New ‘FAIR’ Principles herald more open, transparent, and reusable scientific data
On March 15 2016, the FAIR Guiding Principles for scientific data management and stewardship were formally published in the Nature Publishing Group journal Scientific Data. The FAIR Principles address the lack of widely shared, clearly articulated, and broadly applicable best practices around the publication of scientific data. While the history of scholarly publication in journals is long and well established, the same cannot be said of formal data publication. Yet, data could be considered the primary output of scientific research, and its publication and reuse is necessary to ensure validity, reproducibility, and to drive further discoveries. The FAIR Principles address these needs by providing a precise and measurable set of qualities a good data publication should exhibit - qualities that ensure that the data is Findable, Accessible, Interoperable, and Reusable (FAIR). From Maastricht University, Prof Chris Evelo (professor in Bioinformatics for Integrative Systems Biology) was involved in the development of these principles.
The principles were formulated after a Lorentz Center workshop in January 2014 where a diverse group of stakeholders, sharing an interest in scientific data publication and reuse, met to discuss the features required of contemporary scientific data publishing environments. The first-draft FAIR Principles were published on the Force11 website for evaluation and comment by the wider community - a process that lasted almost two years. This resulted in the clear, concise, broadly supported principles that were published today. The principles support a wide range of new international initiatives, such as the European Open Science Cloud and the NIH Big Data to Knowledge (BD2K), by providing clear guidelines that help ensure all data and associated services in the emergent ‘Internet of Data’ will be Findable, Accessible, Interoperable and Reusable, not only by people, but notably also by machines.
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