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The ontologies community of practice: a CGIAR initiative for big data in agrifood systems

dc.contributor.authorArnaud, E.
dc.contributor.authorLaporte, M.A.
dc.contributor.authorKim, S.
dc.contributor.authorAubert, C.
dc.contributor.authorLeonelli, S.
dc.contributor.authorMiro, B.
dc.contributor.authorCooper, L.
dc.contributor.authorJaiswal, P.
dc.contributor.authorKruseman, G.
dc.contributor.authorShrestha, R.
dc.contributor.authorButtigieg, P.L.
dc.contributor.authorMungall, C.J.
dc.contributor.authorPietragalla, J.
dc.contributor.authorAgbona, A.
dc.contributor.authorMuliro, J.
dc.contributor.authorDetras, J.
dc.contributor.authorHualla, V.
dc.contributor.authorRathore, A.
dc.contributor.authorDas, R.R.
dc.contributor.authorDieng, I.
dc.contributor.authorBauchet, G.J.
dc.contributor.authorMenda, N.
dc.contributor.authorPommier, C.
dc.contributor.authorShaw, F.
dc.contributor.authorLyon, D.
dc.contributor.authorMwanzia, L.
dc.contributor.authorJuarez, H.
dc.contributor.authorBonaiuti, E.
dc.contributor.authorChiputwa, B.
dc.contributor.authorObileye, O.
dc.contributor.authorAuzoux, S.
dc.contributor.authorYeumo, E.D.
dc.contributor.authorMueller, L.
dc.contributor.authorSilverstein, K.
dc.contributor.authorLafargue, A.
dc.contributor.authorAntezana, E.
dc.contributor.authorDevare, M.
dc.contributor.authorKing, B.
dc.date.accessioned2022-09-16T07:48:37Z
dc.date.available2022-09-16T07:48:37Z
dc.date.issued2020-10-09
dc.identifier.citationArnaud, E., Laporte, M.A., Kim, S., Aubert, C., Leonelli, S., Miro, B., ... & King, B. (2020). The ontologies community of practice: a CGIAR initiative for big data in agrifood systems. Patterns, 1(7): 100105, 1-12.
dc.identifier.issn2666-3899
dc.identifier.urihttps://hdl.handle.net/20.500.12478/7757
dc.description.abstractThe Bigger Picture Digital technology use in agriculture and agrifood systems research accelerates the production of multidisciplinary data, which spans genetics, environment, agroecology, biology, and socio-economics. Quality labeling of data secures its online findability, reusability, interoperability, and reliable interpretation, through controlled vocabularies organized into meaningful and computer-readable knowledge domains called ontologies. There is currently no full set of recommended ontologies for agricultural research, so data scientists, data managers, and database developers struggle to find validated terminology. The Ontologies Community of Practice of the CGIAR Platform for Big Data in Agriculture harnesses international expertise in knowledge representation and ontology development to produce missing ontologies, identifies best practices, and guides data labeling by teams managing multidisciplinary information platforms to release the FAIR data underpinning the evidence of research impact. Summary Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture and agrifood systems requires quality data labeling or annotation in order to be interoperable. As recommended by the FAIR principles, data, labels, and metadata must use controlled vocabularies and ontologies that are popular in the knowledge domain and commonly used by the community. Despite the existence of robust ontologies in the Life Sciences, there is currently no comprehensive full set of ontologies recommended for data annotation across agricultural research disciplines. In this paper, we discuss the added value of the Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture for harnessing relevant expertise in ontology development and identifying innovative solutions that support quality data annotation. The Ontologies CoP stimulates knowledge sharing among stakeholders, such as researchers, data managers, domain experts, experts in ontology design, and platform development teams.
dc.description.sponsorshipCGIAR Trust Fund
dc.description.sponsorshipUK Aid
dc.description.sponsorshipNational Science Foundation
dc.description.sponsorshipFrontiers in Arctic Marine Monitoring
dc.description.sponsorshipBBSRC Core Strategic Program
dc.description.sponsorshipAlan Turing Institute
dc.description.sponsorshipEuropean Commission
dc.format.extent1-12
dc.language.isoen
dc.subjectOntology
dc.subjectAgriculture
dc.subjectAgrifood Systems
dc.subjectCrop Production
dc.subjectBreeding
dc.subjectPhenotypes
dc.subjectGenotypes
dc.titleThe ontologies community of practice: a CGIAR initiative for big data in agrifood systems
dc.typeJournal Article
cg.contributor.affiliationBioversity International
cg.contributor.affiliationInternational Food Policy Research Institute
cg.contributor.affiliationUniversity of Exeter
cg.contributor.affiliationOregon State University
cg.contributor.affiliationInternational Maize and Wheat Improvement Center
cg.contributor.affiliationGEOMAR Helmholtz Centre for Ocean Research, Germany
cg.contributor.affiliationLawrence Berkeley National Laboratory
cg.contributor.affiliationIntegrated Breeding Platform, Mexico
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.contributor.affiliationWorldFish
cg.contributor.affiliationInternational Rice Research Institute
cg.contributor.affiliationInternational Potato Center
cg.contributor.affiliationInternational Crops Research Institute for the Semi-Arid Tropics
cg.contributor.affiliationBoyce Thompson Institute for Plant Research
cg.contributor.affiliationInstitut National de la Recherche pour l’Agriculture, l’Alimentation et l’Environnement, France
cg.contributor.affiliationEarlham Institute
cg.contributor.affiliationInternational Center for Agricultural Research in the Dry Areas
cg.contributor.affiliationWorld Agroforestry Centre
cg.contributor.affiliationThe French Agricultural Research Centre for International Development
cg.contributor.affiliationUniversity of Minnesota
cg.contributor.affiliationCP RDIT, Syngenta, France
cg.contributor.affiliationBayer Crop Science SA-NV, Belgium
cg.contributor.affiliationNorwegian University of Science and Technology
cg.contributor.affiliationInternational Center for Tropical Agriculture
cg.contributor.affiliationUniversité Paris-Saclay
cg.contributor.affiliationUniversité de Montpellier
cg.coverage.hubHeadquarters and Western Africa Hub
cg.identifier.bibtexciteidARNAUD:2020
cg.authorship.typesCGIAR and advanced research institute
cg.iitasubjectAgronomy
cg.iitasubjectKnowledge Management
cg.iitasubjectPlant Breeding
cg.iitasubjectPlant Production
cg.journalPatterns
cg.notesOpen Access Article; Published online: 25 Sept, 2020
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 (CC BY-NC-ND 4.0)
cg.targetaudienceScientists
cg.identifier.doihttps://dx.doi.org/10.1016/j.patter.2020.100105
cg.futureupdate.requiredNo
cg.identifier.issue7
cg.identifier.volume1


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