In 2016, the ‘FAIR Guiding Principles for scientific data management and stewardship’ were published in Scientific Data. The authors intended to provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. The principles emphasize machine-actionability 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.
Related Guides & Resources
A data commons is a software platform along with a governance framework that together allow a community to manage, analyze and share its data.
Resources from McKinsey, Stanford Center on Philanthropy and Civil Society and +2