government, and commercial software, pharmaceutical, and biotechnology companies from the United States and in 15+ countries around the globe. In support of the development of a Rapid Learning Health System, the caBIG® participation includes both academic and community cancer centers.

The caBIG® program is organized into workspaces focused on specific domains such as medical imaging, IT architecture, and clinical trials. Subject matter experts and developers within each workspace use virtual conferences and regular face-to-face meetings to work collaboratively on domain-specific issues and projects. The entire caBIG® community meets once per year for the Annual Meeting, whose growth in size and scope year-over-year has mirrored that of the caBIG® program. More than 1,100 individuals representing more than 300 organizations and 13 countries attended the 2009 meeting, held in Washington, DC, where participants celebrated the first 5 years of the caBIG® program by planning new applications and research uses.

While the caBIG® community is highly diverse, its members have similar needs for data management and analysis.

Through participation in the caBIG® program, they are able to access the informatics infrastructure required to work productively, advancing the knowledge of the underlying causes of disease and providing improved patient outcomes.


From a technology perspective, caBIG® is centered on four key principles:

  • Open development—Planning, testing, validation, and deployment of caBIG® tools and infrastructure are open to the entire research community, and contributions from many organizations ensure applicability to a wide range of common research problems.
  • Open access—caBIG® is open to all individuals and organizations interested in solving their data management and connectivity challenges, thus ensuring widespread access to tools, data, and infrastructure.
  • Open source—The underlying software code of caBIG® tools is freely available for use and modification by any organization, public or private, thus encouraging commercial partnerships.
  • Federation—Data and analytical resources can be controlled locally or integrated across multiple sites. Control of secure access to those resources is retained by the originating organization. This federated approach obviates the need for a central authority and reduces data management overhead.

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