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caGrid 1.0: An Enterprise Grid Infrastructure for Biomedical Research

^a Department of Biomedical Informatics, The Ohio State University, Columbus, OH
^b Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL
^c National Cancer Institute Center for Bioinformatics, Rockville, MD
^d SemanticBits, Reston, VA.

^_* Correspondence and reprints: Tahsin Kurc, Biomedical Informatics Department, Ohio State University, 3184 Graves Hall, 333 West 10th Ave, Columbus, OH, 43210 (Email: kurc{at}bmi.osu.edu).

Received for publication: 05/30/07; accepted for publication: 12/07/07.

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^TM) 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.