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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Detalhes bibliográficos
Publicado no:PLoS One
Main Authors: 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: Artigo
Idioma:Inglês
Publicado em: Public Library of Science 2019
Assuntos:
Research Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6459504/
https://ncbi.nlm.nih.gov/pubmed/30973881
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0213013
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