“The scholarly record is evolving to incorporate a widening range of research outputs, with stakeholders, systems, practices, and norms both adapting to and shaping this evolution. Stewardship of research data has received particular attention, evidenced by an ever-thickening network of services, resources, and consensus- or standards-building activities dedicated to making data sets accessible and reusable. One prominent initiative is FAIR: a set of principles that describe how to make data sets Findable, Accessible, Interoperable, and Reusable. It is still early days for FAIR – the principles were introduced in a 2016 article in Scientific Data. The future of FAIR is therefore very much to be determined; however, publishers, funders, researchers, and other stakeholders can draw some helpful lessons from history….
Changing data management practices is just as much about changing mindset and culture as it is about technical solutions – perhaps more. FAIR is a valuable tool for advocacy, in the sense of communicating the high-level goals of open, reusable data. FAIR is a valuable resource for education, by providing a shared framework within which new perspectives on responsible data management can be formed – even if those perspectives are not uniform, or easily operationalized. And FAIR is a valuable marker for how seriously the community is taking up the issue of open data: even if repositories declare their data FAIR without formal compliance or certification protocols, at least they are gesturing to the importance of the issue, and maybe even doing something substantive about it.
So the experience of OAIS tells us we should not place all our emphasis on formal implementation of FAIR as the final yardstick of its value to the community. FAIR can be, and I expect will be, a powerful catalyst in moving the research data community as a whole in the right direction….”