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Enabling collaborative research using the Biomedical Informatics Research Network (BIRN)
Authors:Karl G Helmer  Jose Luis Ambite  Joseph Ames  Rachana Ananthakrishnan  Gully Burns  Ann L Chervenak  Ian Foster  Lee Liming  David Keator  Fabio Macciardi  Ravi Madduri  John-Paul Navarro  Steven Potkin  Bruce Rosen  Seth Ruffins  Robert Schuler  Jessica A Turner  Arthur Toga  Christina Williams  Carl Kesselman  for the Biomedical Informatics Research Network
Abstract:

Objective

As biomedical technology becomes increasingly sophisticated, researchers can probe ever more subtle effects with the added requirement that the investigation of small effects often requires the acquisition of large amounts of data. In biomedicine, these data are often acquired at, and later shared between, multiple sites. There are both technological and sociological hurdles to be overcome for data to be passed between researchers and later made accessible to the larger scientific community. The goal of the Biomedical Informatics Research Network (BIRN) is to address the challenges inherent in biomedical data sharing.

Materials and methods

BIRN tools are grouped into ‘capabilities’ and are available in the areas of data management, data security, information integration, and knowledge engineering. BIRN has a user-driven focus and employs a layered architectural approach that promotes reuse of infrastructure. BIRN tools are designed to be modular and therefore can work with pre-existing tools. BIRN users can choose the capabilities most useful for their application, while not having to ensure that their project conforms to a monolithic architecture.

Results

BIRN has implemented a new software-based data-sharing infrastructure that has been put to use in many different domains within biomedicine. BIRN is actively involved in outreach to the broader biomedical community to form working partnerships.

Conclusion

BIRN''s mission is to provide capabilities and services related to data sharing to the biomedical research community. It does this by forming partnerships and solving specific, user-driven problems whose solutions are then available for use by other groups.
Keywords:Genomics  statistical genetics  bioinformatics  complex traits  data  machine learning  data sharing  information integration  data mediation  data security  data management  knowledge engineering
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