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