NIH Data Commons Pilot Phase Consortium

The Data Commons Pilot Phase Consortium (DCPPC) will design innovative solutions that meet the needs of the computational, data, and scientific key capabilities of the NIH Data Commons Pilot Phase. These key capabilities include:

  1. Guidelines and metrics for making data Findable, Accessible, Interoperable, and Reusable (FAIR)
  2. An approach to Global Unique Identifiers (GUIDs)
  3. Application Program Interfaces (APIs) based on open standards 
  4. Architecture independent of a specific cloud platform or provider
  5. Workspaces to find and interact with data and associated tools
  6. Research ethics, privacy, and security (including authentication and authorization)
  7. Indexing and search functionality
  8. Use cases that demonstrate how the NIH Data Commons Pilot could advance biomedical research
  9. Coordination, training, and outreach

Along with NIH staff, contracting staff, and external program consultants, the investigators listed below will form the NIH Data Commons Pilot Phase Consortium (DCPPC). 

    Awards Made Under Research Opportunity Announcement (ROA) RM-17-026

    The following projects were awarded using a special type of funding mechanism called Other Transactions (OT). The OT mechanism gives NIH considerable flexibility in making and managing awards. This will be particularly important for the DCPPC to stay nimble as it approaches the complex task involved in the development of the NIH Data Commons Pilot Phase under the ever-changing conditions of data science and biomedical science.

    Project Title DCPPC Members Institution (s)
    University of Maryland NIH Data Commons Facilitation Center Crabtree, Jonathan University of Maryland
    Felix, Victor University of Maryland
    Giglio, Michelle Gwinn University of Maryland
    O'Connor, Timothy University of Maryland
    Sansone, Susanna-Assunta University of Oxford, Oxford e-Research Centre
    Schriml, Lynn University of Maryland
    White, Owen University of Maryland
    Development and Implementation Plan for Community Supported FAIR Guidelines and Metrics Dumontier, Michel Maastricht University
    Ma'ayan, Avi Icahn School of Medicine at Mount Sinai
    Klenk, Juergen Deloitte Consulting LLP
    Sansone, Susanna-Assunta University of Oxford, Oxford e-Research Centre
    Schurer, Stephan University of Miami
    Patient-centric information commons under FAIR principals (PIC-FAIR) Avillach, Paul Harvard Medical School
    Kohane, Isaac Harvard Medical School
    Kreda, David Harvard Medical School
    Manrai, Arjun K. Harvard Medical School
    Patel, Chirag J. Harvard Medical School
    Susan, Churchill Harvard Medical School
    Versmee, Laura Harvard Medical School
    The Commons Alliance: A partnership to catalyze the creation of an NIH Data Commons Grossman, Robert L. University of Chicago
    Haussler, David University of California, Santa Cruz
    O’Connor, Brian University of California, Santa Cruz 
    Paten, Benedict University of California, Santa Cruz
    Philippakis, Anthony Broad Institute
    Tang, Yajing (Phillis) University of Chicago
    Yung, Christina University of Chicago
    A Commons Platform for Promoting Continuous FAIRness Chard, Kyle University of Chicago: Globus
    Foster, Ian University of Chicago: Globus
    Kesselman, Carl University of Southern California
    Madduri, Ravi University of Chicago: Globus
    Tools and workflows for mining genomic data on many clouds Brown, C. Titus University of California, Davis
    Zaranek, Alexander Wait Curoverse Innovations, Inc.
    A collaboration for the NIH Data Commons Ahalt, Stanley Renaissance Computing Institute: RENCI
    Boyles, Rebecca RTI International
    Castillo, Claris Renaissance Computing Institute: RENCI
    Conway, Michael Renaissance Computing Institute: RENCI
    Cox, Steven Renaissance Computing Institute: RENCI
    Dumontier, Michel Maastricht University
    Haendel, Melissa Oregon Health Science University
    Mungall, Christopher Lawrence Berkeley National Laboratory
    Oprea, Tudor University of New Mexico Health Sciences Center
    Peter, Robinson The Jackson Laboratory
    FAIR data to drive CURES Davis-Dusenbery, Brandi Seven Bridges Genomics Inc
    Nielsen, Fiona Repositive
    Pyarajan, Saiju US Department of Veterans Affairs
    de Waard, Anita Elsevier
    CALIFORNIA: Cloud-agnostic Architecture to Locate Indexed FAIR objects and safely reuse them in new integrated analyses Ohno-Machado, Lucila

    University of California, San Diego

    Jiang, Xiaoqian University of California, San Diego
    Sansone, Susanna-Assunta University of Oxford, Oxford e-Research Centre
    Xu, Hua University of Texas Health Science Center at Houston
    Towards a FAIR Digital Ecosystem in the Cloud Clark, Timothy

    Harvard University

    Crosas, Mercè

    Harvard University

    Fenner, Martin

    DataCite


      Data Stewards

      The stewards for each of the following data sets received supplemental funding to existing grants to participate as members of the DCPPC. These data sets will serve as test cases to develop the capabilities of the NIH Data Commons Pilot Phase.

      Data Set DCPPC Members Institution(s)
      Genotype Tissue Expression (GTEx)

      Ardlie, Kristin

      Broad Institute Inc.
      Getz, Gad Broad Institute Inc.
      Alliance of Genome Resources (AGR) Judith Blake     The Jackson Library
      Carol Bult     The Jackson Library
      J. Michael Cherry     Stanford University
      Suzanna Lewis     Lawrence Berkeley National Laboratory
      Mary Shimoyama     Medical College of Wisconsin
      Paul Thomas     University of Southern California
      Trans-Omics for Precision Medicine (TOPMed) Abecasis, Goncalo University of Michigan
      Blackwell, Tom University of Michigan
      Borecki, Ingrid University of Washington
      Laurie, Catherine University of Washington
      Psaty, Bruce University of Washington
      Weir, Bruce University of Washington

      Learn more about each of the Test Case Data Sets

      Cloud Service Providers

      Researchers and staff from the NIH Data Commons Pilot Phase and the STRIDES initiative will work with cloud service providers (CSPs) to learn how to provide a sustainable cloud infrastructure to support NIH-derived data sets including the Data Commons Pilot Phase test case datasets.

      Assessment and Logistical Support

      The MITRE Corporation, operator of the HHS federally funded research and development center, will provide a broad range of support services for the NIH Data Commons Pilot Phase including the following:

      • Assessment services to analyze usage, costs, business models, and long-term data viability
      • Communications, coordination, training, and other logistical support 

      This contract is administered by the Center for Information Technology, and is a trans-NIH initiative funded by multiple Institutes, Centers, and Offices. 

      This page last reviewed on July 24, 2018