Developing data interoperability using standards: A wheat community use case

cg.authorship.typesCGIAR and advanced research instituteen
cg.contributor.affiliationInstitut National de la Recherche Agronomique, Franceen
cg.contributor.affiliationBioversity Internationalen
cg.contributor.affiliationUniversity of Adelaideen
cg.contributor.affiliationInstitut National de la Recherche Scientifique, Franceen
cg.contributor.affiliationOregon State Universityen
cg.contributor.affiliationPolish Academy of Sciencesen
cg.contributor.affiliationEarlham Instituteen
cg.contributor.affiliationInternational Maize and Wheat Improvement Centeren
cg.contributor.affiliationStanford Universityen
cg.contributor.affiliationUniversité de Montpellieren
cg.contributor.affiliationInstitut de Recherche pour le Développement, Franceen
cg.contributor.affiliationNEUROPUBLIC S.Aen
cg.contributor.affiliationInstitut de Recerca i Tecnologia Agroalimentariesen
cg.contributor.affiliationFood and Agriculture Organization of the United Nationsen
cg.contributor.affiliationCommonwealth Scientific and Industrial Research Organisation, Australiaen
cg.contributor.crpBig Data
cg.creator.identifierElizabeth Arnaud: 0000-0002-6020-5919en
cg.identifier.doihttps://doi.org/10.12688/f1000research.12234.2en
cg.issn2046-1402en
cg.journalF1000Researchen
cg.reviewStatusPeer Reviewen
cg.subject.bioversityONTOLOGYen
cg.subject.bioversitySTANDARDSen
cg.subject.bioversityKNOWLEDGE ORGANIZATION SYSTEMen
cg.subject.systemdataen
cg.volume6en
dc.contributor.authorDzale-Yeumo, E.en
dc.contributor.authorAlaux, M.en
dc.contributor.authorArnaud, Elizabethen
dc.contributor.authorAubin, S.en
dc.contributor.authorBaumann, U.en
dc.contributor.authorBuche, P.en
dc.contributor.authorCooper, Laurel D.en
dc.contributor.authorCwiek-Kupczynska, H.en
dc.contributor.authorDavey, R.P.en
dc.contributor.authorFulss, R.A.en
dc.contributor.authorJonquet, C.en
dc.contributor.authorLaporte, Marie-Angéliqueen
dc.contributor.authorLarmande, Pierreen
dc.contributor.authorPommier, C.en
dc.contributor.authorProtonotarios, V.en
dc.contributor.authorReverte, C.en
dc.contributor.authorShrestha, R.en
dc.contributor.authorSubirats, I.en
dc.contributor.authorVenkatesan, A.en
dc.contributor.authorWhan, A.en
dc.contributor.authorQuesneville, H.en
dc.date.accessioned2017-12-29T09:30:46Zen
dc.date.available2017-12-29T09:30:46Zen
dc.identifier.urihttps://hdl.handle.net/10568/89854
dc.titleDeveloping data interoperability using standards: A wheat community use caseen
dcterms.abstractIn this article, we present a joint effort of the wheat research community, along with data and ontology experts, to develop wheat data interoperability guidelines. Interoperability is the ability of two or more systems and devices to cooperate and exchange data, and interpret that shared information. Interoperability is a growing concern to the wheat scientific community, and agriculture in general, as the need to interpret the deluge of data obtained through high-throughput technologies grows. Agreeing on common data formats, metadata, and vocabulary standards is an important step to obtain the required data interoperability level in order to add value by encouraging data sharing, and subsequently facilitate the extraction of new information from existing and new datasets. During a period of more than 18 months, the RDA Wheat Data Interoperability Working Group (WDI-WG) surveyed the wheat research community about the use of data standards, then discussed and selected a set of recommendations based on consensual criteria. The recommendations promote standards for data types identified by the wheat research community as the most important for the coming years: nucleotide sequence variants, genome annotations, phenotypes, germplasm data, gene expression experiments, and physical maps. For each of these data types, the guidelines recommend best practices in terms of use of data formats, metadata standards and ontologies. In addition to the best practices, the guidelines provide examples of tools and implementations that are likely to facilitate the adoption of the recommendations. To maximize the adoption of the recommendations, the WDI-WG used a community-driven approach that involved the wheat research community from the start, took into account their needs and practices, and provided them with a framework to keep the recommendations up to date. We also report this approach’s potential to be generalizable to other (agricultural) domains.en
dcterms.accessRightsOpen Access
dcterms.available2017-12-06en
dcterms.bibliographicCitationDzale Yeumo, E.; Alaux, M.; Arnaud, E.; Aubin, S.; Baumann, U.; Buche, P.; Cooper, L.; Cwiek-Kupczynska, H.; Davey, R.P.; Fulss, R.A.; Jonquet, C.; Laporte, M-A.; Larmande, P.; Pommier, C.; Protonotarios, V.; Reverte, C.; Shrestha, R.; Subirats, I.; Venkatesan, A.; Whan, A.; Quesneville, H. (2017) Developing data interoperability using standards: A wheat community use case. [version 2; referees: 2 approved]. F1000Research 6:1843en
dcterms.issued2017en
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherF1000 Research Ltden
dcterms.subjectontologyen
dcterms.subjectstandardsen
dcterms.subjectterminologyen
dcterms.subjectknowledge organization systemen
dcterms.subjectdataen
dcterms.subjectwheaten
dcterms.typeJournal Article

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