Abstract
Open data, FAIR (findable, accessible, interoperable and reusable) and research data management (RDM) are three overlapping but distinct concepts, each emphasizing different aspects of handling and sharing research data. They have different strengths in terms of informing and influencing how research data is treated, and there is much scope for enrichment of data if they are applied collectively. This paper explores the boundaries of each concept and where they intersect and overlap. As well as providing greater definitional clarity, this will help researchers to manage and share their data, and those supporting researchers, such as librarians and data stewards, to understand how these concepts can best be used in an advocacy setting. FAIR and open both focus on data sharing, ensuring content is made available in ways that promote access and reuse. Data management by contrast is about the stewardship of data from the point of conception onwards. It makes no assumptions about access, but is essential if data are to be meaningful to others. The concepts of FAIR and open are more noble aspirations and are, this paper argues, a useful way to engage researchers and encourage good data practices from the outset.
Highlights
The last 20 years have seen several shifts in emphasis and priorities in the area of research data management (RDM) and sharing
Whether using the terms RDM, FAIR or open, it is all too easy for those of us advocating for data management and sharing to get caught up in our concern for the data and forget what matters to the researcher – their research! We do not advocate for data management and sharing for their own sake, and whilst the end goals vary from reproducibility, to reuse across disciplines, to application by practitioners, the use which that data can be put to should be at the heart of our activities
RDM, FAIR and open are all important in their own right and should be viewed as complementary yet distinct concepts
Summary
The last 20 years have seen several shifts in emphasis and priorities in the area of research data management (RDM) and sharing. Data could be made open or somewhat FAIR without being well managed, resulting in poorly documented and less reusable data This is why it is important that data are well managed to support sharing in a meaningful way and promote reuse. Managing and sharing research data are often not a high priority when talking to researchers, and whilst RDM, FAIR and open all help to encourage good practice, this proliferation of terminology can sometimes cause confusion. Acknowledge impact, citation and prestige When discussing both FAIR and open data, many participants raised issues around citations, impact, prestige and researcher assessment These issues may not be the focus of RDM, it is important to recognize the pressures on researchers to publish papers in a prestige journal, and be clear about how sharing data in a FAIR and open way can help support this. The 15 FAIR principles include several clear action points, such as obtaining a persistent identifier, assigning a usage licence and providing metadata online
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