FAIR principles for AI models with a practical application for accelerated high energy diffraction microscopy

A concise and measurable set of FAIR (Findable, Accessible, Interoperable and Reusable) principles for scientific data is transforming the state-of-practice for data management and stewardship, supporting and enabling discovery and innovation. Learning from this initiative, and acknowledging the imp...

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Detalles Bibliográficos
Autores principales: Ravi, Nikil, Chaturvedi, Pranshu, Huerta, E. A., Liu, Zhengchun, Chard, Ryan, Scourtas, Aristana, Schmidt, K. J., Chard, Kyle, Blaiszik, Ben, Foster, Ian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9649764/
https://www.ncbi.nlm.nih.gov/pubmed/36357431
http://dx.doi.org/10.1038/s41597-022-01712-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9649764/
https://www.ncbi.nlm.nih.gov/pubmed/36357431
http://dx.doi.org/10.1038/s41597-022-01712-9

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