The US National Institute of Standards and Technology (NIST) is considering the development of a Research Data Framework, patterned on the well-known NIST Cybersecurity Framework (https://www.nist.gov/cyberframework) in which community consensus was established around “standards, guidelines, and best practices to manage cybersecurity-related risk.”  The Research Data Framework (RDaF) seeks to identify interests, obligations, costs, benefits, and risks surrounding the generation, analysis, curation, preservation, distribution, and re-use of research data.  This is a broad and dynamic environment, and it is already clear that few people or organizations fully comprehend the complexity of the research data ecosystem.  Many stakeholders share interests in research data (both produced through research or used by researchers in unanticipated contexts), including government agencies, funders (both public and private), data centers, repositories, universities and university associations, libraries, professional societies and associations, tool and infrastructure providers, academic publishers, policy organizations, advocacy groups, national and international data organizations, topical data initiatives, and, of course, individual researchers in all fields of science and humanities.  A number of stakeholders have multiple roles in this rich but complex space.  Open science and open data are trending and important topics, intersecting with key issues such as reproducibility, replicability, and reliability of research findings.  The FAIR data guidelines are an important element of the research data ecosystem, and I will describe the RDaF in general as well as specific actions NIST is taking toward increasing the FAIRness of its research data.<br/>

NIST Research Data Framework and its relevance for FAIR data

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.