FAIRsharing presents its community approach to mapping and tracking the development of data standards and policies across scientific fields. In an article published in Nature Biotechnology, the team behind FAIRsharing, along with key representatives of its user community, describe how FAIRsharing helps address the ongoing challenges to establish widely-adopted community standards across all stages of the data management cycle.
As today’s research is increasingly driven by data, there is a need for an interconnected network of data repositories, data and metadata standards, and policies, to ensure that data are trustworthy, persistent, and support reproducibility. Community-developed standards, such as those for the identification and reporting of data and metadata, are the fundamental components of the FAIR principles. These principles are designed to make all digital assets Findable, Accessible, Interoperable and Reusable by humans as well as by machines.
FAIRsharing is a key resource that systematically maps and connects the different community-driven standards, databases, repositories and data policies across all fields of science. It guides researchers, publishers, funders and others professionals by curating information about standards for the identification, citation and reporting on data, and how they relate to each other. As of February 2019, FAIRsharing had over 2,600 records, 1,200 standards, 1,200 databases and 118 data policies from scientific journals and funders.
Read the full article: Nature Biotechnology