Overview
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.
Do you have feedback on this resource?
Thank you for your feedback as we strive to curate and publish resources to help social impact organizations succeed with data.
Explore More
Related Guides & Resources
3 Key Steps to a Successful Data Commons
A data commons is a software platform along with a governance framework that together allow a community to manage, analyze and share its data.
Overview Publicly available data from open sources are vital resources for students and researchers in a variety of disciplines. Unfortunately, processing these datasets is often tedious and cumbersome. Organizations follow distinctive practices for codifying datasets. Combining data from different sources requires mapping common entities (city, county, etc.) and resolving different…
Overview “A data commons is a system of stewardship through which data resources are managed involving processes of sustainable and ethical production, use, re-use, and redistribution — and governed through collaboration among stakeholding users and/or data producers. Despite a wide range of possible organizational structures, it is possible to identify…