement and how existing methods for reporting, review, and analysis of medical error relate to patient care; team composition and workflow; and the impact of information technologies on clinical practice. Also considered is how protocol-driven and standardized practice affects both patients and the fiscal interests of the health care system.

Final technical report for DE-SC00012633 AToM (Advanced Tokamak Modeling)

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

Holland, Christopher; Orlov, Dmitri; Izzo, Valerie

This final report for the AToM project documents contributions from University of California, San Diego researchers over the period of 9/1/2014 – 8/31/2017. The primary focus of these efforts was on performing validation studies of core tokamak transport models using the OMFIT framework, including development of OMFIT workflow scripts. Additional work was performed to develop tools for use of the nonlinear magnetohydrodynamics code NIMROD in OMFIT, and its use in the study of runaway electron dynamics in tokamak disruptions.

Single-cell Transcriptome Study as Big Data

PubMed Central

Yu, Pingjian; Lin, Wei

2016-01-01

The rapid growth of single-cell RNA-seq studies (scRNA-seq) demands efficient data storage, processing, and analysis. Big-data technology provides a framework that facilitates the comprehensive discovery of biological signals from inter-institutional scRNA-seq datasets. The strategies to solve the stochastic and heterogeneous single-cell transcriptome signal are discussed in this article. After extensively reviewing the available big-data applications of next-generation sequencing (NGS)-based studies, we propose a workflow that accounts for the unique characteristics of scRNA-seq data and primary objectives of single-cell studies. PMID:26876720

Design and Applications of a GeoSemantic Framework for Integration of Data and Model Resources in Hydrologic Systems

NASA Astrophysics Data System (ADS)

Elag, M.; Kumar, P.

2016-12-01

Hydrologists today have to integrate resources such as data and models, which originate and reside in multiple autonomous and heterogeneous repositories over the Web. Several resource management systems have emerged within geoscience communities for sharing long-tail data, which are collected by individual or small research groups, and long-tail models, which are developed by scientists or small modeling communities. While these systems have increased the availability of resources within geoscience domains, deficiencies remain due to the heterogeneity in the methods, which are used to describe, encode, and publish information about resources over the Web. This heterogeneity limits our ability to access the right information in the right context so that it can be efficiently retrieved and understood without the Hydrologist's mediation. A primary challenge of the Web today is the lack of the semantic interoperability among the massive number of resources, which already exist and are continually being generated at rapid rates. To address this challenge, we have developed a decentralized GeoSemantic (GS) framework, which provides three sets of micro-web services to support (i) semantic annotation of resources, (ii) semantic alignment between the metadata of two resources, and (iii) semantic mediation among Standard Names. Here we present the design of the framework and demonstrate its application for semantic integration between data and models used in the IML-CZO. First we show how the IML-CZO data are annotated using the Semantic Annotation Services. Then we illustrate how the Resource Alignment Services and Knowledge Integration Services are used to create a semantic workflow among TopoFlow model, which is a spatially-distributed hydrologic model and the annotated data. Results of this work are (i) a demonstration of how the GS framework advances the integration of heterogeneous data and models of water-related disciplines by seamless handling of their semantic heterogeneity, (ii) an introduction of new paradigm for reusing existing and new standards as well as tools and models without the need of their implementation in the Cyberinfrastructures of water-related disciplines, and (iii) an investigation of a methodology by which distributed models can be coupled in a workflow using the GS services.

Integrated Modeling of Time Evolving 3D Kinetic MHD Equilibria and NTV Torque

NASA Astrophysics Data System (ADS)

Logan, N. C.; Park, J.-K.; Grierson, B. A.; Haskey, S. R.; Nazikian, R.; Cui, L.; Smith, S. P.; Meneghini, O.

2016-10-01

New analysis tools and integrated modeling of plasma dynamics developed in the OMFIT framework are used to study kinetic MHD equilibria evolution on the transport time scale. The experimentally observed profile dynamics following the application of 3D error fields are described using a new OMFITprofiles workflow that directly addresses the need for rapid and comprehensive analysis of dynamic equilibria for next-step theory validation. The workflow treats all diagnostic data as fundamentally time dependent, provides physics-based manipulations such as ELM phase data selection, and is consistent across multiple machines - including DIII-D and NSTX-U. The seamless integration of tokamak data and simulation is demonstrated by using the self-consistent kinetic EFIT equilibria and profiles as input into 2D particle, momentum and energy transport calculations using TRANSP as well as 3D kinetic MHD equilibrium stability and neoclassical transport modeling using General Perturbed Equilibrium Code (GPEC). The result is a smooth kinetic stability and NTV torque evolution over transport time scales. Work supported by DE-AC02-09CH11466.

Virtual planning for craniomaxillofacial surgery--7 years of experience.

PubMed

Adolphs, Nicolai; Haberl, Ernst-Johannes; Liu, Weichen; Keeve, Erwin; Menneking, Horst; Hoffmeister, Bodo

2014-07-01

Contemporary computer-assisted surgery systems more and more allow for virtual simulation of even complex surgical procedures with increasingly realistic predictions. Preoperative workflows are established and different commercially software solutions are available. Potential and feasibility of virtual craniomaxillofacial surgery as an additional planning tool was assessed retrospectively by comparing predictions and surgical results. Since 2006 virtual simulation has been performed in selected patient cases affected by complex craniomaxillofacial disorders (n = 8) in addition to standard surgical planning based on patient specific 3d-models. Virtual planning could be performed for all levels of the craniomaxillofacial framework within a reasonable preoperative workflow. Simulation of even complex skeletal displacements corresponded well with the real surgical result and soft tissue simulation proved to be helpful. In combination with classic 3d-models showing the underlying skeletal pathology virtual simulation improved planning and transfer of craniomaxillofacial corrections. Additional work and expenses may be justified by increased possibilities of visualisation, information, instruction and documentation in selected craniomaxillofacial procedures. Copyright © 2013 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Using bio.tools to generate and annotate workbench tool descriptions

PubMed Central

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

2017-01-01

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

Developing integrated workflows for the digitisation of herbarium specimens using a modular and scalable approach

PubMed Central

Haston, Elspeth; Cubey, Robert; Pullan, Martin; Atkins, Hannah; Harris, David J

2012-01-01

Abstract Digitisation programmes in many institutes frequently involve disparate and irregular funding, diverse selection criteria and scope, with different members of staff managing and operating the processes. These factors have influenced the decision at the Royal Botanic Garden Edinburgh to develop an integrated workflow for the digitisation of herbarium specimens which is modular and scalable to enable a single overall workflow to be used for all digitisation projects. This integrated workflow is comprised of three principal elements: a specimen workflow, a data workflow and an image workflow. The specimen workflow is strongly linked to curatorial processes which will impact on the prioritisation, selection and preparation of the specimens. The importance of including a conservation element within the digitisation workflow is highlighted. The data workflow includes the concept of three main categories of collection data: label data, curatorial data and supplementary data. It is shown that each category of data has its own properties which influence the timing of data capture within the workflow. Development of software has been carried out for the rapid capture of curatorial data, and optical character recognition (OCR) software is being used to increase the efficiency of capturing label data and supplementary data. The large number and size of the images has necessitated the inclusion of automated systems within the image workflow. PMID:22859881

Multimodal Teaching Analytics: Automated Extraction of Orchestration Graphs from Wearable Sensor Data

ERIC Educational Resources Information Center

Prieto, L. P.; Sharma, K.; Kidzinski, L.; Rodríguez-Triana, M. J.; Dillenbourg, P.

2018-01-01

The pedagogical modelling of everyday classroom practice is an interesting kind of evidence, both for educational research and teachers' own professional development. This paper explores the usage of wearable sensors and machine learning techniques to automatically extract orchestration graphs (teaching activities and their social plane over time)…

Generic Service Integration in Adaptive Learning Experiences Using IMS Learning Design

ERIC Educational Resources Information Center

de-la-Fuente-Valentin, Luis; Pardo, Abelardo; Kloos, Carlos Delgado

2011-01-01

IMS Learning Design is a specification to capture the orchestration taking place in a learning scenario. This paper presents an extension called Generic Service Integration. This paradigm allows a bidirectional communication between the course engine in charge of the orchestration and conventional Web 2.0 tools. This communication allows the…

Instructional Design or School Politics? A Discussion of "Orchestration" in TEL Research

ERIC Educational Resources Information Center

Perrotta, C.; Evans, M. A.

2013-01-01

This paper argues that the emphasis on orchestration as a metaphor for teaching in technology-enhanced learning (TEL) environments, featured in recent academic discussions, is an opportunity to broaden the scope of the inquiry into educational technology. Drawing on sociological literature and research that investigated the systemic factors that…

Kindergarten Teachers' Orchestration of Mathematical Activities Afforded by Technology: Agency and Mediation

ERIC Educational Resources Information Center

Carlsen, Martin; Erfjord, Ingvald; Hundeland, Per Sigurd; Monaghan, John

2016-01-01

This paper focuses on kindergarten teachers' interactions with young children during mathematical learning activities involving the use of digital tools. We aim to characterise the teachers' roles and actions in these activities and extend considerations of teachers' orchestrations current in the research literature with regard to agency and…

Incorporating Brokers within Collaboration Environments

NASA Astrophysics Data System (ADS)

Rajasekar, A.; Moore, R.; de Torcy, A.

2013-12-01

A collaboration environment, such as the integrated Rule Oriented Data System (iRODS - http://irods.diceresearch.org), provides interoperability mechanisms for accessing storage systems, authentication systems, messaging systems, information catalogs, networks, and policy engines from a wide variety of clients. The interoperability mechanisms function as brokers, translating actions requested by clients to the protocol required by a specific technology. The iRODS data grid is used to enable collaborative research within hydrology, seismology, earth science, climate, oceanography, plant biology, astronomy, physics, and genomics disciplines. Although each domain has unique resources, data formats, semantics, and protocols, the iRODS system provides a generic framework that is capable of managing collaborative research initiatives that span multiple disciplines. Each interoperability mechanism (broker) is linked to a name space that enables unified access across the heterogeneous systems. The collaboration environment provides not only support for brokers, but also support for virtualization of name spaces for users, files, collections, storage systems, metadata, and policies. The broker enables access to data or information in a remote system using the appropriate protocol, while the collaboration environment provides a uniform naming convention for accessing and manipulating each object. Within the NSF DataNet Federation Consortium project (http://www.datafed.org), three basic types of interoperability mechanisms have been identified and applied: 1) drivers for managing manipulation at the remote resource (such as data subsetting), 2) micro-services that execute the protocol required by the remote resource, and 3) policies for controlling the execution. For example, drivers have been written for manipulating NetCDF and HDF formatted files within THREDDS servers. Micro-services have been written that manage interactions with the CUAHSI data repository, the DataONE information catalog, and the GeoBrain broker. Policies have been written that manage transfer of messages between an iRODS message queue and the Advanced Message Queuing Protocol. Examples of these brokering mechanisms will be presented. The DFC collaboration environment serves as the intermediary between community resources and compute grids, enabling reproducible data-driven research. It is possible to create an analysis workflow that retrieves data subsets from a remote server, assemble the required input files, automate the execution of the workflow, automatically track the provenance of the workflow, and share the input files, workflow, and output files. A collaborator can re-execute a shared workflow, compare results, change input files, and re-execute an analysis.

Next-generation sequencing facilitates quantitative analysis of wild-type and Nrl−/− retinal transcriptomes

PubMed Central

Brooks, Matthew J.; Rajasimha, Harsha K.; Roger, Jerome E.

2011-01-01

Purpose Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis. Methods Retinal mRNA profiles of 21-day-old wild-type (WT) and neural retina leucine zipper knockout (Nrl−/−) mice were generated by deep sequencing, in triplicate, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays. Results Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl−/− mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and a goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl−/− retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusions Our study represents the first detailed analysis of retinal transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. PMID:22162623

Classical workflow nets and workflow nets with reset arcs: using Lyapunov stability for soundness verification

NASA Astrophysics Data System (ADS)

Clempner, Julio B.

2017-01-01

This paper presents a novel analytical method for soundness verification of workflow nets and reset workflow nets, using the well-known stability results of Lyapunov for Petri nets. We also prove that the soundness property is decidable for workflow nets and reset workflow nets. In addition, we provide evidence of several outcomes related with properties such as boundedness, liveness, reversibility and blocking using stability. Our approach is validated theoretically and by a numerical example related to traffic signal-control synchronisation.

The Mining Minds digital health and wellness framework.

PubMed

Banos, Oresti; Bilal Amin, Muhammad; Ali Khan, Wajahat; Afzal, Muhammad; Hussain, Maqbool; Kang, Byeong Ho; Lee, Sungyong

2016-07-15

The provision of health and wellness care is undergoing an enormous transformation. A key element of this revolution consists in prioritizing prevention and proactivity based on the analysis of people's conducts and the empowerment of individuals in their self-management. Digital technologies are unquestionably destined to be the main engine of this change, with an increasing number of domain-specific applications and devices commercialized every year; however, there is an apparent lack of frameworks capable of orchestrating and intelligently leveraging, all the data, information and knowledge generated through these systems. This work presents Mining Minds, a novel framework that builds on the core ideas of the digital health and wellness paradigms to enable the provision of personalized support. Mining Minds embraces some of the most prominent digital technologies, ranging from Big Data and Cloud Computing to Wearables and Internet of Things, as well as modern concepts and methods, such as context-awareness, knowledge bases or analytics, to holistically and continuously investigate on people's lifestyles and provide a variety of smart coaching and support services. This paper comprehensively describes the efficient and rational combination and interoperation of these technologies and methods through Mining Minds, while meeting the essential requirements posed by a framework for personalized health and wellness support. Moreover, this work presents a realization of the key architectural components of Mining Minds, as well as various exemplary user applications and expert tools to illustrate some of the potential services supported by the proposed framework. Mining Minds constitutes an innovative holistic means to inspect human behavior and provide personalized health and wellness support. The principles behind this framework uncover new research ideas and may serve as a reference for similar initiatives.

Biowep: a workflow enactment portal for bioinformatics applications.

PubMed

Romano, Paolo; Bartocci, Ezio; Bertolini, Guglielmo; De Paoli, Flavio; Marra, Domenico; Mauri, Giancarlo; Merelli, Emanuela; Milanesi, Luciano

2007-03-08

The huge amount of biological information, its distribution over the Internet and the heterogeneity of available software tools makes the adoption of new data integration and analysis network tools a necessity in bioinformatics. ICT standards and tools, like Web Services and Workflow Management Systems (WMS), can support the creation and deployment of such systems. Many Web Services are already available and some WMS have been proposed. They assume that researchers know which bioinformatics resources can be reached through a programmatic interface and that they are skilled in programming and building workflows. Therefore, they are not viable to the majority of unskilled researchers. A portal enabling these to take profit from new technologies is still missing. We designed biowep, a web based client application that allows for the selection and execution of a set of predefined workflows. The system is available on-line. Biowep architecture includes a Workflow Manager, a User Interface and a Workflow Executor. The task of the Workflow Manager is the creation and annotation of workflows. These can be created by using either the Taverna Workbench or BioWMS. Enactment of workflows is carried out by FreeFluo for Taverna workflows and by BioAgent/Hermes, a mobile agent-based middleware, for BioWMS ones. Main workflows' processing steps are annotated on the basis of their input and output, elaboration type and application domain by using a classification of bioinformatics data and tasks. The interface supports users authentication and profiling. Workflows can be selected on the basis of users' profiles and can be searched through their annotations. Results can be saved. We developed a web system that support the selection and execution of predefined workflows, thus simplifying access for all researchers. The implementation of Web Services allowing specialized software to interact with an exhaustive set of biomedical databases and analysis software and the creation of effective workflows can significantly improve automation of in-silico analysis. Biowep is available for interested researchers as a reference portal. They are invited to submit their workflows to the workflow repository. Biowep is further being developed in the sphere of the Laboratory of Interdisciplinary Technologies in Bioinformatics - LITBIO.

Biowep: a workflow enactment portal for bioinformatics applications

PubMed Central

Romano, Paolo; Bartocci, Ezio; Bertolini, Guglielmo; De Paoli, Flavio; Marra, Domenico; Mauri, Giancarlo; Merelli, Emanuela; Milanesi, Luciano

2007-01-01

Background The huge amount of biological information, its distribution over the Internet and the heterogeneity of available software tools makes the adoption of new data integration and analysis network tools a necessity in bioinformatics. ICT standards and tools, like Web Services and Workflow Management Systems (WMS), can support the creation and deployment of such systems. Many Web Services are already available and some WMS have been proposed. They assume that researchers know which bioinformatics resources can be reached through a programmatic interface and that they are skilled in programming and building workflows. Therefore, they are not viable to the majority of unskilled researchers. A portal enabling these to take profit from new technologies is still missing. Results We designed biowep, a web based client application that allows for the selection and execution of a set of predefined workflows. The system is available on-line. Biowep architecture includes a Workflow Manager, a User Interface and a Workflow Executor. The task of the Workflow Manager is the creation and annotation of workflows. These can be created by using either the Taverna Workbench or BioWMS. Enactment of workflows is carried out by FreeFluo for Taverna workflows and by BioAgent/Hermes, a mobile agent-based middleware, for BioWMS ones. Main workflows' processing steps are annotated on the basis of their input and output, elaboration type and application domain by using a classification of bioinformatics data and tasks. The interface supports users authentication and profiling. Workflows can be selected on the basis of users' profiles and can be searched through their annotations. Results can be saved. Conclusion We developed a web system that support the selection and execution of predefined workflows, thus simplifying access for all researchers. The implementation of Web Services allowing specialized software to interact with an exhaustive set of biomedical databases and analysis software and the creation of effective workflows can significantly improve automation of in-silico analysis. Biowep is available for interested researchers as a reference portal. They are invited to submit their workflows to the workflow repository. Biowep is further being developed in the sphere of the Laboratory of Interdisciplinary Technologies in Bioinformatics – LITBIO. PMID:17430563

Exploring the impact of an automated prescription-filling device on community pharmacy technician workflow.

PubMed

Walsh, Kristin E; Chui, Michelle Anne; Kieser, Mara A; Williams, Staci M; Sutter, Susan L; Sutter, John G

2011-01-01

To explore community pharmacy technician workflow change after implementation of an automated robotic prescription-filling device. At an independent community pharmacy in rural Mayville, WI, pharmacy technicians were observed before and 3 months after installation of an automated robotic prescription-filling device. The main outcome measures were sequences and timing of technician workflow steps, workflow interruptions, automation surprises, and workarounds. Of the 77 and 80 observations made before and 3 months after robot installation, respectively, 17 different workflow sequences were observed before installation and 38 after installation. Average prescription filling time was reduced by 40 seconds per prescription with use of the robot. Workflow interruptions per observation increased from 1.49 to 1.79 (P = 0.11), and workarounds increased from 10% to 36% after robot use. Although automated prescription-filling devices can increase efficiency, workflow interruptions and workarounds may negate that efficiency. Assessing changes in workflow and sequencing of tasks that may result from the use of automation can help uncover opportunities for workflow policy and procedure redesign.

Integration of Geographical Information Systems and Geophysical Applications with Distributed Computing Technologies.

NASA Astrophysics Data System (ADS)

Pierce, M. E.; Aktas, M. S.; Aydin, G.; Fox, G. C.; Gadgil, H.; Sayar, A.

2005-12-01

We examine the application of Web Service Architectures and Grid-based distributed computing technologies to geophysics and geo-informatics. We are particularly interested in the integration of Geographical Information System (GIS) services with distributed data mining applications. GIS services provide the general purpose framework for building archival data services, real time streaming data services, and map-based visualization services that may be integrated with data mining and other applications through the use of distributed messaging systems and Web Service orchestration tools. Building upon on our previous work in these areas, we present our current research efforts. These include fundamental investigations into increasing XML-based Web service performance, supporting real time data streams, and integrating GIS mapping tools with audio/video collaboration systems for shared display and annotation.

The Behavioral Intervention Technology Model: An Integrated Conceptual and Technological Framework for eHealth and mHealth Interventions

PubMed Central

Schueller, Stephen M; Montague, Enid; Burns, Michelle Nicole; Rashidi, Parisa

2014-01-01

A growing number of investigators have commented on the lack of models to inform the design of behavioral intervention technologies (BITs). BITs, which include a subset of mHealth and eHealth interventions, employ a broad range of technologies, such as mobile phones, the Web, and sensors, to support users in changing behaviors and cognitions related to health, mental health, and wellness. We propose a model that conceptually defines BITs, from the clinical aim to the technological delivery framework. The BIT model defines both the conceptual and technological architecture of a BIT. Conceptually, a BIT model should answer the questions why, what, how (conceptual and technical), and when. While BITs generally have a larger treatment goal, such goals generally consist of smaller intervention aims (the "why") such as promotion or reduction of specific behaviors, and behavior change strategies (the conceptual "how"), such as education, goal setting, and monitoring. Behavior change strategies are instantiated with specific intervention components or “elements” (the "what"). The characteristics of intervention elements may be further defined or modified (the technical "how") to meet the needs, capabilities, and preferences of a user. Finally, many BITs require specification of a workflow that defines when an intervention component will be delivered. The BIT model includes a technological framework (BIT-Tech) that can integrate and implement the intervention elements, characteristics, and workflow to deliver the entire BIT to users over time. This implementation may be either predefined or include adaptive systems that can tailor the intervention based on data from the user and the user’s environment. The BIT model provides a step towards formalizing the translation of developer aims into intervention components, larger treatments, and methods of delivery in a manner that supports research and communication between investigators on how to design, develop, and deploy BITs. PMID:24905070

The behavioral intervention technology model: an integrated conceptual and technological framework for eHealth and mHealth interventions.

PubMed

Mohr, David C; Schueller, Stephen M; Montague, Enid; Burns, Michelle Nicole; Rashidi, Parisa

2014-06-05

A growing number of investigators have commented on the lack of models to inform the design of behavioral intervention technologies (BITs). BITs, which include a subset of mHealth and eHealth interventions, employ a broad range of technologies, such as mobile phones, the Web, and sensors, to support users in changing behaviors and cognitions related to health, mental health, and wellness. We propose a model that conceptually defines BITs, from the clinical aim to the technological delivery framework. The BIT model defines both the conceptual and technological architecture of a BIT. Conceptually, a BIT model should answer the questions why, what, how (conceptual and technical), and when. While BITs generally have a larger treatment goal, such goals generally consist of smaller intervention aims (the "why") such as promotion or reduction of specific behaviors, and behavior change strategies (the conceptual "how"), such as education, goal setting, and monitoring. Behavior change strategies are instantiated with specific intervention components or "elements" (the "what"). The characteristics of intervention elements may be further defined or modified (the technical "how") to meet the needs, capabilities, and preferences of a user. Finally, many BITs require specification of a workflow that defines when an intervention component will be delivered. The BIT model includes a technological framework (BIT-Tech) that can integrate and implement the intervention elements, characteristics, and workflow to deliver the entire BIT to users over time. This implementation may be either predefined or include adaptive systems that can tailor the intervention based on data from the user and the user's environment. The BIT model provides a step towards formalizing the translation of developer aims into intervention components, larger treatments, and methods of delivery in a manner that supports research and communication between investigators on how to design, develop, and deploy BITs.

Generic worklist handler for workflow-enabled products

NASA Astrophysics Data System (ADS)

Schmidt, Joachim; Meetz, Kirsten; Wendler, Thomas

1999-07-01

Workflow management (WfM) is an emerging field of medical information technology. It appears as a promising key technology to model, optimize and automate processes, for the sake of improved efficiency, reduced costs and improved patient care. The Application of WfM concepts requires the standardization of architectures and interfaces. A component of central interest proposed in this report is a generic work list handler: A standardized interface between a workflow enactment service and application system. Application systems with embedded work list handlers will be called 'Workflow Enabled Application Systems'. In this paper we discus functional requirements of work list handlers, as well as their integration into workflow architectures and interfaces. To lay the foundation for this specification, basic workflow terminology, the fundamentals of workflow management and - later in the paper - the available standards as defined by the Workflow Management Coalition are briefly reviewed.

Elementary Introduction to the Green Management of the Construction in Whole Process

NASA Astrophysics Data System (ADS)

Na), Wu Y. N.(Yun; Yu), Yan H. Y.(Hong; Jun), Huang Z. J.(Zhi

Construction industries consume more energy resources than necessary. it is essential to establish a management system with all pollution problems resolved to construct green buildings. By applying the theory of whole life cycle, this paper divides the whole process of construction into four sub-phases, which will also be subdivided into more concrete working procedures. Based on this, a systematic framework is promoted for the green management of the construction, especially and creatively, considering the green aims as important as the traditional three aims-"quality aim, schedule aim and cost aim". This framework, adhering to the integration idea-"customers first, whole optimal", regards the green control and workflow as an organic whole in order to build green, sustainable and healthy architecture, and then provide a perfect guide and reference to the green management.

The EVER-EST portal as support for the Sea Monitoring Virtual Research Community, through the sharing of resources, enabling dynamic collaboration and promoting community engagement

NASA Astrophysics Data System (ADS)

Foglini, Federica; Grande, Valentina; De Leo, Francesco; Mantovani, Simone; Ferraresi, Sergio

2017-04-01

EVER-EST offers a framework based on advanced services delivered both at the e-infrastructure and domain-specific level, with the objective of supporting each phase of the Earth Science Research and Information Lifecycle. It provides innovative e-research services to Earth Science user communities for communication, cross-validation and the sharing of knowledge and science outputs. The project follows a user-centric approach: real use cases taken from pre-selected Virtual Research Communities (VRC) covering different Earth Science research scenarios drive the implementation of the Virtual Research Environment (VRE) services and capabilities. The Sea Monitoring community is involved in the evaluation of the EVER-EST infrastructure. The community of potential users is wide and heterogeneous including both multi-disciplinary scientists and national/international agencies and authorities (e.g. MPAs directors, technicians from regional agencies like ARPA in Italy, the technicians working for the Ministry of the Environment) dealing with the adoption of a better way of measuring the quality of the environment. The scientific community has the main role of assessing the best criteria and indicators for defining the Good Environmental Status (GES) in their own sub regions, and implementing methods, protocols and tools for monitoring the GES descriptors. According to the Marine Strategy Framework Directive (MSFD), the environmental status of marine waters is defined by 11 descriptors, and forms a proposed set of 29 associated criteria and 56 different indicators. The objective of the Sea Monitoring VRC is to provide useful and applicable contributions to the evaluation of the descriptors: D1.Biodiversity, D2.Non-indigenous species and D6.Seafloor Integrity (http://ec.europa.eu/environment/marine/good-environmental-status/index_en.htm). The main challenges for the community members are: 1. discovery of existing data and products distributed among different infrastructures; 2. sharing methodologies about the GES evaluation and monitoring; 3. working on the same workflows and data; 4. adopting shared powerful tools for data processing (e.g. software and servers). The Sea Monitoring portal provides the VRC users with tools and services aimed at enhancing their ability to interoperate and share knowledge, experience and methods for GES assessment and monitoring, such as: •digital information services for data management, exploitation and preservation (accessibility of heterogeneous data sources including associated documentation); •e-collaboration services to communicate and share knowledge, ideas, protocols and workflows; •e-learning services to facilitate the use of common workflows for assessing GES indicators; •e-research services for workflow management, validation and verification, as well as visualization and interactive services. The current study is co-financed by the European Union's Horizon 2020 research and innovation programme under the EVER-EST project (Grant Agreement No. 674907).

Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms.

PubMed

Wang, Jianwu; Korambath, Prakashan; Altintas, Ilkay; Davis, Jim; Crawl, Daniel

2014-01-01

With more and more workflow systems adopting cloud as their execution environment, it becomes increasingly challenging on how to efficiently manage various workflows, virtual machines (VMs) and workflow execution on VM instances. To make the system scalable and easy-to-extend, we design a Workflow as a Service (WFaaS) architecture with independent services. A core part of the architecture is how to efficiently respond continuous workflow requests from users and schedule their executions in the cloud. Based on different targets, we propose four heuristic workflow scheduling algorithms for the WFaaS architecture, and analyze the differences and best usages of the algorithms in terms of performance, cost and the price/performance ratio via experimental studies.

Tigres Workflow Library: Supporting Scientific Pipelines on HPC Systems

DOE PAGES

Hendrix, Valerie; Fox, James; Ghoshal, Devarshi; ...

2016-07-21

The growth in scientific data volumes has resulted in the need for new tools that enable users to operate on and analyze data on large-scale resources. In the last decade, a number of scientific workflow tools have emerged. These tools often target distributed environments, and often need expert help to compose and execute the workflows. Data-intensive workflows are often ad-hoc, they involve an iterative development process that includes users composing and testing their workflows on desktops, and scaling up to larger systems. In this paper, we present the design and implementation of Tigres, a workflow library that supports the iterativemore » workflow development cycle of data-intensive workflows. Tigres provides an application programming interface to a set of programming templates i.e., sequence, parallel, split, merge, that can be used to compose and execute computational and data pipelines. We discuss the results of our evaluation of scientific and synthetic workflows showing Tigres performs with minimal template overheads (mean of 13 seconds over all experiments). We also discuss various factors (e.g., I/O performance, execution mechanisms) that affect the performance of scientific workflows on HPC systems.« less

Tigres Workflow Library: Supporting Scientific Pipelines on HPC Systems

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

Hendrix, Valerie; Fox, James; Ghoshal, Devarshi

The growth in scientific data volumes has resulted in the need for new tools that enable users to operate on and analyze data on large-scale resources. In the last decade, a number of scientific workflow tools have emerged. These tools often target distributed environments, and often need expert help to compose and execute the workflows. Data-intensive workflows are often ad-hoc, they involve an iterative development process that includes users composing and testing their workflows on desktops, and scaling up to larger systems. In this paper, we present the design and implementation of Tigres, a workflow library that supports the iterativemore » workflow development cycle of data-intensive workflows. Tigres provides an application programming interface to a set of programming templates i.e., sequence, parallel, split, merge, that can be used to compose and execute computational and data pipelines. We discuss the results of our evaluation of scientific and synthetic workflows showing Tigres performs with minimal template overheads (mean of 13 seconds over all experiments). We also discuss various factors (e.g., I/O performance, execution mechanisms) that affect the performance of scientific workflows on HPC systems.« less

Standardizing clinical trials workflow representation in UML for international site comparison.

PubMed

de Carvalho, Elias Cesar Araujo; Jayanti, Madhav Kishore; Batilana, Adelia Portero; Kozan, Andreia M O; Rodrigues, Maria J; Shah, Jatin; Loures, Marco R; Patil, Sunita; Payne, Philip; Pietrobon, Ricardo

2010-11-09

With the globalization of clinical trials, a growing emphasis has been placed on the standardization of the workflow in order to ensure the reproducibility and reliability of the overall trial. Despite the importance of workflow evaluation, to our knowledge no previous studies have attempted to adapt existing modeling languages to standardize the representation of clinical trials. Unified Modeling Language (UML) is a computational language that can be used to model operational workflow, and a UML profile can be developed to standardize UML models within a given domain. This paper's objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML. Two Brazilian clinical trial sites in rheumatology and oncology were examined to model their workflow and collect time-motion data. UML modeling was conducted in Eclipse, and a UML profile was developed to incorporate information used in discrete event simulation software. Ethnographic observation revealed bottlenecks in workflow: these included tasks requiring full commitment of CRCs, transferring notes from paper to computers, deviations from standard operating procedures, and conflicts between different IT systems. Time-motion analysis revealed that nurses' activities took up the most time in the workflow and contained a high frequency of shorter duration activities. Administrative assistants performed more activities near the beginning and end of the workflow. Overall, clinical trial tasks had a greater frequency than clinic routines or other general activities. This paper describes a method for modeling clinical trial workflow in UML and standardizing these workflow diagrams through a UML profile. In the increasingly global environment of clinical trials, the standardization of workflow modeling is a necessary precursor to conducting a comparative analysis of international clinical trials workflows.

Standardizing Clinical Trials Workflow Representation in UML for International Site Comparison

PubMed Central

de Carvalho, Elias Cesar Araujo; Jayanti, Madhav Kishore; Batilana, Adelia Portero; Kozan, Andreia M. O.; Rodrigues, Maria J.; Shah, Jatin; Loures, Marco R.; Patil, Sunita; Payne, Philip; Pietrobon, Ricardo

2010-01-01

Background With the globalization of clinical trials, a growing emphasis has been placed on the standardization of the workflow in order to ensure the reproducibility and reliability of the overall trial. Despite the importance of workflow evaluation, to our knowledge no previous studies have attempted to adapt existing modeling languages to standardize the representation of clinical trials. Unified Modeling Language (UML) is a computational language that can be used to model operational workflow, and a UML profile can be developed to standardize UML models within a given domain. This paper's objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML. Methods Two Brazilian clinical trial sites in rheumatology and oncology were examined to model their workflow and collect time-motion data. UML modeling was conducted in Eclipse, and a UML profile was developed to incorporate information used in discrete event simulation software. Results Ethnographic observation revealed bottlenecks in workflow: these included tasks requiring full commitment of CRCs, transferring notes from paper to computers, deviations from standard operating procedures, and conflicts between different IT systems. Time-motion analysis revealed that nurses' activities took up the most time in the workflow and contained a high frequency of shorter duration activities. Administrative assistants performed more activities near the beginning and end of the workflow. Overall, clinical trial tasks had a greater frequency than clinic routines or other general activities. Conclusions This paper describes a method for modeling clinical trial workflow in UML and standardizing these workflow diagrams through a UML profile. In the increasingly global environment of clinical trials, the standardization of workflow modeling is a necessary precursor to conducting a comparative analysis of international clinical trials workflows. PMID:21085484

Optimal Experimental Design of Borehole Locations for Bayesian Inference of Past Ice Sheet Surface Temperatures

NASA Astrophysics Data System (ADS)

Davis, A. D.; Huan, X.; Heimbach, P.; Marzouk, Y.

2017-12-01

Borehole data are essential for calibrating ice sheet models. However, field expeditions for acquiring borehole data are often time-consuming, expensive, and dangerous. It is thus essential to plan the best sampling locations that maximize the value of data while minimizing costs and risks. We present an uncertainty quantification (UQ) workflow based on rigorous probability framework to achieve these objectives. First, we employ an optimal experimental design (OED) procedure to compute borehole locations that yield the highest expected information gain. We take into account practical considerations of location accessibility (e.g., proximity to research sites, terrain, and ice velocity may affect feasibility of drilling) and robustness (e.g., real-time constraints such as weather may force researchers to drill at sub-optimal locations near those originally planned), by incorporating a penalty reflecting accessibility as well as sensitivity to deviations from the optimal locations. Next, we extract vertical temperature profiles from these boreholes and formulate a Bayesian inverse problem to reconstruct past surface temperatures. Using a model of temperature advection/diffusion, the top boundary condition (corresponding to surface temperatures) is calibrated via efficient Markov chain Monte Carlo (MCMC). The overall procedure can then be iterated to choose new optimal borehole locations for the next expeditions.Through this work, we demonstrate powerful UQ methods for designing experiments, calibrating models, making predictions, and assessing sensitivity--all performed under an uncertain environment. We develop a theoretical framework as well as practical software within an intuitive workflow, and illustrate their usefulness for combining data and models for environmental and climate research.

The pipeline system for Octave and Matlab (PSOM): a lightweight scripting framework and execution engine for scientific workflows.

PubMed

Bellec, Pierre; Lavoie-Courchesne, Sébastien; Dickinson, Phil; Lerch, Jason P; Zijdenbos, Alex P; Evans, Alan C

2012-01-01

The analysis of neuroimaging databases typically involves a large number of inter-connected steps called a pipeline. The pipeline system for Octave and Matlab (PSOM) is a flexible framework for the implementation of pipelines in the form of Octave or Matlab scripts. PSOM does not introduce new language constructs to specify the steps and structure of the workflow. All steps of analysis are instead described by a regular Matlab data structure, documenting their associated command and options, as well as their input, output, and cleaned-up files. The PSOM execution engine provides a number of automated services: (1) it executes jobs in parallel on a local computing facility as long as the dependencies between jobs allow for it and sufficient resources are available; (2) it generates a comprehensive record of the pipeline stages and the history of execution, which is detailed enough to fully reproduce the analysis; (3) if an analysis is started multiple times, it executes only the parts of the pipeline that need to be reprocessed. PSOM is distributed under an open-source MIT license and can be used without restriction for academic or commercial projects. The package has no external dependencies besides Matlab or Octave, is straightforward to install and supports of variety of operating systems (Linux, Windows, Mac). We ran several benchmark experiments on a public database including 200 subjects, using a pipeline for the preprocessing of functional magnetic resonance images (fMRI). The benchmark results showed that PSOM is a powerful solution for the analysis of large databases using local or distributed computing resources.

UBioLab: a web-LABoratory for Ubiquitous in-silico experiments.

PubMed

Bartocci, E; Di Berardini, M R; Merelli, E; Vito, L

2012-03-01

The huge and dynamic amount of bioinformatic resources (e.g., data and tools) available nowadays in Internet represents a big challenge for biologists -for what concerns their management and visualization- and for bioinformaticians -for what concerns the possibility of rapidly creating and executing in-silico experiments involving resources and activities spread over the WWW hyperspace. Any framework aiming at integrating such resources as in a physical laboratory has imperatively to tackle -and possibly to handle in a transparent and uniform way- aspects concerning physical distribution, semantic heterogeneity, co-existence of different computational paradigms and, as a consequence, of different invocation interfaces (i.e., OGSA for Grid nodes, SOAP for Web Services, Java RMI for Java objects, etc.). The framework UBioLab has been just designed and developed as a prototype following the above objective. Several architectural features -as those ones of being fully Web-based and of combining domain ontologies, Semantic Web and workflow techniques- give evidence of an effort in such a direction. The integration of a semantic knowledge management system for distributed (bioinformatic) resources, a semantic-driven graphic environment for defining and monitoring ubiquitous workflows and an intelligent agent-based technology for their distributed execution allows UBioLab to be a semantic guide for bioinformaticians and biologists providing (i) a flexible environment for visualizing, organizing and inferring any (semantics and computational) "type" of domain knowledge (e.g., resources and activities, expressed in a declarative form), (ii) a powerful engine for defining and storing semantic-driven ubiquitous in-silico experiments on the domain hyperspace, as well as (iii) a transparent, automatic and distributed environment for correct experiment executions.

The pipeline system for Octave and Matlab (PSOM): a lightweight scripting framework and execution engine for scientific workflows

PubMed Central

Bellec, Pierre; Lavoie-Courchesne, Sébastien; Dickinson, Phil; Lerch, Jason P.; Zijdenbos, Alex P.; Evans, Alan C.

2012-01-01

The analysis of neuroimaging databases typically involves a large number of inter-connected steps called a pipeline. The pipeline system for Octave and Matlab (PSOM) is a flexible framework for the implementation of pipelines in the form of Octave or Matlab scripts. PSOM does not introduce new language constructs to specify the steps and structure of the workflow. All steps of analysis are instead described by a regular Matlab data structure, documenting their associated command and options, as well as their input, output, and cleaned-up files. The PSOM execution engine provides a number of automated services: (1) it executes jobs in parallel on a local computing facility as long as the dependencies between jobs allow for it and sufficient resources are available; (2) it generates a comprehensive record of the pipeline stages and the history of execution, which is detailed enough to fully reproduce the analysis; (3) if an analysis is started multiple times, it executes only the parts of the pipeline that need to be reprocessed. PSOM is distributed under an open-source MIT license and can be used without restriction for academic or commercial projects. The package has no external dependencies besides Matlab or Octave, is straightforward to install and supports of variety of operating systems (Linux, Windows, Mac). We ran several benchmark experiments on a public database including 200 subjects, using a pipeline for the preprocessing of functional magnetic resonance images (fMRI). The benchmark results showed that PSOM is a powerful solution for the analysis of large databases using local or distributed computing resources. PMID:22493575

MSNoise: Not Only dv/v! A Framework for Continuous Seismic Data Analysis

NASA Astrophysics Data System (ADS)

Mordret, A.; Lecocq, T.; De Plaen, R.; Caudron, C.; Brenguier, F.

2015-12-01

MSNoise is an Open and Free Python package known to be the only complete integrated workflow designed to analyse ambient seismic noise and study relative velocity changes (dv/v) in the crust. It is based on state of the art and well maintained Python modules, among which ObsPy plays an important role. To our knowledge, it is officially used for continuous monitoring at least in three notable places: the Observatory of the Piton de la Fournaise volcano (OVPF, France), the Auckland Volcanic Field (New Zealand) and on the South Napa earthquake (Berkeley, USA). It is also used by many researchers to process archive data, e.g. focussing on fault zones, intraplate Europe, geothermal exploitations or Antarctica. We first present the general working of MSNoise, originally written in 2010 to automatically scan data archives and process seismic data in order to produce dv/v time series. We demonstrate that its modularity provides a new potential to easily test new algorithms for each processing step. For example, to experiment new methods of cross-correlation (done by default in the frequency domain), stacking (default is linear stacking, averaging), or dt/t or dv/v estimation (default is moving window cross-spectrum "MWCS", so-called "doublet"), etc. Finally, we present the last major evolution of MSNoise, from a "single workflow: data archive to dv/v" to a framework system that allows plugins and modules to be developed and integrated into the MSNoise ecosystem. Examples of plugins in development such as continuous PPSD (à la McNamarra & Buland) or continuous RSAM/SSAM (Endo & Murray, Stephens) will be presented.

Network thermodynamic curation of human and yeast genome-scale metabolic models.

PubMed

Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

2014-07-15

Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

An Architecture Framework for Orchestrating Context-Aware IT Ecosystems: A Case Study for Quantitative Evaluation †.

PubMed

Park, Soojin; Park, Sungyong; Park, Young B

2018-02-12

With the emergence of various forms of smart devices and new paradigms such as the Internet of Things (IoT) concept, the IT (Information Technology) service areas are expanding explosively compared to the provision of services by single systems. A new system operation concept that has emerged in accordance with such technical trends is the IT ecosystem. The IT ecosystem can be considered a special type of system of systems in which multiple systems with various degrees of autonomy achieve common goals while adapting to the given environment. The single systems that participate in the IT ecosystem adapt autonomously to the current situation based on collected data from sensors. Furthermore, to maintain the services supported by the whole IT ecosystem sustainably, the configuration of single systems that participate in the IT ecosystem also changes appropriately in accordance with the changed situation. In order to support the IT ecosystem, this paper proposes an architecture framework that supports dynamic configuration changes to achieve the goal of the whole IT ecosystem, while ensuring the autonomy of single systems through the collection of data from sensors so as to recognize the situational context of individual participating systems. For the feasibility evaluation of the proposed framework, a simulated example of an IT ecosystem for unmanned forest management was constructed, and the quantitative evaluation results are discussed in terms of the extent to which the proposed architecture framework can continuously provide sustainable services in response to diverse environmental context changes.

Structural Control of Metabolic Flux

PubMed Central

Sajitz-Hermstein, Max; Nikoloski, Zoran

2013-01-01

Organisms have to continuously adapt to changing environmental conditions or undergo developmental transitions. To meet the accompanying change in metabolic demands, the molecular mechanisms of adaptation involve concerted interactions which ultimately induce a modification of the metabolic state, which is characterized by reaction fluxes and metabolite concentrations. These state transitions are the effect of simultaneously manipulating fluxes through several reactions. While metabolic control analysis has provided a powerful framework for elucidating the principles governing this orchestrated action to understand metabolic control, its applications are restricted by the limited availability of kinetic information. Here, we introduce structural metabolic control as a framework to examine individual reactions' potential to control metabolic functions, such as biomass production, based on structural modeling. The capability to carry out a metabolic function is determined using flux balance analysis (FBA). We examine structural metabolic control on the example of the central carbon metabolism of Escherichia coli by the recently introduced framework of functional centrality (FC). This framework is based on the Shapley value from cooperative game theory and FBA, and we demonstrate its superior ability to assign “share of control” to individual reactions with respect to metabolic functions and environmental conditions. A comparative analysis of various scenarios illustrates the usefulness of FC and its relations to other structural approaches pertaining to metabolic control. We propose a Monte Carlo algorithm to estimate FCs for large networks, based on the enumeration of elementary flux modes. We further give detailed biological interpretation of FCs for production of lactate and ATP under various respiratory conditions. PMID:24367246

Development of telescope control system for the 50cm telescope of UC Observatory Santa Martina

NASA Astrophysics Data System (ADS)

Shen, Tzu-Chiang; Soto, Ruben; Reveco, Johnny; Vanzi, Leonardo; Fernández, Jose M.; Escarate, Pedro; Suc, Vincent

2012-09-01

The main telescope of the UC Observatory Santa Martina is a 50cm optical telescope donated by ESO to Pontificia Universidad Catolica de Chile. During the past years the telescope has been refurbished and used as the main facility for testing and validating new instruments under construction by the center of Astro-Engineering UC. As part of this work, the need to develop a more efficient and flexible control system arises. The new distributed control system has been developed on top of Internet Communication Engine (ICE), a framework developed by Zeroc Inc. This framework features a lightweight but powerful and flexible inter-process communication infrastructure and provides binding to classic and modern programming languages, such as, C/C++, java, c#, ruby-rail, objective c, etc. The result of this work shows ICE as a real alternative for CORBA and other de-facto distribute programming framework. Classical control software architecture has been chosen and comprises an observation control system (OCS), the orchestrator of the observation, which controls the telescope control system (TCS), and detector control system (DCS). The real-time control and monitoring system is deployed and running over ARM based single board computers. Other features such as logging and configuration services have been developed as well. Inter-operation with other main astronomical control frameworks are foreseen in order achieve a smooth integration of instruments when they will be integrated in the main observatories in the north of Chile

An Architecture Framework for Orchestrating Context-Aware IT Ecosystems: A Case Study for Quantitative Evaluation †

PubMed Central

Park, Young B.

2018-01-01

With the emergence of various forms of smart devices and new paradigms such as the Internet of Things (IoT) concept, the IT (Information Technology) service areas are expanding explosively compared to the provision of services by single systems. A new system operation concept that has emerged in accordance with such technical trends is the IT ecosystem. The IT ecosystem can be considered a special type of system of systems in which multiple systems with various degrees of autonomy achieve common goals while adapting to the given environment. The single systems that participate in the IT ecosystem adapt autonomously to the current situation based on collected data from sensors. Furthermore, to maintain the services supported by the whole IT ecosystem sustainably, the configuration of single systems that participate in the IT ecosystem also changes appropriately in accordance with the changed situation. In order to support the IT ecosystem, this paper proposes an architecture framework that supports dynamic configuration changes to achieve the goal of the whole IT ecosystem, while ensuring the autonomy of single systems through the collection of data from sensors so as to recognize the situational context of individual participating systems. For the feasibility evaluation of the proposed framework, a simulated example of an IT ecosystem for unmanned forest management was constructed, and the quantitative evaluation results are discussed in terms of the extent to which the proposed architecture framework can continuously provide sustainable services in response to diverse environmental context changes. PMID:29439540

Quantitative workflow based on NN for weighting criteria in landfill suitability mapping

NASA Astrophysics Data System (ADS)

Abujayyab, Sohaib K. M.; Ahamad, Mohd Sanusi S.; Yahya, Ahmad Shukri; Ahmad, Siti Zubaidah; Alkhasawneh, Mutasem Sh.; Aziz, Hamidi Abdul

2017-10-01

Our study aims to introduce a new quantitative workflow that integrates neural networks (NNs) and multi criteria decision analysis (MCDA). Existing MCDA workflows reveal a number of drawbacks, because of the reliance on human knowledge in the weighting stage. Thus, new workflow presented to form suitability maps at the regional scale for solid waste planning based on NNs. A feed-forward neural network employed in the workflow. A total of 34 criteria were pre-processed to establish the input dataset for NN modelling. The final learned network used to acquire the weights of the criteria. Accuracies of 95.2% and 93.2% achieved for the training dataset and testing dataset, respectively. The workflow was found to be capable of reducing human interference to generate highly reliable maps. The proposed workflow reveals the applicability of NN in generating landfill suitability maps and the feasibility of integrating them with existing MCDA workflows.

An evolving computational platform for biological mass spectrometry: workflows, statistics and data mining with MASSyPup64.

PubMed

Winkler, Robert

2015-01-01

In biological mass spectrometry, crude instrumental data need to be converted into meaningful theoretical models. Several data processing and data evaluation steps are required to come to the final results. These operations are often difficult to reproduce, because of too specific computing platforms. This effect, known as 'workflow decay', can be diminished by using a standardized informatic infrastructure. Thus, we compiled an integrated platform, which contains ready-to-use tools and workflows for mass spectrometry data analysis. Apart from general unit operations, such as peak picking and identification of proteins and metabolites, we put a strong emphasis on the statistical validation of results and Data Mining. MASSyPup64 includes e.g., the OpenMS/TOPPAS framework, the Trans-Proteomic-Pipeline programs, the ProteoWizard tools, X!Tandem, Comet and SpiderMass. The statistical computing language R is installed with packages for MS data analyses, such as XCMS/metaXCMS and MetabR. The R package Rattle provides a user-friendly access to multiple Data Mining methods. Further, we added the non-conventional spreadsheet program teapot for editing large data sets and a command line tool for transposing large matrices. Individual programs, console commands and modules can be integrated using the Workflow Management System (WMS) taverna. We explain the useful combination of the tools by practical examples: (1) A workflow for protein identification and validation, with subsequent Association Analysis of peptides, (2) Cluster analysis and Data Mining in targeted Metabolomics, and (3) Raw data processing, Data Mining and identification of metabolites in untargeted Metabolomics. Association Analyses reveal relationships between variables across different sample sets. We present its application for finding co-occurring peptides, which can be used for target proteomics, the discovery of alternative biomarkers and protein-protein interactions. Data Mining derived models displayed a higher robustness and accuracy for classifying sample groups in targeted Metabolomics than cluster analyses. Random Forest models do not only provide predictive models, which can be deployed for new data sets, but also the variable importance. We demonstrate that the later is especially useful for tracking down significant signals and affected pathways in untargeted Metabolomics. Thus, Random Forest modeling supports the unbiased search for relevant biological features in Metabolomics. Our results clearly manifest the importance of Data Mining methods to disclose non-obvious information in biological mass spectrometry . The application of a Workflow Management System and the integration of all required programs and data in a consistent platform makes the presented data analyses strategies reproducible for non-expert users. The simple remastering process and the Open Source licenses of MASSyPup64 (http://www.bioprocess.org/massypup/) enable the continuous improvement of the system.

Visualizing Cross-sectional Data in a Real-World Context

NASA Astrophysics Data System (ADS)

Van Noten, K.; Lecocq, T.

2016-12-01

If you could fly around your research results in three dimensions, wouldn't you like to do it? Visualizing research results properly during scientific presentations already does half the job of informing the public on the geographic framework of your research. Many scientists use the Google Earth™ mapping service (V7.1.2.2041) because it's a great interactive mapping tool for assigning geographic coordinates to individual data points, localizing a research area, and draping maps of results over Earth's surface for 3D visualization. However, visualizations of research results in vertical cross-sections are often not shown simultaneously with the maps in Google Earth. A few tutorials and programs to display cross-sectional data in Google Earth do exist, and the workflow is rather simple. By importing a cross-sectional figure into in the open software SketchUp Make [Trimble Navigation Limited, 2016], any spatial model can be exported to a vertical figure in Google Earth. In this presentation a clear workflow/tutorial is presented how to image cross-sections manually in Google Earth. No software skills, nor any programming codes are required. It is very easy to use, offers great possibilities for teaching and allows fast figure manipulation in Google Earth. The full workflow can be found in "Van Noten, K. 2016. Visualizing Cross-Sectional Data in a Real-World Context. EOS, Transactions AGU, 97, 16-19".The video tutorial can be found here: https://www.youtube.com/watch?v=Tr8LwFJ4RYU&Figure: Cross-sectional Research Examples Illustrated in Google Earth

Bridging the Guideline Implementation Gap: A Systematic, Document-Centered Approach to Guideline Implementation

PubMed Central

Shiffman, Richard N.; Michel, George; Essaihi, Abdelwaheb; Thornquist, Elizabeth

2004-01-01

Objective: A gap exists between the information contained in published clinical practice guidelines and the knowledge and information that are necessary to implement them. This work describes a process to systematize and make explicit the translation of document-based knowledge into workflow-integrated clinical decision support systems. Design: This approach uses the Guideline Elements Model (GEM) to represent the guideline knowledge. Implementation requires a number of steps to translate the knowledge contained in guideline text into a computable format and to integrate the information into clinical workflow. The steps include: (1) selection of a guideline and specific recommendations for implementation, (2) markup of the guideline text, (3) atomization, (4) deabstraction and (5) disambiguation of recommendation concepts, (6) verification of rule set completeness, (7) addition of explanations, (8) building executable statements, (9) specification of origins of decision variables and insertions of recommended actions, (10) definition of action types and selection of associated beneficial services, (11) choice of interface components, and (12) creation of requirement specification. Results: The authors illustrate these component processes using examples drawn from recent experience translating recommendations from the National Heart, Lung, and Blood Institute's guideline on management of chronic asthma into a workflow-integrated decision support system that operates within the Logician electronic health record system. Conclusion: Using the guideline document as a knowledge source promotes authentic translation of domain knowledge and reduces the overall complexity of the implementation task. From this framework, we believe that a better understanding of activities involved in guideline implementation will emerge. PMID:15187061

Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms

PubMed Central

Wang, Jianwu; Korambath, Prakashan; Altintas, Ilkay; Davis, Jim; Crawl, Daniel

2017-01-01

With more and more workflow systems adopting cloud as their execution environment, it becomes increasingly challenging on how to efficiently manage various workflows, virtual machines (VMs) and workflow execution on VM instances. To make the system scalable and easy-to-extend, we design a Workflow as a Service (WFaaS) architecture with independent services. A core part of the architecture is how to efficiently respond continuous workflow requests from users and schedule their executions in the cloud. Based on different targets, we propose four heuristic workflow scheduling algorithms for the WFaaS architecture, and analyze the differences and best usages of the algorithms in terms of performance, cost and the price/performance ratio via experimental studies. PMID:29399237

Scientific Data Management (SDM) Center for Enabling Technologies. Final Report, 2007-2012

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

Ludascher, Bertram; Altintas, Ilkay

Our contributions to advancing the State of the Art in scientific workflows have focused on the following areas: Workflow development; Generic workflow components and templates; Provenance collection and analysis; and, Workflow reliability and fault tolerance.

Exploring the impact of an automated prescription-filling device on community pharmacy technician workflow

PubMed Central

Walsh, Kristin E.; Chui, Michelle Anne; Kieser, Mara A.; Williams, Staci M.; Sutter, Susan L.; Sutter, John G.

2012-01-01

Objective To explore community pharmacy technician workflow change after implementation of an automated robotic prescription-filling device. Methods At an independent community pharmacy in rural Mayville, WI, pharmacy technicians were observed before and 3 months after installation of an automated robotic prescription-filling device. The main outcome measures were sequences and timing of technician workflow steps, workflow interruptions, automation surprises, and workarounds. Results Of the 77 and 80 observations made before and 3 months after robot installation, respectively, 17 different workflow sequences were observed before installation and 38 after installation. Average prescription filling time was reduced by 40 seconds per prescription with use of the robot. Workflow interruptions per observation increased from 1.49 to 1.79 (P = 0.11), and workarounds increased from 10% to 36% after robot use. Conclusion Although automated prescription-filling devices can increase efficiency, workflow interruptions and workarounds may negate that efficiency. Assessing changes in workflow and sequencing of tasks that may result from the use of automation can help uncover opportunities for workflow policy and procedure redesign. PMID:21896459

Research and Implementation of Key Technologies in Multi-Agent System to Support Distributed Workflow

NASA Astrophysics Data System (ADS)

Pan, Tianheng

2018-01-01

In recent years, the combination of workflow management system and Multi-agent technology is a hot research field. The problem of lack of flexibility in workflow management system can be improved by introducing multi-agent collaborative management. The workflow management system adopts distributed structure. It solves the problem that the traditional centralized workflow structure is fragile. In this paper, the agent of Distributed workflow management system is divided according to its function. The execution process of each type of agent is analyzed. The key technologies such as process execution and resource management are analyzed.

Progress in digital color workflow understanding in the International Color Consortium (ICC) Workflow WG

NASA Astrophysics Data System (ADS)

McCarthy, Ann

2006-01-01

The ICC Workflow WG serves as the bridge between ICC color management technologies and use of those technologies in real world color production applications. ICC color management is applicable to and is used in a wide range of color systems, from highly specialized digital cinema color special effects to high volume publications printing to home photography. The ICC Workflow WG works to align ICC technologies so that the color management needs of these diverse use case systems are addressed in an open, platform independent manner. This report provides a high level summary of the ICC Workflow WG objectives and work to date, focusing on the ways in which workflow can impact image quality and color systems performance. The 'ICC Workflow Primitives' and 'ICC Workflow Patterns and Dimensions' workflow models are covered in some detail. Consider the questions, "How much of dissatisfaction with color management today is the result of 'the wrong color transformation at the wrong time' and 'I can't get to the right conversion at the right point in my work process'?" Put another way, consider how image quality through a workflow can be negatively affected when the coordination and control level of the color management system is not sufficient.

Towards a Framework for Evaluating Mobile Mental Health Apps.

PubMed

Chan, Steven; Torous, John; Hinton, Ladson; Yellowlees, Peter

2015-12-01

Mobile phones are ubiquitous in society and owned by a majority of psychiatric patients, including those with severe mental illness. Their versatility as a platform can extend mental health services in the areas of communication, self-monitoring, self-management, diagnosis, and treatment. However, the efficacy and reliability of publicly available applications (apps) have yet to be demonstrated. Numerous articles have noted the need for rigorous evaluation of the efficacy and clinical utility of smartphone apps, which are largely unregulated. Professional clinical organizations do not provide guidelines for evaluating mobile apps. Guidelines and frameworks are needed to evaluate medical apps. Numerous frameworks and evaluation criteria exist from the engineering and informatics literature, as well as interdisciplinary organizations in similar fields such as telemedicine and healthcare informatics. We propose criteria for both patients and providers to use in assessing not just smartphone apps, but also wearable devices and smartwatch apps for mental health. Apps can be evaluated by their usefulness, usability, and integration and infrastructure. Apps can be categorized by their usability in one or more stages of a mental health provider's workflow. Ultimately, leadership is needed to develop a framework for describing apps, and guidelines are needed for both patients and mental health providers.

pyBadlands: A framework to simulate sediment transport, landscape dynamics and basin stratigraphic evolution through space and time

PubMed Central

2018-01-01

Understanding Earth surface responses in terms of sediment dynamics to climatic variability and tectonics forcing is hindered by limited ability of current models to simulate long-term evolution of sediment transfer and associated morphological changes. This paper presents pyBadlands, an open-source python-based framework which computes over geological time (1) sediment transport from landmasses to coasts, (2) reworking of marine sediments by longshore currents and (3) development of coral reef systems. pyBadlands is cross-platform, distributed under the GPLv3 license and available on GitHub (http://github.com/badlands-model). Here, we describe the underlying physical assumptions behind the simulated processes and the main options already available in the numerical framework. Along with the source code, a list of hands-on examples is provided that illustrates the model capabilities. In addition, pre and post-processing classes have been built and are accessible as a companion toolbox which comprises a series of workflows to efficiently build, quantify and explore simulation input and output files. While the framework has been primarily designed for research, its simplicity of use and portability makes it a great tool for teaching purposes. PMID:29649301

Introducing concurrency in the Gaudi data processing framework

NASA Astrophysics Data System (ADS)

Clemencic, Marco; Hegner, Benedikt; Mato, Pere; Piparo, Danilo

2014-06-01

In the past, the increasing demands for HEP processing resources could be fulfilled by the ever increasing clock-frequencies and by distributing the work to more and more physical machines. Limitations in power consumption of both CPUs and entire data centres are bringing an end to this era of easy scalability. To get the most CPU performance per watt, future hardware will be characterised by less and less memory per processor, as well as thinner, more specialized and more numerous cores per die, and rather heterogeneous resources. To fully exploit the potential of the many cores, HEP data processing frameworks need to allow for parallel execution of reconstruction or simulation algorithms on several events simultaneously. We describe our experience in introducing concurrency related capabilities into Gaudi, a generic data processing software framework, which is currently being used by several HEP experiments, including the ATLAS and LHCb experiments at the LHC. After a description of the concurrent framework and the most relevant design choices driving its development, we describe the behaviour of the framework in a more realistic environment, using a subset of the real LHCb reconstruction workflow, and present our strategy and the used tools to validate the physics outcome of the parallel framework against the results of the present, purely sequential LHCb software. We then summarize the measurement of the code performance of the multithreaded application in terms of memory and CPU usage.

STTEPping in the Right Direction? Western Classical Music in an Orchestral Programme for Disadvantaged African Youth

ERIC Educational Resources Information Center

van Niekerk, Caroline; Salminen, Sanna

2008-01-01

This article looks at STTEP, an outreach project currently housed at the University of Pretoria, which concentrates on the teaching of western orchestral instruments, plus background areas such as music theory, to disadvantaged children and youth from a variety of townships around Pretoria, South Africa. STTEP's direction can well be described as…

Radiology information system: a workflow-based approach.

PubMed

Zhang, Jinyan; Lu, Xudong; Nie, Hongchao; Huang, Zhengxing; van der Aalst, W M P

2009-09-01

Introducing workflow management technology in healthcare seems to be prospective in dealing with the problem that the current healthcare Information Systems cannot provide sufficient support for the process management, although several challenges still exist. The purpose of this paper is to study the method of developing workflow-based information system in radiology department as a use case. First, a workflow model of typical radiology process was established. Second, based on the model, the system could be designed and implemented as a group of loosely coupled components. Each component corresponded to one task in the process and could be assembled by the workflow management system. The legacy systems could be taken as special components, which also corresponded to the tasks and were integrated through transferring non-work- flow-aware interfaces to the standard ones. Finally, a workflow dashboard was designed and implemented to provide an integral view of radiology processes. The workflow-based Radiology Information System was deployed in the radiology department of Zhejiang Chinese Medicine Hospital in China. The results showed that it could be adjusted flexibly in response to the needs of changing process, and enhance the process management in the department. It can also provide a more workflow-aware integration method, comparing with other methods such as IHE-based ones. The workflow-based approach is a new method of developing radiology information system with more flexibility, more functionalities of process management and more workflow-aware integration. The work of this paper is an initial endeavor for introducing workflow management technology in healthcare.

Information Issues and Contexts that Impair Team Based Communication Workflow: A Palliative Sedation Case Study.

PubMed

Cornett, Alex; Kuziemsky, Craig

2015-01-01

Implementing team based workflows can be complex because of the scope of providers involved and the extent of information exchange and communication that needs to occur. While a workflow may represent the ideal structure of communication that needs to occur, information issues and contextual factors may impact how the workflow is implemented in practice. Understanding these issues will help us better design systems to support team based workflows. In this paper we use a case study of palliative sedation therapy (PST) to model a PST workflow and then use it to identify purposes of communication, information issues and contextual factors that impact them. We then suggest how our findings could inform health information technology (HIT) design to support team based communication workflows.

A Workflow to Improve the Alignment of Prostate Imaging with Whole-mount Histopathology.

PubMed

Yamamoto, Hidekazu; Nir, Dror; Vyas, Lona; Chang, Richard T; Popert, Rick; Cahill, Declan; Challacombe, Ben; Dasgupta, Prokar; Chandra, Ashish

2014-08-01

Evaluation of prostate imaging tests against whole-mount histology specimens requires accurate alignment between radiologic and histologic data sets. Misalignment results in false-positive and -negative zones as assessed by imaging. We describe a workflow for three-dimensional alignment of prostate imaging data against whole-mount prostatectomy reference specimens and assess its performance against a standard workflow. Ethical approval was granted. Patients underwent motorized transrectal ultrasound (Prostate Histoscanning) to generate a three-dimensional image of the prostate before radical prostatectomy. The test workflow incorporated steps for axial alignment between imaging and histology, size adjustments following formalin fixation, and use of custom-made parallel cutters and digital caliper instruments. The control workflow comprised freehand cutting and assumed homogeneous block thicknesses at the same relative angles between pathology and imaging sections. Thirty radical prostatectomy specimens were histologically and radiologically processed, either by an alignment-optimized workflow (n = 20) or a control workflow (n = 10). The optimized workflow generated tissue blocks of heterogeneous thicknesses but with no significant drifting in the cutting plane. The control workflow resulted in significantly nonparallel blocks, accurately matching only one out of four histology blocks to their respective imaging data. The image-to-histology alignment accuracy was 20% greater in the optimized workflow (P < .0001), with higher sensitivity (85% vs. 69%) and specificity (94% vs. 73%) for margin prediction in a 5 × 5-mm grid analysis. A significantly better alignment was observed in the optimized workflow. Evaluation of prostate imaging biomarkers using whole-mount histology references should include a test-to-reference spatial alignment workflow. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Conceptual-level workflow modeling of scientific experiments using NMR as a case study

PubMed Central

Verdi, Kacy K; Ellis, Heidi JC; Gryk, Michael R

2007-01-01

Background Scientific workflows improve the process of scientific experiments by making computations explicit, underscoring data flow, and emphasizing the participation of humans in the process when intuition and human reasoning are required. Workflows for experiments also highlight transitions among experimental phases, allowing intermediate results to be verified and supporting the proper handling of semantic mismatches and different file formats among the various tools used in the scientific process. Thus, scientific workflows are important for the modeling and subsequent capture of bioinformatics-related data. While much research has been conducted on the implementation of scientific workflows, the initial process of actually designing and generating the workflow at the conceptual level has received little consideration. Results We propose a structured process to capture scientific workflows at the conceptual level that allows workflows to be documented efficiently, results in concise models of the workflow and more-correct workflow implementations, and provides insight into the scientific process itself. The approach uses three modeling techniques to model the structural, data flow, and control flow aspects of the workflow. The domain of biomolecular structure determination using Nuclear Magnetic Resonance spectroscopy is used to demonstrate the process. Specifically, we show the application of the approach to capture the workflow for the process of conducting biomolecular analysis using Nuclear Magnetic Resonance (NMR) spectroscopy. Conclusion Using the approach, we were able to accurately document, in a short amount of time, numerous steps in the process of conducting an experiment using NMR spectroscopy. The resulting models are correct and precise, as outside validation of the models identified only minor omissions in the models. In addition, the models provide an accurate visual description of the control flow for conducting biomolecular analysis using NMR spectroscopy experiment. PMID:17263870

Conceptual-level workflow modeling of scientific experiments using NMR as a case study.

PubMed

Verdi, Kacy K; Ellis, Heidi Jc; Gryk, Michael R

2007-01-30

Scientific workflows improve the process of scientific experiments by making computations explicit, underscoring data flow, and emphasizing the participation of humans in the process when intuition and human reasoning are required. Workflows for experiments also highlight transitions among experimental phases, allowing intermediate results to be verified and supporting the proper handling of semantic mismatches and different file formats among the various tools used in the scientific process. Thus, scientific workflows are important for the modeling and subsequent capture of bioinformatics-related data. While much research has been conducted on the implementation of scientific workflows, the initial process of actually designing and generating the workflow at the conceptual level has received little consideration. We propose a structured process to capture scientific workflows at the conceptual level that allows workflows to be documented efficiently, results in concise models of the workflow and more-correct workflow implementations, and provides insight into the scientific process itself. The approach uses three modeling techniques to model the structural, data flow, and control flow aspects of the workflow. The domain of biomolecular structure determination using Nuclear Magnetic Resonance spectroscopy is used to demonstrate the process. Specifically, we show the application of the approach to capture the workflow for the process of conducting biomolecular analysis using Nuclear Magnetic Resonance (NMR) spectroscopy. Using the approach, we were able to accurately document, in a short amount of time, numerous steps in the process of conducting an experiment using NMR spectroscopy. The resulting models are correct and precise, as outside validation of the models identified only minor omissions in the models. In addition, the models provide an accurate visual description of the control flow for conducting biomolecular analysis using NMR spectroscopy experiment.

Bio-jETI: a service integration, design, and provisioning platform for orchestrated bioinformatics processes.

PubMed

Margaria, Tiziana; Kubczak, Christian; Steffen, Bernhard

2008-04-25

With Bio-jETI, we introduce a service platform for interdisciplinary work on biological application domains and illustrate its use in a concrete application concerning statistical data processing in R and xcms for an LC/MS analysis of FAAH gene knockout. Bio-jETI uses the jABC environment for service-oriented modeling and design as a graphical process modeling tool and the jETI service integration technology for remote tool execution. As a service definition and provisioning platform, Bio-jETI has the potential to become a core technology in interdisciplinary service orchestration and technology transfer. Domain experts, like biologists not trained in computer science, directly define complex service orchestrations as process models and use efficient and complex bioinformatics tools in a simple and intuitive way.

The future of scientific workflows

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

Deelman, Ewa; Peterka, Tom; Altintas, Ilkay

Today’s computational, experimental, and observational sciences rely on computations that involve many related tasks. The success of a scientific mission often hinges on the computer automation of these workflows. In April 2015, the US Department of Energy (DOE) invited a diverse group of domain and computer scientists from national laboratories supported by the Office of Science, the National Nuclear Security Administration, from industry, and from academia to review the workflow requirements of DOE’s science and national security missions, to assess the current state of the art in science workflows, to understand the impact of emerging extreme-scale computing systems on thosemore » workflows, and to develop requirements for automated workflow management in future and existing environments. This article is a summary of the opinions of over 50 leading researchers attending this workshop. We highlight use cases, computing systems, workflow needs and conclude by summarizing the remaining challenges this community sees that inhibit large-scale scientific workflows from becoming a mainstream tool for extreme-scale science.« less

Development of a user customizable imaging informatics-based intelligent workflow engine system to enhance rehabilitation clinical trials

NASA Astrophysics Data System (ADS)

Wang, Ximing; Martinez, Clarisa; Wang, Jing; Liu, Ye; Liu, Brent

2014-03-01

Clinical trials usually have a demand to collect, track and analyze multimedia data according to the workflow. Currently, the clinical trial data management requirements are normally addressed with custom-built systems. Challenges occur in the workflow design within different trials. The traditional pre-defined custom-built system is usually limited to a specific clinical trial and normally requires time-consuming and resource-intensive software development. To provide a solution, we present a user customizable imaging informatics-based intelligent workflow engine system for managing stroke rehabilitation clinical trials with intelligent workflow. The intelligent workflow engine provides flexibility in building and tailoring the workflow in various stages of clinical trials. By providing a solution to tailor and automate the workflow, the system will save time and reduce errors for clinical trials. Although our system is designed for clinical trials for rehabilitation, it may be extended to other imaging based clinical trials as well.

The standard-based open workflow system in GeoBrain (Invited)

NASA Astrophysics Data System (ADS)

Di, L.; Yu, G.; Zhao, P.; Deng, M.

2013-12-01

GeoBrain is an Earth science Web-service system developed and operated by the Center for Spatial Information Science and Systems, George Mason University. In GeoBrain, a standard-based open workflow system has been implemented to accommodate the automated processing of geospatial data through a set of complex geo-processing functions for advanced production generation. The GeoBrain models the complex geoprocessing at two levels, the conceptual and concrete. At the conceptual level, the workflows exist in the form of data and service types defined by ontologies. The workflows at conceptual level are called geo-processing models and cataloged in GeoBrain as virtual product types. A conceptual workflow is instantiated into a concrete, executable workflow when a user requests a product that matches a virtual product type. Both conceptual and concrete workflows are encoded in Business Process Execution Language (BPEL). A BPEL workflow engine, called BPELPower, has been implemented to execute the workflow for the product generation. A provenance capturing service has been implemented to generate the ISO 19115-compliant complete product provenance metadata before and after the workflow execution. The generation of provenance metadata before the workflow execution allows users to examine the usability of the final product before the lengthy and expensive execution takes place. The three modes of workflow executions defined in the ISO 19119, transparent, translucent, and opaque, are available in GeoBrain. A geoprocessing modeling portal has been developed to allow domain experts to develop geoprocessing models at the type level with the support of both data and service/processing ontologies. The geoprocessing models capture the knowledge of the domain experts and are become the operational offering of the products after a proper peer review of models is conducted. An automated workflow composition has been experimented successfully based on ontologies and artificial intelligence technology. The GeoBrain workflow system has been used in multiple Earth science applications, including the monitoring of global agricultural drought, the assessment of flood damage, the derivation of national crop condition and progress information, and the detection of nuclear proliferation facilities and events.

Design and implementation of an internet-based electrical engineering laboratory.

PubMed

He, Zhenlei; Shen, Zhangbiao; Zhu, Shanan

2014-09-01

This paper describes an internet-based electrical engineering laboratory (IEE-Lab) with virtual and physical experiments at Zhejiang University. In order to synthesize the advantages of both experiment styles, the IEE-Lab is come up with Client/Server/Application framework and combines the virtual and physical experiments. The design and workflow of IEE-Lab are introduced. The analog electronic experiment is taken as an example to show Flex plug-in design, data communication based on XML (Extensible Markup Language), experiment simulation modeled by Modelica and control terminals' design. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Diabetes Information Technology: Designing Informatics Systems to Catalyze Change in Clinical Care

PubMed Central

Lester, William T.; Zai, Adrian H.; Chueh, Henry C.; Grant, Richard W.

2008-01-01

Current computerized reminder and decision support systems intended to improve diabetes care have had a limited effect on clinical outcomes. Increasing pressures on health care networks to meet standards of diabetes care have created an environment where information technology systems for diabetes management are often created under duress, appended to existing clinical systems, and poorly integrated into the existing workflow. After defining the components of diabetes disease management, the authors present an eight-step conceptual framework to guide the development of more effective diabetes information technology systems for translating clinical information into clinical action. PMID:19885355

The Application of Wearable Technology in Surgery: Ensuring the Positive Impact of the Wearable Revolution on Surgical Patients

PubMed Central

Slade Shantz, Jesse Alan; Veillette, Christian J. H.

2014-01-01

Wearable technology has become an important trend in consumer electronics in the past year. The miniaturization and mass production of myriad sensors have made possible the integration of sensors and output devices in wearable platforms. Despite the consumer focus of the wearable revolution some surgical applications are being developed. These fall into augmentative, assistive, and assessment functions and primarily layer onto current surgical workflows. Some challenges to the adoption of wearable technologies are discussed and a conceptual framework for understanding the potential of wearable technology to revolutionize surgical practice are presented. PMID:25593963

A UIMA wrapper for the NCBO annotator.

PubMed

Roeder, Christophe; Jonquet, Clement; Shah, Nigam H; Baumgartner, William A; Verspoor, Karin; Hunter, Lawrence

2010-07-15

The Unstructured Information Management Architecture (UIMA) framework and web services are emerging as useful tools for integrating biomedical text mining tools. This note describes our work, which wraps the National Center for Biomedical Ontology (NCBO) Annotator-an ontology-based annotation service-to make it available as a component in UIMA workflows. This wrapper is freely available on the web at http://bionlp-uima.sourceforge.net/ as part of the UIMA tools distribution from the Center for Computational Pharmacology (CCP) at the University of Colorado School of Medicine. It has been implemented in Java for support on Mac OS X, Linux and MS Windows.

A characterization of workflow management systems for extreme-scale applications

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

Ferreira da Silva, Rafael; Filgueira, Rosa; Pietri, Ilia

We present that the automation of the execution of computational tasks is at the heart of improving scientific productivity. Over the last years, scientific workflows have been established as an important abstraction that captures data processing and computation of large and complex scientific applications. By allowing scientists to model and express entire data processing steps and their dependencies, workflow management systems relieve scientists from the details of an application and manage its execution on a computational infrastructure. As the resource requirements of today’s computational and data science applications that process vast amounts of data keep increasing, there is a compellingmore » case for a new generation of advances in high-performance computing, commonly termed as extreme-scale computing, which will bring forth multiple challenges for the design of workflow applications and management systems. This paper presents a novel characterization of workflow management systems using features commonly associated with extreme-scale computing applications. We classify 15 popular workflow management systems in terms of workflow execution models, heterogeneous computing environments, and data access methods. Finally, the paper also surveys workflow applications and identifies gaps for future research on the road to extreme-scale workflows and management systems.« less

A characterization of workflow management systems for extreme-scale applications

DOE PAGES

Ferreira da Silva, Rafael; Filgueira, Rosa; Pietri, Ilia; ...

2017-02-16

We present that the automation of the execution of computational tasks is at the heart of improving scientific productivity. Over the last years, scientific workflows have been established as an important abstraction that captures data processing and computation of large and complex scientific applications. By allowing scientists to model and express entire data processing steps and their dependencies, workflow management systems relieve scientists from the details of an application and manage its execution on a computational infrastructure. As the resource requirements of today’s computational and data science applications that process vast amounts of data keep increasing, there is a compellingmore » case for a new generation of advances in high-performance computing, commonly termed as extreme-scale computing, which will bring forth multiple challenges for the design of workflow applications and management systems. This paper presents a novel characterization of workflow management systems using features commonly associated with extreme-scale computing applications. We classify 15 popular workflow management systems in terms of workflow execution models, heterogeneous computing environments, and data access methods. Finally, the paper also surveys workflow applications and identifies gaps for future research on the road to extreme-scale workflows and management systems.« less

Scheduling Multilevel Deadline-Constrained Scientific Workflows on Clouds Based on Cost Optimization

DOE PAGES

Malawski, Maciej; Figiela, Kamil; Bubak, Marian; ...

2015-01-01

This paper presents a cost optimization model for scheduling scientific workflows on IaaS clouds such as Amazon EC2 or RackSpace. We assume multiple IaaS clouds with heterogeneous virtual machine instances, with limited number of instances per cloud and hourly billing. Input and output data are stored on a cloud object store such as Amazon S3. Applications are scientific workflows modeled as DAGs as in the Pegasus Workflow Management System. We assume that tasks in the workflows are grouped into levels of identical tasks. Our model is specified using mathematical programming languages (AMPL and CMPL) and allows us to minimize themore » cost of workflow execution under deadline constraints. We present results obtained using our model and the benchmark workflows representing real scientific applications in a variety of domains. The data used for evaluation come from the synthetic workflows and from general purpose cloud benchmarks, as well as from the data measured in our own experiments with Montage, an astronomical application, executed on Amazon EC2 cloud. We indicate how this model can be used for scenarios that require resource planning for scientific workflows and their ensembles.« less

Observing health professionals' workflow patterns for diabetes care - First steps towards an ontology for EHR services.

PubMed

Schweitzer, M; Lasierra, N; Hoerbst, A

2015-01-01

Increasing the flexibility from a user-perspective and enabling a workflow based interaction, facilitates an easy user-friendly utilization of EHRs for healthcare professionals' daily work. To offer such versatile EHR-functionality, our approach is based on the execution of clinical workflows by means of a composition of semantic web-services. The backbone of such architecture is an ontology which enables to represent clinical workflows and facilitates the selection of suitable services. In this paper we present the methods and results after running observations of diabetes routine consultations which were conducted in order to identify those workflows and the relation among the included tasks. Mentioned workflows were first modeled by BPMN and then generalized. As a following step in our study, interviews will be conducted with clinical personnel to validate modeled workflows.

A framework for the correction of slow physiological drifts during MR-guided HIFU therapies: Proof of concept.

PubMed

Zachiu, Cornel; Denis de Senneville, Baudouin; Moonen, Chrit; Ries, Mario

2015-07-01

While respiratory motion compensation for magnetic resonance (MR)-guided high intensity focused ultrasound (HIFU) interventions has been extensively studied, the influence of slow physiological motion due to, for example, peristaltic activity, has so far been largely neglected. During lengthy interventions, the magnitude of the latter can exceed acceptable therapeutic margins. The goal of the present study is to exploit the episodic workflow of these therapies to implement a motion correction strategy for slow varying drifts of the target area and organs at risk over the entire duration of the intervention. The therapeutic workflow of a MR-guided HIFU intervention is in practice often episodic: Bursts of energy delivery are interleaved with periods of inactivity, allowing the effects of the beam on healthy tissues to recede and/or during which the plan of the intervention is reoptimized. These periods usually last for at least several minutes. It is at this time scale that organ drifts due to slow physiological motion become significant. In order to capture these drifts, the authors propose the integration of 3D MR scans in the therapy workflow during the inactivity intervals. Displacements were estimated using an optical flow algorithm applied on the 3D acquired images. A preliminary study was conducted on ten healthy volunteers. For each volunteer, 3D MR images of the abdomen were acquired at regular intervals of 10 min over a total duration of 80 min. Motion analysis was restricted to the liver and kidneys. For validating the compatibility of the proposed motion correction strategy with the workflow of a MR-guided HIFU therapy, an in vivo experiment on a porcine liver was conducted. A volumetric HIFU ablation was completed over a time span of 2 h. A 3D image was acquired before the first sonication, as well as after each sonication. Following the volunteer study, drifts larger than 8 mm for the liver and 5 mm for the kidneys prove that slow physiological motion can exceed acceptable therapeutic margins. In the animal experiment, motion tracking revealed an initial shift of up to 4 mm during the first 10 min and a subsequent continuous shift of ∼2 mm/h until the end of the intervention. This leads to a continuously increasing mismatch of the initial shot planning, the thermal dose measurements, and the true underlying anatomy. The estimated displacements allowed correcting the planned sonication cell cluster positions to the true target position, as well as the thermal dose estimates during the entire intervention and to correct the nonperfused volume measurement. A spatial coherence of all three is particularly important to assure a confluent ablation volume and to prevent remaining islets of viable malignant tissue. This study proposes a motion correction strategy for displacements resulting from slowly varying physiological motion that might occur during a MR-guided HIFU intervention. The authors have shown that such drifts can lead to a misalignment between interventional planning, energy delivery, and therapeutic validation. The presented volunteer study and in vivo experiment demonstrate both the relevance of the problem for HIFU therapies and the compatibility of the proposed motion compensation framework with the workflow of a HIFU intervention under clinical conditions.

A framework for the correction of slow physiological drifts during MR-guided HIFU therapies: Proof of concept

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

Zachiu, Cornel, E-mail: C.Zachiu@umcutrecht.nl; Moonen, Chrit; Ries, Mario

Purpose: While respiratory motion compensation for magnetic resonance (MR)-guided high intensity focused ultrasound (HIFU) interventions has been extensively studied, the influence of slow physiological motion due to, for example, peristaltic activity, has so far been largely neglected. During lengthy interventions, the magnitude of the latter can exceed acceptable therapeutic margins. The goal of the present study is to exploit the episodic workflow of these therapies to implement a motion correction strategy for slow varying drifts of the target area and organs at risk over the entire duration of the intervention. Methods: The therapeutic workflow of a MR-guided HIFU intervention ismore » in practice often episodic: Bursts of energy delivery are interleaved with periods of inactivity, allowing the effects of the beam on healthy tissues to recede and/or during which the plan of the intervention is reoptimized. These periods usually last for at least several minutes. It is at this time scale that organ drifts due to slow physiological motion become significant. In order to capture these drifts, the authors propose the integration of 3D MR scans in the therapy workflow during the inactivity intervals. Displacements were estimated using an optical flow algorithm applied on the 3D acquired images. A preliminary study was conducted on ten healthy volunteers. For each volunteer, 3D MR images of the abdomen were acquired at regular intervals of 10 min over a total duration of 80 min. Motion analysis was restricted to the liver and kidneys. For validating the compatibility of the proposed motion correction strategy with the workflow of a MR-guided HIFU therapy, an in vivo experiment on a porcine liver was conducted. A volumetric HIFU ablation was completed over a time span of 2 h. A 3D image was acquired before the first sonication, as well as after each sonication. Results: Following the volunteer study, drifts larger than 8 mm for the liver and 5 mm for the kidneys prove that slow physiological motion can exceed acceptable therapeutic margins. In the animal experiment, motion tracking revealed an initial shift of up to 4 mm during the first 10 min and a subsequent continuous shift of ∼2 mm/h until the end of the intervention. This leads to a continuously increasing mismatch of the initial shot planning, the thermal dose measurements, and the true underlying anatomy. The estimated displacements allowed correcting the planned sonication cell cluster positions to the true target position, as well as the thermal dose estimates during the entire intervention and to correct the nonperfused volume measurement. A spatial coherence of all three is particularly important to assure a confluent ablation volume and to prevent remaining islets of viable malignant tissue. Conclusions: This study proposes a motion correction strategy for displacements resulting from slowly varying physiological motion that might occur during a MR-guided HIFU intervention. The authors have shown that such drifts can lead to a misalignment between interventional planning, energy delivery, and therapeutic validation. The presented volunteer study and in vivo experiment demonstrate both the relevance of the problem for HIFU therapies and the compatibility of the proposed motion compensation framework with the workflow of a HIFU intervention under clinical conditions.« less

Interactive Whiteboards and All that Jazz: The Contribution of Musical Metaphors to the Analysis of Classroom Activity with Interactive Technologies

ERIC Educational Resources Information Center

Beauchamp, Gary; Kennewell, Steve; Tanner, Howard; Jones, Sonia

2010-01-01

The teacher's role has often been described as one of "orchestration", and this musical analogy is a powerful one in characterising the manipulation of features in the classroom setting in order to generate activity or "performance" which leads to learning. However, a classical view of orchestration would fail to recognise the extent to which…

Orchestrating BMD Control in Extended BPEL

DTIC Science & Technology

2008-05-21

Orchestration of secure WebMail , Technical Report ISE-TR-06-08, George Mason University, Fairfax, VA, August 2006. [9] E. Christensen, F. Curbera...methods to access and dissemination control, securing circuit switched (SS7) and IP based telecommunication (VoIP) systems, multimedia, security ...decorating the Business Process Execution Language (BPEL) with Quality of Service (QoS), Measures of Performance (MoP), Measures of Effectiveness (MoE

A Framework for Daylighting Optimization in Whole Buildings with OpenStudio

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

None

2016-08-12

We present a toolkit and workflow for leveraging the OpenStudio (Guglielmetti et al. 2010) platform to perform daylighting analysis and optimization in a whole building energy modeling (BEM) context. We have re-implemented OpenStudio's integrated Radiance and EnergyPlus functionality as an OpenStudio Measure. The OpenStudio Radiance Measure works within the OpenStudio Application and Parametric Analysis Tool, as well as the OpenStudio Server large scale analysis framework, allowing a rigorous daylighting simulation to be performed on a single building model or potentially an entire population of programmatically generated models. The Radiance simulation results can automatically inform the broader building energy model, andmore » provide dynamic daylight metrics as a basis for decision. Through introduction and example, this paper illustrates the utility of the OpenStudio building energy modeling platform to leverage existing simulation tools for integrated building energy performance simulation, daylighting analysis, and reportage.« less

A Crowdsourcing Framework for Medical Data Sets.

PubMed

Ye, Cheng; Coco, Joseph; Epishova, Anna; Hajaj, Chen; Bogardus, Henry; Novak, Laurie; Denny, Joshua; Vorobeychik, Yevgeniy; Lasko, Thomas; Malin, Bradley; Fabbri, Daniel

2018-01-01

Crowdsourcing services like Amazon Mechanical Turk allow researchers to ask questions to crowds of workers and quickly receive high quality labeled responses. However, crowds drawn from the general public are not suitable for labeling sensitive and complex data sets, such as medical records, due to various concerns. Major challenges in building and deploying a crowdsourcing system for medical data include, but are not limited to: managing access rights to sensitive data and ensuring data privacy controls are enforced; identifying workers with the necessary expertise to analyze complex information; and efficiently retrieving relevant information in massive data sets. In this paper, we introduce a crowdsourcing framework to support the annotation of medical data sets. We further demonstrate a workflow for crowdsourcing clinical chart reviews including (1) the design and decomposition of research questions; (2) the architecture for storing and displaying sensitive data; and (3) the development of tools to support crowd workers in quickly analyzing information from complex data sets.

Meeting report: advancing practical applications of biodiversity ontologies

PubMed Central

2014-01-01

We describe the outcomes of three recent workshops aimed at advancing development of the Biological Collections Ontology (BCO), the Population and Community Ontology (PCO), and tools to annotate data using those and other ontologies. The first workshop gathered use cases to help grow the PCO, agreed upon a format for modeling challenging concepts such as ecological niche, and developed ontology design patterns for defining collections of organisms and population-level phenotypes. The second focused on mapping datasets to ontology terms and converting them to Resource Description Framework (RDF), using the BCO. To follow-up, a BCO hackathon was held concurrently with the 16th Genomics Standards Consortium Meeting, during which we converted additional datasets to RDF, developed a Material Sample Core for the Global Biodiversity Information Framework, created a Web Ontology Language (OWL) file for importing Darwin Core classes and properties into BCO, and developed a workflow for converting biodiversity data among formats.

Climbing the ladder: capability maturity model integration level 3

NASA Astrophysics Data System (ADS)

Day, Bryce; Lutteroth, Christof

2011-02-01

This article details the attempt to form a complete workflow model for an information and communication technologies (ICT) company in order to achieve a capability maturity model integration (CMMI) maturity rating of 3. During this project, business processes across the company's core and auxiliary sectors were documented and extended using modern enterprise modelling tools and a The Open Group Architectural Framework (TOGAF) methodology. Different challenges were encountered with regard to process customisation and tool support for enterprise modelling. In particular, there were problems with the reuse of process models, the integration of different project management methodologies and the integration of the Rational Unified Process development process framework that had to be solved. We report on these challenges and the perceived effects of the project on the company. Finally, we point out research directions that could help to improve the situation in the future.

Integrated, systems metabolic picture of acetone-butanol-ethanol fermentation by Clostridium acetobutylicum.

PubMed

Liao, Chen; Seo, Seung-Oh; Celik, Venhar; Liu, Huaiwei; Kong, Wentao; Wang, Yi; Blaschek, Hans; Jin, Yong-Su; Lu, Ting

2015-07-07

Microbial metabolism involves complex, system-level processes implemented via the orchestration of metabolic reactions, gene regulation, and environmental cues. One canonical example of such processes is acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum, during which cells convert carbon sources to organic acids that are later reassimilated to produce solvents as a strategy for cellular survival. The complexity and systems nature of the process have been largely underappreciated, rendering challenges in understanding and optimizing solvent production. Here, we present a system-level computational framework for ABE fermentation that combines metabolic reactions, gene regulation, and environmental cues. We developed the framework by decomposing the entire system into three modules, building each module separately, and then assembling them back into an integrated system. During the model construction, a bottom-up approach was used to link molecular events at the single-cell level into the events at the population level. The integrated model was able to successfully reproduce ABE fermentations of the WT C. acetobutylicum (ATCC 824), as well as its mutants, using data obtained from our own experiments and from literature. Furthermore, the model confers successful predictions of the fermentations with various network perturbations across metabolic, genetic, and environmental aspects. From foundation to applications, the framework advances our understanding of complex clostridial metabolism and physiology and also facilitates the development of systems engineering strategies for the production of advanced biofuels.

Integrated, systems metabolic picture of acetone-butanol-ethanol fermentation by Clostridium acetobutylicum

PubMed Central

Liao, Chen; Seo, Seung-Oh; Celik, Venhar; Liu, Huaiwei; Kong, Wentao; Wang, Yi; Blaschek, Hans; Jin, Yong-Su; Lu, Ting

2015-01-01

Microbial metabolism involves complex, system-level processes implemented via the orchestration of metabolic reactions, gene regulation, and environmental cues. One canonical example of such processes is acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum, during which cells convert carbon sources to organic acids that are later reassimilated to produce solvents as a strategy for cellular survival. The complexity and systems nature of the process have been largely underappreciated, rendering challenges in understanding and optimizing solvent production. Here, we present a system-level computational framework for ABE fermentation that combines metabolic reactions, gene regulation, and environmental cues. We developed the framework by decomposing the entire system into three modules, building each module separately, and then assembling them back into an integrated system. During the model construction, a bottom-up approach was used to link molecular events at the single-cell level into the events at the population level. The integrated model was able to successfully reproduce ABE fermentations of the WT C. acetobutylicum (ATCC 824), as well as its mutants, using data obtained from our own experiments and from literature. Furthermore, the model confers successful predictions of the fermentations with various network perturbations across metabolic, genetic, and environmental aspects. From foundation to applications, the framework advances our understanding of complex clostridial metabolism and physiology and also facilitates the development of systems engineering strategies for the production of advanced biofuels. PMID:26100881

A service-based framework for pharmacogenomics data integration

NASA Astrophysics Data System (ADS)

Wang, Kun; Bai, Xiaoying; Li, Jing; Ding, Cong

2010-08-01

Data are central to scientific research and practices. The advance of experiment methods and information retrieval technologies leads to explosive growth of scientific data and databases. However, due to the heterogeneous problems in data formats, structures and semantics, it is hard to integrate the diversified data that grow explosively and analyse them comprehensively. As more and more public databases are accessible through standard protocols like programmable interfaces and Web portals, Web-based data integration becomes a major trend to manage and synthesise data that are stored in distributed locations. Mashup, a Web 2.0 technique, presents a new way to compose content and software from multiple resources. The paper proposes a layered framework for integrating pharmacogenomics data in a service-oriented approach using the mashup technology. The framework separates the integration concerns from three perspectives including data, process and Web-based user interface. Each layer encapsulates the heterogeneous issues of one aspect. To facilitate the mapping and convergence of data, the ontology mechanism is introduced to provide consistent conceptual models across different databases and experiment platforms. To support user-interactive and iterative service orchestration, a context model is defined to capture information of users, tasks and services, which can be used for service selection and recommendation during a dynamic service composition process. A prototype system is implemented and cases studies are presented to illustrate the promising capabilities of the proposed approach.

LHCbDIRAC as Apache Mesos microservices

NASA Astrophysics Data System (ADS)

Haen, Christophe; Couturier, Benjamin

2017-10-01

The LHCb experiment relies on LHCbDIRAC, an extension of DIRAC, to drive its offline computing. This middleware provides a development framework and a complete set of components for building distributed computing systems. These components are currently installed and run on virtual machines (VM) or bare metal hardware. Due to the increased workload, high availability is becoming more and more important for the LHCbDIRAC services, and the current installation model is showing its limitations. Apache Mesos is a cluster manager which aims at abstracting heterogeneous physical resources on which various tasks can be distributed thanks to so called “frameworks” The Marathon framework is suitable for long running tasks such as the DIRAC services, while the Chronos framework meets the needs of cron-like tasks like the DIRAC agents. A combination of the service discovery tool Consul together with HAProxy allows to expose the running containers to the outside world while hiding their dynamic placements. Such an architecture brings a greater flexibility in the deployment of LHCbDirac services, allowing for easier deployment maintenance and scaling of services on demand (e..g LHCbDirac relies on 138 services and 116 agents). Higher reliability is also easier, as clustering is part of the toolset, which allows constraints on the location of the services. This paper describes the investigations carried out to package the LHCbDIRAC and DIRAC components into Docker containers and orchestrate them using the previously described set of tools.

Models of chromatin spatial organisation in the cell nucleus

NASA Astrophysics Data System (ADS)

Nicodemi, Mario

2014-03-01

In the cell nucleus chromosomes have a complex architecture serving vital functional purposes. Recent experiments have started unveiling the interaction map of DNA sites genome-wide, revealing different levels of organisation at different scales. The principles, though, which orchestrate such a complex 3D structure remain still mysterious. I will overview the scenario emerging from some classical polymer physics models of the general aspect of chromatin spatial organisation. The available experimental data, which can be rationalised in a single framework, support a picture where chromatin is a complex mixture of differently folded regions, self-organised across spatial scales according to basic physical mechanisms. I will also discuss applications to specific DNA loci, e.g. the HoxB locus, where models informed with biological details, and tested against targeted experiments, can help identifying the determinants of folding.

GeNeDA: An Open-Source Workflow for Design Automation of Gene Regulatory Networks Inspired from Microelectronics.

PubMed

Madec, Morgan; Pecheux, François; Gendrault, Yves; Rosati, Elise; Lallement, Christophe; Haiech, Jacques

2016-10-01

The topic of this article is the development of an open-source automated design framework for synthetic biology, specifically for the design of artificial gene regulatory networks based on a digital approach. In opposition to other tools, GeNeDA is an open-source online software based on existing tools used in microelectronics that have proven their efficiency over the last 30 years. The complete framework is composed of a computation core directly adapted from an Electronic Design Automation tool, input and output interfaces, a library of elementary parts that can be achieved with gene regulatory networks, and an interface with an electrical circuit simulator. Each of these modules is an extension of microelectronics tools and concepts: ODIN II, ABC, the Verilog language, SPICE simulator, and SystemC-AMS. GeNeDA is first validated on a benchmark of several combinatorial circuits. The results highlight the importance of the part library. Then, this framework is used for the design of a sequential circuit including a biological state machine.

Attending unintended transformations of health care infrastructure

PubMed Central

Wentzer, Helle; Bygholm, Ann

2007-01-01

Introduction Western health care is under pressure from growing demands on quality and efficiency. The development and implementation of information technology, IT is a key mean of health care authorities to improve on health care infrastructure. Theory and methods Against a background of theories on human-computer interaction and IT-mediated communication, different empirical studies of IT implementation in health care are analyzed. The outcome is an analytical discernment between different relations of communication and levels of interaction with IT in health care infrastructure. These relations and levels are synthesized into a framework for identifying tensions and potential problems in the mediation of health care with the IT system. These problems are also known as unexpected adverse consequences, UACs, from IT implementation into clinical health care practices. Results This paper develops a conceptual framework for addressing transformations of communication and workflow in health care as a result of implementing IT. Conclusion and discussion The purpose of the conceptual framework is to support the attention to and continuous screening for errors and unintended consequences of IT implementation into health care practices and outcomes. PMID:18043725

Design and implementation of workflow engine for service-oriented architecture

NASA Astrophysics Data System (ADS)

Peng, Shuqing; Duan, Huining; Chen, Deyun

2009-04-01

As computer network is developed rapidly and in the situation of the appearance of distribution specialty in enterprise application, traditional workflow engine have some deficiencies, such as complex structure, bad stability, poor portability, little reusability and difficult maintenance. In this paper, in order to improve the stability, scalability and flexibility of workflow management system, a four-layer architecture structure of workflow engine based on SOA is put forward according to the XPDL standard of Workflow Management Coalition, the route control mechanism in control model is accomplished and the scheduling strategy of cyclic routing and acyclic routing is designed, and the workflow engine which adopts the technology such as XML, JSP, EJB and so on is implemented.

A three-level atomicity model for decentralized workflow management systems

NASA Astrophysics Data System (ADS)

Ben-Shaul, Israel Z.; Heineman, George T.

1996-12-01

A workflow management system (WFMS) employs a workflow manager (WM) to execute and automate the various activities within a workflow. To protect the consistency of data, the WM encapsulates each activity with a transaction; a transaction manager (TM) then guarantees the atomicity of activities. Since workflows often group several activities together, the TM is responsible for guaranteeing the atomicity of these units. There are scalability issues, however, with centralized WFMSs. Decentralized WFMSs provide an architecture for multiple autonomous WFMSs to interoperate, thus accommodating multiple workflows and geographically-dispersed teams. When atomic units are composed of activities spread across multiple WFMSs, however, there is a conflict between global atomicity and local autonomy of each WFMS. This paper describes a decentralized atomicity model that enables workflow administrators to specify the scope of multi-site atomicity based upon the desired semantics of multi-site tasks in the decentralized WFMS. We describe an architecture that realizes our model and execution paradigm.

Updates in metabolomics tools and resources: 2014-2015.

PubMed

Misra, Biswapriya B; van der Hooft, Justin J J

2016-01-01

Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platforms (MS or NMR spectroscopy based) used for data acquisition. Improved machinery in metabolomics generates increasingly complex datasets that create the need for more and better processing and analysis software and in silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources--in the form of tools, software, and databases--is currently lacking. Thus, here we provide an overview of freely-available, and open-source, tools, algorithms, and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR-based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Data-driven discovery of new Dirac semimetal materials

NASA Astrophysics Data System (ADS)

Yan, Qimin; Chen, Ru; Neaton, Jeffrey

In recent years, a significant amount of materials property data from high-throughput computations based on density functional theory (DFT) and the application of database technologies have enabled the rise of data-driven materials discovery. In this work, we initiate the extension of the data-driven materials discovery framework to the realm of topological semimetal materials and to accelerate the discovery of novel Dirac semimetals. We implement current available and develop new workflows to data-mine the Materials Project database for novel Dirac semimetals with desirable band structures and symmetry protected topological properties. This data-driven effort relies on the successful development of several automatic data generation and analysis tools, including a workflow for the automatic identification of topological invariants and pattern recognition techniques to find specific features in a massive number of computed band structures. Utilizing this approach, we successfully identified more than 15 novel Dirac point and Dirac nodal line systems that have not been theoretically predicted or experimentally identified. This work is supported by the Materials Project Predictive Modeling Center through the U.S. Department of Energy, Office of Basic Energy Sciences, Materials Sciences and Engineering Division, under Contract No. DE-AC02-05CH11231.