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caGrid 1.0: An Enterprise Grid Infrastructure for Biomedical Research

  • Scott Oster
  • , Stephen Langella
  • , Shannon Hastings
  • , David Ervin
  • , Ravi Madduri
  • , Joshua Phillips
  • , Tahsin Kurc
  • , Frank Siebenlist
  • , Peter Covitz
  • , Krishnakant Shanbhag
  • , Ian Foster
  • , Joel Saltz
  • Ohio State University
  • Argonne National Laboratory
  • SemanticBits
  • National Institutes of Health

Research output: Contribution to journalArticlepeer-review

89 Scopus citations

Abstract

Objective: To develop software infrastructure that will provide support for discovery, characterization, integrated access, and management of diverse and disparate collections of information sources, analysis methods, and applications in biomedical research. Design: An enterprise Grid software infrastructure, called caGrid version 1.0 (caGrid 1.0), has been developed as the core Grid architecture of the NCI-sponsored cancer Biomedical Informatics Grid (caBIG) program. It is designed to support a wide range of use cases in basic, translational, and clinical research, including 1) discovery, 2) integrated and large-scale data analysis, and 3) coordinated study. Measurements: The caGrid is built as a Grid software infrastructure and leverages Grid computing technologies and the Web Services Resource Framework standards. It provides a set of core services, toolkits for the development and deployment of new community provided services, and application programming interfaces for building client applications. Results: The caGrid 1.0 was released to the caBIG community in December 2006. It is built on open source components and caGrid source code is publicly and freely available under a liberal open source license. The core software, associated tools, and documentation can be downloaded from the following URL: https://cabig.nci.nih.gov/workspaces/Architecture/caGrid. Conclusions: While caGrid 1.0 is designed to address use cases in cancer research, the requirements associated with discovery, analysis and integration of large scale data, and coordinated studies are common in other biomedical fields. In this respect, caGrid 1.0 is the realization of a framework that can benefit the entire biomedical community.

Original languageEnglish
Pages (from-to)138-149
Number of pages12
JournalJournal of the American Medical Informatics Association
Volume15
Issue number2
DOIs
StatePublished - Mar 2008

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