The FAIR data principles by Maxi Kindling and Laura Rothfritz
This collection aims to aggregate scholarly literature a well as grey literature on the principles of FAIR (findable, accessible, interoperable, reusable) data and its implications on research infrastructures.
Collection details
The FAIR principles were first published by Wilkinson et al. in 2016. They are not supposed to serve as a standard but rather as guiding principles to enhance the machine-driven discovery and reusability of scientific outputs, especially data.
Editors
Collection Information
| Main image credit: | Image from: fair - The Scholarly Kitchen (sspnet.org) |
| Background image credit: | Image by Michal Jarmoluk from Pixabay |
| ScienceOpen disciplines: | Assessment, Evaluation & Research methods, Information & Library science, Information systems & theory |
| Keywords: | FAIR data, FAIR principles, research data management, data reuse, open science |
| DOI: | 10.14293/S2199-1006.1.SOR-COMPSCI.CLNBRUP.v1 |
Latest Articles20
- Data models to GO-FAIRAuthors: