FAIRly big: A framework for computationally reproducible processing of large-scale data

Large-scale datasets present unique opportunities to perform scientific investigations with unprecedented breadth. However, they also pose considerable challenges for the findability, accessibility, interoperability, and reusability (FAIR) of research outcomes due to infrastructure limitations, data...

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Detalles Bibliográficos
Autores principales: Wagner, Adina S., Waite, Laura K., Wierzba, Małgorzata, Hoffstaedter, Felix, Waite, Alexander Q., Poldrack, Benjamin, Eickhoff, Simon B., Hanke, Michael
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/PMC8917149/
https://www.ncbi.nlm.nih.gov/pubmed/35277501
http://dx.doi.org/10.1038/s41597-022-01163-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917149/
https://www.ncbi.nlm.nih.gov/pubmed/35277501
http://dx.doi.org/10.1038/s41597-022-01163-2

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