Administrative Supplements Available to Strengthen NIH-Funded Biomedical Data Repositories

The National Institutes of Health’s (NIH) Office of Data Science Strategy (ODSS) recently announced a Notice of Special Interest (NOSI) to strengthen NIH-funded biomedical data repositories to better enable data discoverability, interoperability, and reuse by aligning with the FAIR and TRUST principles and using metrics to measure their effectiveness (NOT-OD-21-089). The intent is to provide an opportunity for existing repositories of all sizes, and at different stages of establishment, to increase “FAIR”-ness and “TRUST”-worthiness to improve their usage, utility, and impact throughout the data resource lifecycle.

NIH funds a range of biomedical data repositories that differ in size, complexity, and the research domains they serve. Biomedical repositories accept submission of relevant data from the community to store, organize, validate, archive, preserve, and distribute data, in compliance with the FAIR data principles. There is also a spectrum of ability and readiness for data repositories to adopt the characteristics that are desirable for repositories that are aligned with FAIR and TRUST principles. In addition, developing metrics for evaluating the usage, utility, and impact of a given repository is evolving. This evolution is likely a function of several aspects, including, but not limited to the level of maturity, expanding resource reach and scale, and understanding whether user needs have changed.

This initiative is part of a plan for implementing the NIH Strategic Plan for Data Science, which describes actions aimed at modernizing the biomedical research data ecosystem. This effort supports the NIH Policy for Data Management and Sharing: Selecting a Repository for Data Resulting from NIH-Supported Research (NOT-OD-21-016) to better position NIH repositories for the updated data sharing requirements which will be implemented in 2023.

Learn more about this NOSI (NOT-OD-21-089) and apply by May 20. All inquiries may be directed to Fenglou Mao, Ph.D., at reposupport@nih.gov.

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