Grapevine and Wine Metabolomics-Based Guidelines for FAIR Data and Metadata Management

In the era of big and omics data, good organization, management, and description of experimental data are crucial for achieving high-quality datasets. This, in turn, is essential for the export of robust results, to publish reliable papers, make data more easily available, and unlock the huge potent...

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Autores principales: Stefania Savoi, Panagiotis Arapitsas, Éric Duchêne, Maria Nikolantonaki, Ignacio Ontañón, Silvia Carlin, Florian Schwander, Régis D. Gougeon, António César Silva Ferreira, Georgios Theodoridis, Reinhard Töpfer, Urska Vrhovsek, Anne-Francoise Adam-Blondon, Mario Pezzotti, Fulvio Mattivi
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Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/421976d74f074eb7a1fbf6078a940dbe
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spelling oai:doaj.org-article:421976d74f074eb7a1fbf6078a940dbe2021-11-25T18:20:41ZGrapevine and Wine Metabolomics-Based Guidelines for FAIR Data and Metadata Management10.3390/metabo111107572218-1989https://doaj.org/article/421976d74f074eb7a1fbf6078a940dbe2021-11-01T00:00:00Zhttps://www.mdpi.com/2218-1989/11/11/757https://doaj.org/toc/2218-1989In the era of big and omics data, good organization, management, and description of experimental data are crucial for achieving high-quality datasets. This, in turn, is essential for the export of robust results, to publish reliable papers, make data more easily available, and unlock the huge potential of data reuse. Lately, more and more journals now require authors to share data and metadata according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. This work aims to provide a step-by-step guideline for the FAIR data and metadata management specific to grapevine and wine science. In detail, the guidelines include recommendations for the organization of data and metadata regarding (i) meaningful information on experimental design and phenotyping, (ii) sample collection, (iii) sample preparation, (iv) chemotype analysis, (v) data analysis (vi) metabolite annotation, and (vii) basic ontologies. We hope that these guidelines will be helpful for the grapevine and wine metabolomics community and that it will benefit from the true potential of data usage in creating new knowledge being revealed.Stefania SavoiPanagiotis ArapitsasÉric DuchêneMaria NikolantonakiIgnacio OntañónSilvia CarlinFlorian SchwanderRégis D. GougeonAntónio César Silva FerreiraGeorgios TheodoridisReinhard TöpferUrska VrhovsekAnne-Francoise Adam-BlondonMario PezzottiFulvio MattiviMDPI AGarticleopen-dataplantsomics<i>Vitis</i>winemetabolitesMicrobiologyQR1-502ENMetabolites, Vol 11, Iss 757, p 757 (2021)
institution DOAJ
collection DOAJ
language EN
topic open-data
plants
omics
<i>Vitis</i>
wine
metabolites
Microbiology
QR1-502
spellingShingle open-data
plants
omics
<i>Vitis</i>
wine
metabolites
Microbiology
QR1-502
Stefania Savoi
Panagiotis Arapitsas
Éric Duchêne
Maria Nikolantonaki
Ignacio Ontañón
Silvia Carlin
Florian Schwander
Régis D. Gougeon
António César Silva Ferreira
Georgios Theodoridis
Reinhard Töpfer
Urska Vrhovsek
Anne-Francoise Adam-Blondon
Mario Pezzotti
Fulvio Mattivi
Grapevine and Wine Metabolomics-Based Guidelines for FAIR Data and Metadata Management
description In the era of big and omics data, good organization, management, and description of experimental data are crucial for achieving high-quality datasets. This, in turn, is essential for the export of robust results, to publish reliable papers, make data more easily available, and unlock the huge potential of data reuse. Lately, more and more journals now require authors to share data and metadata according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. This work aims to provide a step-by-step guideline for the FAIR data and metadata management specific to grapevine and wine science. In detail, the guidelines include recommendations for the organization of data and metadata regarding (i) meaningful information on experimental design and phenotyping, (ii) sample collection, (iii) sample preparation, (iv) chemotype analysis, (v) data analysis (vi) metabolite annotation, and (vii) basic ontologies. We hope that these guidelines will be helpful for the grapevine and wine metabolomics community and that it will benefit from the true potential of data usage in creating new knowledge being revealed.
format article
author Stefania Savoi
Panagiotis Arapitsas
Éric Duchêne
Maria Nikolantonaki
Ignacio Ontañón
Silvia Carlin
Florian Schwander
Régis D. Gougeon
António César Silva Ferreira
Georgios Theodoridis
Reinhard Töpfer
Urska Vrhovsek
Anne-Francoise Adam-Blondon
Mario Pezzotti
Fulvio Mattivi
author_facet Stefania Savoi
Panagiotis Arapitsas
Éric Duchêne
Maria Nikolantonaki
Ignacio Ontañón
Silvia Carlin
Florian Schwander
Régis D. Gougeon
António César Silva Ferreira
Georgios Theodoridis
Reinhard Töpfer
Urska Vrhovsek
Anne-Francoise Adam-Blondon
Mario Pezzotti
Fulvio Mattivi
author_sort Stefania Savoi
title Grapevine and Wine Metabolomics-Based Guidelines for FAIR Data and Metadata Management
title_short Grapevine and Wine Metabolomics-Based Guidelines for FAIR Data and Metadata Management
title_full Grapevine and Wine Metabolomics-Based Guidelines for FAIR Data and Metadata Management
title_fullStr Grapevine and Wine Metabolomics-Based Guidelines for FAIR Data and Metadata Management
title_full_unstemmed Grapevine and Wine Metabolomics-Based Guidelines for FAIR Data and Metadata Management
title_sort grapevine and wine metabolomics-based guidelines for fair data and metadata management
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/421976d74f074eb7a1fbf6078a940dbe
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