The FAIR Funder pilot programme to make it easy for funders to require\n and for grantees to produce FAIR Data

There is a growing acknowledgement in the scientific community of the\nimportance of making experimental data machine findable, accessible,\ninteroperable, and reusable (FAIR). Recognizing that high quality metadata are\nessential to make datasets FAIR, members of the GO FAIR Initiative and the\nResearch Data Alliance (RDA) have initiated a series of workshops to encourage\nthe creation of Metadata for Machines (M4M), enabling any self-identified\nstakeholder to define and promote the reuse of standardized, comprehensive\nmachine-actionable metadata. The funders of scientific research recognize that\nthey have an important role to play in ensuring that experimental results are\nFAIR, and that high quality metadata and careful planning for FAIR data\nstewardship are central to these goals. We describe the outcome of a recent M4M\nworkshop that has led to a pilot programme involving two national science\nfunders, the Health Research Board of Ireland (HRB) and the Netherlands\nOrganisation for Health Research and Development (ZonMW). These funding\norganizations will explore new technologies to define at the time that a\nrequest for proposals is issued the minimal set of machine-actionable metadata\nthat they would like investigators to use to annotate their datasets, to enable\ninvestigators to create such metadata to help make their data FAIR, and to\ndevelop data-stewardship plans that ensure that experimental data will be\nmanaged appropriately abiding by the FAIR principles. The FAIR Funders design\nenvisions a data-management workflow having seven essential stages, where\nsolution providers are openly invited to participate. The initial pilot\nprogramme will launch using existing computer-based tools of those who attended\nthe M4M Workshop.\n