The ‘FAIR Guiding Principles for scientific data management and stewardship’ were published in Scientific Data in 2016. The authors intended to provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets.
The principles emphasise machine-actionability (i.e. the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data.
The FAIR data principles are described at Force11 - The Future of Research Communications and e-Scholarship.