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The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems.


ABSTRACT: 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.

SUBMITTER: Arnaud E 

PROVIDER: S-EPMC7660444 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems.

Arnaud Elizabeth E   Laporte Marie-Angélique MA   Kim Soonho S   Aubert Céline C   Leonelli Sabina S   Miro Berta B   Cooper Laurel L   Jaiswal Pankaj P   Kruseman Gideon G   Shrestha Rosemary R   Buttigieg Pier Luigi PL   Mungall Christopher J CJ   Pietragalla Julian J   Agbona Afolabi A   Muliro Jacqueline J   Detras Jeffrey J   Hualla Vilma V   Rathore Abhishek A   Das Roma Rani RR   Dieng Ibnou I   Bauchet Guillaume G   Menda Naama N   Pommier Cyril C   Shaw Felix F   Lyon David D   Mwanzia Leroy L   Juarez Henry H   Bonaiuti Enrico E   Chiputwa Brian B   Obileye Olatunbosun O   Auzoux Sandrine S   Yeumo Esther Dzalé ED   Mueller Lukas A LA   Silverstein Kevin K   Lafargue Alexandra A   Antezana Erick E   Devare Medha M   King Brian B  

Patterns (New York, N.Y.) 20200925 7


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 ont  ...[more]

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