Common Fund Data Ecosystem Working Group
The NIH Common Fund, within the Division of Program Coordination, Planning, and Strategic Initiatives (DPCPSI), supports bold scientific programs that catalyze discovery across all biomedical and behavioral research. The Common Fund makes strategic investments in time-limited, goal-driven programs that significantly change the trajectory of research and spur subsequent advances that otherwise would not be possible. These programs often generate broadly useful resources, including large, complex data sets and computational tools. Approximately two-thirds of the current Common Fund programs are generating rich, multi-faceted data sets intended to foster discoveries across a wide range of biomedical and behavioral research areas.
The Common Fund Data Ecosystem (CFDE) is a trans-Common Fund infrastructure investment intended to support novel discoveries through enhanced usage of Common Fund data sets. It began in 2018 through support of a CFDE Coordinating Center (CFDE-CC) which was asked to work across various Common Fund programs to identify opportunities and challenges associated with making Common Fund data sets more Findable, Accessible, Interoperable, and Reusable (FAIR). In September 2019, the Council of Councils approved a concept to engage the Data Coordinating Centers (DCCs) of these programs to collaborate in the creation of the CFDE. An exploratory/pilot phase was launched, with a plan to evaluate and adjust as needed in September 2022.
The goals of the CFDE are to:
- Enable users to query across and use Common Fund data sets;
- Sustain Common Fund data and tools after individual programs end; and
- Train users to work with Common Fund data in a cloud environment.
The CFDE is not a data platform but is intended to enable simultaneous exploration of data that are stored in many platforms. Because of the diversity of the data types generated by Common Fund programs and the location of the data in many places, the CFDE currently complements other NIH data interoperability and data management activities. In the future, it may have broader implications for such trans-NIH activities.
In May 2021, the Council of Councils voted to establish a Working Group of the Council of Councils to assess the CFDE and provide recommendations for the CFDE’s future. The Working Group will deliver a report to the Council of Councils in May 2022. If the Council of Councils approves this report, the Council will deliver the report to the NIH Director. The NIH expects to use recommendations from the approved report to guide a concept for the future of the CFDE to begin in the fall of 2022.
The charge of the Council of Councils CFDE Working Group is to provide advice and recommendations on the scope, goals, and future of the CFDE. Specifically, the Working Group is charged with:
- Reviewing the current scope and goals of the CFDE as well as progress to date
- Making recommendations for future scope and goals in the following areas:
- Findability and accessibility of data
- Data harmonization and interoperability
- Cloud workspaces
- Sustaining access to data and tools after Common Fund programs end
- Training and outreach to enhance access to, and use of, the data
- CFDE scope and strategy in the context of related NIH activities
Rick Horwitz, Ph.D.
Allen Institute for Cell Science
Elizabeth Wilder, Ph.D.
Office of Strategic Coordination
Division of Program Coordination, Planning, and Strategic Initiatives, NIH
Sergio Baranzini, Ph.D.
Professor of Neurology
Weill Institute for Neuroscience
University of California, San Francisco
Emiley Eloe-Fadrosh, Ph.D.
Metagenome Program Lead
DOE Joint Genome Institute
Warren Kibbe, Ph.D.
Professor in Biostatistics and Bioinformatics
Duke University School of Medicine
Devin Schweppe, Ph.D.
Assistant Professor of Genome Sciences
University of Washington
Bruce Weir, Ph.D.
Professor of Biostatistics, Epidemiology, and Genome Sciences
University of Washington
Cathy Wu, Ph.D.
Unidel Edward G. Jefferson Chair in Engineering and Computer Science
Director, Center for Bioinformatics and Computational Biology
University of Delaware
This page last reviewed on July 23, 2021