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The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.

DataScience@NIH Updates

June 8th, 2017 / in Announcements, policy, Research News / by Helen Wright

NIH Data Science Logo

Check out the following updates from Data Science at the National Institutes of Health (NIH). 

Highlights and video of selected presentations from the May 16-18 BD2K-LINCS Data Science Symposium are now available on the BD2K Centers Coordinating Center website. See researchers from the Library of Integrated Network-based Cellular Signatures (LINCS) program describe “Global Analysis and Visualization of the Thousands of Expression Signatures for Drug and Target Discovery.”

Data Science Opportunities:

The NIH, under the BD2K program, will be launching a Data Commons Pilot Phase to test ways to store, access, and share FAIR biomedical data and associated tools in the cloud. The NIH Data Commons Pilot Phase is expected to span fiscal years 2017-2020, with an estimated total budget of approximately $55.5 Million, pending available funds. Learn more here.

Call for Submissions for a special issue on “Open Research Data Resources” for Scientific Data, for articles describing novel data resources or significant and recent extensions to existing data repositories. Organizers include: Patricia Cruse (Executive Director, DataCite); Michael Huerta (NLM Coordinator of Data & Open Science Initiatives, NIH), Mike Thorley (Head of Science Information, NERC); and Susanna-Assunta Sansone (Associate Director, University of Oxford e-Research Centre).

  • Manuscript submissions due July 31, 2017.
  • For additional information, visit this website.

RFA-NS-17-018 “BRAIN Initiative: Team-Research BRAIN Circuit Programs – TeamBCP (U19).” This program will support integrated, interdisciplinary collaborative research teams from prior BRAIN technology and/or integrated approaches teams, and/or new projects from the research community that focus on examining circuit functions related to behavior, using advanced and innovative technologies.

  • Applications due October 17, 2017.

Data Science Events:

Machine Learning-Brain Imaging Lecture Series presents “Machine Learning that Understands Complex Data” by Dr. Janusz Wojtusiak, Director of the Center for Discovery Science & Health Informatics at George Mason University, June 12, 2017, 2:00pm-3:00pm ET, Bldg. 49, Room 1A51/1A59, on the NIH Main Campus in Bethesda, MD. For additional information or to schedule a meeting with the speaker, contact Daniel Handwerker at:

DCH2017 International Interdisciplinary Conference on Digital Cultural Heritage, August 30, 2017 – September 1, 2017, in Berlin. Organized by CODATA-Germany, the German National Committee for CODATA, Committee on Data for Science and Technology of the International Council for Science (ICSU). Registration is now open, take advantage of specially reduced rates for early booking available until June 12, 2017, more information here.

NINR 2017 Precision Health Boot Camp, “Precision Health: From ‘Omics’ to Data Science, August 7-11, 2017on the NIH Main Campus in Bethesda, MD. This free, one-week intensive research training course covers the latest advances in genomics, pharmacogenomics, nutrigenomics, metabolomics, microbiomics, and data science as well as the associated ethical, legal and social implications of precision health. The course is provided by NINR at no cost. Registration is now closed. To join the wait list, visit this website.

Save the Date!  International CODATA 2017 Conference, “Global Challenges and Data-Driven Science,” October 8-13, 2017, Saint-Petersburg, Russia.

DataScience@NIH Updates

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