Reproducible big data science: A case study in continuous FAIRness

Big biomedical data create exciting opportunities for discovery, but make it difficult to capture analyses and outputs in forms that are findable, accessible, interoperable, and reusable (FAIR). In response, we describe tools that make it easy to capture, and assign identifiers to, data and code thr...

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Detalles Bibliográficos
Autores principales: Madduri, Ravi, Chard, Kyle, D’Arcy, Mike, Jung, Segun C., Rodriguez, Alexis, Sulakhe, Dinanath, Deutsch, Eric, Funk, Cory, Heavner, Ben, Richards, Matthew, Shannon, Paul, Glusman, Gustavo, Price, Nathan, Kesselman, Carl, Foster, Ian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6459504/
https://www.ncbi.nlm.nih.gov/pubmed/30973881
http://dx.doi.org/10.1371/journal.pone.0213013

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6459504/
https://www.ncbi.nlm.nih.gov/pubmed/30973881
http://dx.doi.org/10.1371/journal.pone.0213013

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