More on Big Data Training for the Scientific Workforce


Biomedical science and healthcare research are generating increasingly large and complex sets of data, from many different subfields. New strategies are needed to manage, integrate, analyze, visualize and draw conclusions from this “big data”, and our Big Data to Knowledge (BD2K) Initiative, which originated from an Advisory Committee to the Director (ACD) working group, is NIH’s way of addressing these needs.

In February of 2013 I wrote about NIH’s request for community input on how to best prepare the research workforce to capitalize on big data. Since then, the BD2K group has announced its flagship programs, and welcomed Philip E. Bourne as NIH’s first Associate Director for Data Science. Now, I’m excited to update you on the important research training programs that are part of the BD2K initiative.

Using responses from the request for information and input from a workshop on Enhancing Training for Biomedical Big Data (day 1 and day 2 of the videocast are archived online), the BD2K working group developed a series of big data training-specific funding opportunity announcements (FOAs), to prepare the biomedical workforce to tackle health-related big data challenges, both as users of biomedical big data and as developers of tools and methods for using big data.

Three of these opportunities are now accepting applications: two are geared toward developing analytic big data skills in scientists and clinicians (Courses in for Skills Development in Biomedical Big Data Science (R25) and Open Educational Resources for Biomedical Big Data (R25)) and the other is an early career development award in big data research (Mentored Career Development Award in Biomedical Big Data Science for Clinicians and Doctorally Prepared Scientists (K01)).

In addition, the BD2K Initiative intends to publish three more research training FOAs in the coming weeks: one for establishing new predoctoral training programs in big data, and two for revisions to add biomedical big data training to existing training programs (T32s and T15s).

Solving big data challenges in health requires the combination of knowledge and skills in computing and the quantitative sciences, as well as in the biomedical sciences. These training programs are key to helping scientists acquire these analytic skills. If you’re interested in learning more about these training opportunities or the other ways NIH is advancing health discoveries through big data, visit the BD2K website for more information.

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