As biomedical tools and technologies rapidly improve, researchers are producing and analyzing an ever-expanding amount of complex biological data called “big data.” The Big Data to Knowledge (BD2K) program is a trans-NIH initiative that was launched in 2013 to support the research and development of innovative and transformative approaches and tools to maximize and accelerate the integration of big data and data science into biomedical research. The BD2K Program also supported initial efforts toward making data sets “FAIR” Findable, Accessible, Interoperable, and Reusable. Learn more about the FAIR principles.
Big Data to Knowledge Phase I & II
In its first phase (FY2014-FY2017), BD2K invested $200 million in grant awards to address some major data science challenges and to stimulate data-driven discovery. It focused on facilitating broad use of biomedical big data, developing and disseminating analysis methods and software, enhancing training relevant for large-scale data analysis,and establishing centers of excellence for biomedical big data. BD2K funded a series of small projects to explore the feasibility of a Commons Framework to support sharing and reuse of digital objects in cloud environments, and to facilitate implementation of FAIR principles. These awards will continue through award end dates, and lessons from this initial investment will help inform the second phase of the program (FY2018-FY2021).
BD2K has now entered a second phase that will focus on making the products of research developed in Phase I usable, discoverable, and disseminated to their intended end-users. In addition, the program will continue to pursue approaches to making biomedical big data Findable, Accessible, Interoperable, and Reusable or “FAIR.”
BD2K is one of many data science-related programs at NIH. To learn more about NIH Data Science efforts visit the Data Science at NIH website.
This page last reviewed on October 25, 2018