Experiment design driven FAIRification of omics data matrices, an exemplar

We outline a principled approach to data FAIRification rooted in the notions of experimental design, and whose main intent is to clarify the semantics of data matrices. Using two related metabolomics datasets associated to journal articles, we perform retrospective data and metadata curation and re-...

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Autores principales: Rocca-Serra, Philippe, Sansone, Susanna-Assunta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Comment
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6908569/
https://www.ncbi.nlm.nih.gov/pubmed/31831744
http://dx.doi.org/10.1038/s41597-019-0286-0
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author Rocca-Serra, Philippe
Sansone, Susanna-Assunta
author_facet Rocca-Serra, Philippe
Sansone, Susanna-Assunta
author_sort Rocca-Serra, Philippe
collection PubMed
description We outline a principled approach to data FAIRification rooted in the notions of experimental design, and whose main intent is to clarify the semantics of data matrices. Using two related metabolomics datasets associated to journal articles, we perform retrospective data and metadata curation and re-annotation, using community, open, interoperability standards. The results are semantically-anchored data matrices, deposited in public archives, which are readable by software agents for data-level queries, and which can support the reproducibility and reuse of the data underpinning the publications.
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spelling pubmed-69085692019-12-23 Experiment design driven FAIRification of omics data matrices, an exemplar Rocca-Serra, Philippe Sansone, Susanna-Assunta Sci Data Comment We outline a principled approach to data FAIRification rooted in the notions of experimental design, and whose main intent is to clarify the semantics of data matrices. Using two related metabolomics datasets associated to journal articles, we perform retrospective data and metadata curation and re-annotation, using community, open, interoperability standards. The results are semantically-anchored data matrices, deposited in public archives, which are readable by software agents for data-level queries, and which can support the reproducibility and reuse of the data underpinning the publications. Nature Publishing Group UK 2019-12-12 /pmc/articles/PMC6908569/ /pubmed/31831744 http://dx.doi.org/10.1038/s41597-019-0286-0 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Comment
Rocca-Serra, Philippe
Sansone, Susanna-Assunta
Experiment design driven FAIRification of omics data matrices, an exemplar
title Experiment design driven FAIRification of omics data matrices, an exemplar
title_full Experiment design driven FAIRification of omics data matrices, an exemplar
title_fullStr Experiment design driven FAIRification of omics data matrices, an exemplar
title_full_unstemmed Experiment design driven FAIRification of omics data matrices, an exemplar
title_short Experiment design driven FAIRification of omics data matrices, an exemplar
title_sort experiment design driven fairification of omics data matrices, an exemplar
topic Comment
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6908569/
https://www.ncbi.nlm.nih.gov/pubmed/31831744
http://dx.doi.org/10.1038/s41597-019-0286-0
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