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Data Science Community

Building a digital ecosystem for biomedicine.

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BD2KBig Data to Knowledge

Broadening impact through biomedical data science research and training.

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Commons

Connecting resources and enabling discovery.

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Data Science at NIH

The NIH is dedicated to harnessing the potential of the computational and quantitative sciences to elevate the impact and efficiency of biomedical research. NIH efforts in the integration of Data Science with the biomedical sciences are coordinated by the NIH Scientific Data Council and the NIH Office of the Associate Director for Data Science (ADDS). The ADDS office leads the development of the overall NIH vision in Data Science and coordinates across the 27 Institutes and Centers in support of biomedical research as a digital enterprise.

 
Input | Output Blog

Get the news and tell the community what you think. Input | Output is the Data Science @ NIH news and discussion forum.

 
NIH Data Science Community

Who’s doing Data Science? How can it help you? Learn about the NIH Data Science community to find out.

 
BD2K Funding Announcements

BD2K funding catalyzes Data Science research in support of biomedicine. Find out about new funding opportunities here.

 
NIH Data Science Workforce Development

New to Data Science? Want to Learn more? Find NIH resources for training and teaching here.

Data Science Community News

  • Call for Public Feedback for bioCADDIE DataMed DDI Prototype

    The National Institutes for Health (NIH) is pleased to announce an opportunity to evaluate and...read more

  • NIH Office of Research Infrastructure Programs (ORIP) Request for Information (RFI) NOT-OD-16-091

    The NIH Office of Research Infrastructure Programs (ORIP,...read more

  • Big Data to Knowledge Multi-Council Working Group - January 2016

    Notice is hereby given of a meeting of the Big Data to Knowledge Multi-Council Working Group....read more

  • Big Data to Knowledge Multi-Council Working Group - May 2016

    Notice is hereby given of a meeting of the Big Data to Knowledge (BD2K) Multi-Council...read more

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Biomedical Data Science Upcoming Events

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2016 BD2K All Hands Meeting & Science Symposium

November 29, 2016 - December 1, 2016

2016 BD2K All Hands Meeting...

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View Data Science Events
 The Commons

The Commons is intended to facilitate access and catalyze the sharing, use, reuse, interoperability, and discoverability of shared digital research objects. It is a shared and interoperable computing environment intended to take advantage of emergent public and private cloud computing platforms and existing high performance computing (HPC) resources. The NIH is currently implementing a number of Commons pilots to develop, test, and use each element of the Commons individually and in concert. The results of these pilot efforts will provide a basis for widespread application of the Commons.

Learn More About Commons
 Data Science Community

Biomedical Data Science is everywhere at the NIH and the community is growing. From funding opportunities to book clubs, you can find the support or training you need at the NIH.

Data Science Community at NIH

The NIH has a vibrant community of intramural researchers, world-class resources, and strong extramural programs invested in Data Science. Whether you are looking for collaboration, a Beowulf cluster, or a funding opportunity chances are you'll find it at one or more of the NIH Institutes and Centers. Find out more about what the NIH Data Science community is all about here.

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Join the Data Discussion

Everybody is talking about Data Science! From NIH sponsored Scientific Interest Groups (SIGs) to informal meet-ups it is easy to find people interested in Data Science at the NIH. Stay Current on the latest news with email subscriptions or learn about a new technique at a SIG discussion.

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Workforce Development

Want to learn Data Science skills? Training opportunities are at your fingertips. Explore online and on campus activities at the NIH Data Science Training Center or apply to BD2K extramural training funding opportunities. Find out more about how to get the training you need here.

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Community Engagement

Biomedical Data Science offers great career opportunities at many educational levels. Diverse perspectives support innovation and ingenuity. Data Science at NIH is dedicated to reaching out to underrepresented populations in biomedical data science and to supporting the unique needs of the different fields of biomedicine. Learn how to join in and to make data science work for you here.

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 Big Data to Knowledge | BD2K Learn More About BD2K
  • Image of Scientists working in a lab.

    Why BD2K

    The ability to harvest the wealth of information contained in biomedical Big Data will advance our understanding of human health and disease; however, lack of appropriate tools, poor data accessibility, and insufficient training, are major impediments to rapid translational impact. To meet this challenge, the National Institutes of Health (NIH) launched the Big Data to Knowledge (BD2K) initiative in 2012.

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  • Image of Scientists working in a lab.

    What is BD2K?

    The Big Data to Knowledge (BD2K) program is a trans-NIH initiative established to enable biomedical research as a digital research enterprise, to facilitate discovery and support new knowledge, and to maximize community engagement. BD2K supports biomedical Big Data at the NIH and in the scientific community through a broad range of mechanisms, including workshops, seminars, challenges, and grant funding.

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  • Image of Scientists working in a lab.

    Who is involved in BD2K?

    BD2K is a collaboration of researchers, educators, clinicians, developers, and administrators devoted to enabling the integration of the computational and quantitative sciences and the biomedical sciences. We are grantees, workshop participants, program and science officers, advisors, NIH staff, and volunteers, working together and adding the perspectives of our institutions, institutes, or centers, our scientific and technical backgrounds, and our individual experiences to make this program a success.

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