TY - JA AU - Arnaud,E. AU - Laporte,M.A. AU - Soonho Kim AU - Aubert,C. AU - Leonelli,S. AU - Miro,B. AU - Cooper,L. AU - Jaiswal,P. AU - Kruseman,G. AU - Shrestha,R. AU - Buttigieg,P.L. AU - Mungall,C.J. AU - Pietragalla,J. AU - Agbona,A. AU - Muliro,J. AU - Detras,J. AU - Hualla,V. AU - Rathore,A. AU - Das,R.R. AU - Dieng,I. AU - Bauchet,G.J. AU - Menda,N. AU - Pommier,C. AU - Shaw,F. AU - Lyon,D. AU - Mwanzia,L. AU - Juarez,H. AU - Bonaiuti,E. AU - Chiputwa,B. AU - Obileye,O. AU - Auzoux,S. AU - Dzale Yeumo,E. AU - Mueller,L.A. AU - Silverstein,K. AU - Lafargue,A. AU - Antezana,E. AU - Devare,M. AU - King,B. TI - The Ontologies Community of Practice: a CGIAR initiative for big data in agrifood systems SN - 2666-3899 PY - 2020/// CY - Cambridge, MA (USA) PB - Cell Press KW - AGROVOC KW - Data KW - Agricultural research KW - Ontology KW - Agrifood systems N1 - Peer review; Open Access N2 - 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 UR - https://hdl.handle.net/10883/20962 DO - https://doi.org/10.1016/j.patter.2020.100105 T2 - Patterns ER -