FAIR veri prensipleri hakkında akademik makaleler, uygulamalı rehberler ve uluslararası standartlardan oluşan kapsamlı bir koleksiyon.
Mark D. Wilkinson, M. Dumontier, I. J. Aalbersberg, Gabrielle Appleton, M. Axton, A. Baak, N. Blomberg, J. Boiten, Luiz Olavo Bonino da Silva Santos, P. Bourne, et al.
The FAIR Data Principles aim to enhance the reusability of scientific data by improving machine findability and supporting individual reuse.
Annika Jacobsen, R. de Miranda Azevedo, N. Juty, Dominique Batista, S. Coles, R. Cornet, Mélanie Courtot, M. Crosas, M. Dumontier, et al.
FAIR principles can be implemented in various ways, but consistent implementation is crucial for true interoperability and accelerating global participation in digital resource discovery and reuse.
B. Mons, C. Neylon, Jan Velterop, M. Dumontier, Luiz Olavo Bonino da Silva Santos, Mark D. Wilkinson
The FAIR Data Principles, which propose that all scholarly output should be Findable, Accessible, Interoperable, and Reusable, have become increasingly relevant in the European Open Science Cloud, with a growing understanding of their meaning and implications.
Putu Hadi Purnama Jati, Yi Lin, Sara Nodehi, D. B. Cahyono, M. Reisen
FAIR data focuses on research data complexity, while open data primarily aims to provide public access to non-confidential data, with different approaches to achieve these goals.