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Summary
In the past decade, research data have become widely recognized as a critical national and global resource, and the risks of losing or mismanaging research data can have severe economic and social consequences. The proliferation of artificial intelligence approaches in all fields has created a huge demand for trustworthy research data in both the natural (e.g., chemistry) and social (e.g., economics) sciences. To address these issues, NIST initiated a new, multi-stakeholder project in fall 2019 entitled the Research Data Framework (RDaF). The RDaF provides the stakeholder community with a structured approach to develop a customizable strategy for the management of research data. The audience for the RDaF is the entire research data community, including all organizations and individuals engaged in any activities concerning research data management, from Chief Executive Officers (CEOs) and Chief Data Officers (CDOs) to librarians and researchers.
Version 2.0 of the RDaF Publication
Appendix A: Informative References (zip)
Appendix D: Sample Profiles (excel)
Description
What is the Research Data Framework?
- A map of the research data space: who, what, where, why, when?
- A dynamic guide for the various stakeholders in research data to understand best practices for research data management and dissemination
- A resource for understanding costs, benefits, and risks associated with research data management
- A consensus document based on inputs and conversations amongst the stakeholders in research data
- A tool that may be used to change the research data management culture in an organization
Version 2.0 of the Research Data Framework
The structure of the RDaF follows that of the NIST Cybersecurity and Privacy Frameworks. The foundation of the RDaF consists of six structural elements:
- Research Data Lifecycle Stages organize foundational research data-related activities at their highest level. As depicted in the figure above, a lifecycle approach was selected as the organizing concept of the Framework Core.
- Envision encompasses the review of the overall strategies and drivers of an organization's research data program. The Envision lifecycle stage is where choices and decisions are made that together chart a high-level course of action to achieve desired organizational goals.
- Plan includes the activities associated with preparing for data acquisition, selection of data formats and storage solutions, and anticipation of data sharing and dissemination strategies and policies.
- Generate/Acquire covers the generation of raw research data, both experimentally and computationally, within an organization, and the collection or acquisition of research data produced outside of an organization.
- Process/Analyze concerns the actions performed on generated or externally acquired research data to yield processed research data, typically using software, from which observations and conclusions can be made.
- Share/Use/Reuse outlines how raw and processed research data are disseminated, used, and reused within an organization and any constraints or encouragements to use/reuse. It also includes the dissemination, use, and reuse of raw and processed research data outside of an organization.
- Preserve/Discard delineates the end-of-use and end-of-life provisions for research data in an organization and includes records management, archiving, and safe disposal.
- Topics (formerly termed Categories) for the six Lifecycle Stages are closely tied to programmatic needs and activities, as well as other important factors.
- Subtopics (formerly termed Subcategories) further divide the Topics.
- Overarching Themes interweave all lifecycle stages
- Informative References are standards, guidelines, and practices associated with a Subcategory that provide the means to address that topic.
- Profiles allow the RDaF to be tailored to different levels of stakeholders/users from a CEO to an individual researcher. Stakeholder Workshop Presentation for a Generic Job/Role (PDF).
Version 2 of the RDaF is a substantial expansion over Versions 1 and 1.5. Topics and subtopics have been extended and clarified based on community feedback, and overarching themes and sample profiles have been added. All topics and subtopics have explicit definitions, with references. It now stands as the most comprehensive overview of the research data ecosystem in existence.
This research data framework represents nearly four years of development, coordinated by the NIST Office of Data and Informatics and the NIST Research Library. This framework is not a NIST imposition or standard, but rather a resource built with extensive community engagement, including: 3 plenary workshops, 15 topical breakout meetings, community inputs received in response to a Federal Registry Request for Comment, and a community engagement meeting hosted by the National Academy of Sciences.
Recent Developments and Next Steps
Since the publication of RDaF version 2.0 we have been creating and running workshops for institutions interested in implementing the RDaF locally. The team is also refining the RDaF web app and looking into ways of visualizing the framework through network graphs.
How can you or your organization become involved in the RDaF development?
- Organize and host an informational webinar or workshop on the RDaF
- Identify informative references, both existing and under development, that are associated with the Subtopics in the RDaF Framework Core
- Promulgate the RDaF through engagement and outreach activities at relevant technical events and venues
- Publish notices concerning the RDaF in topical newsletters, journals, and social media
- Inform us of any implementation projects within your organization
Related Documents and Information
RDaF Version 1.5 RDaF Version 1.0
Acknowledgments and Special Thanks
The RDaF team would like to thank those who have worked on the project for many years including: Alda Yuan, Debbie Kaiser, Andrea Medina-Smith, Eva Campo, Bonnie Carroll (Steering Committee chair), the stakeholders from all disciplines who have assisted in validating the framework and the former RDaF Steering Committee:
- Laura Biven, NIH
- Cate Brinson, Duke University
- Martin Halbert, NSF
- Hilary Hanahoe, RDA
- Heather Joseph, SPARC
- Mark Leggott, Digital Research Alliance of Canada
- Barend Mons, Leiden University, CODATA, GO-FAIR
- Sarah Nusser, Iowa State University and the University of Virginia
- Beth Plale, Indiana University
- Anita de Waard, Elsevier
- Christopher Erdmann, SciLifeLab Data Center