The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems.
The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems.
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DOI：
10.1016/j.patter.2020.100105
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发表时间：
2020-10-09
期刊：
影响因子：
--
通讯作者：
King B
中科院分区：
文献类型：
--
作者：
Arnaud E;Laporte MA;Kim S;Aubert C;Leonelli S;Miro B;Cooper L;Jaiswal P;Kruseman G;Shrestha R;Buttigieg PL;Mungall CJ;Pietragalla J;Agbona A;Muliro J;Detras J;Hualla V;Rathore A;Das RR;Dieng I;Bauchet G;Menda N;Pommier C;Shaw F;Lyon D;Mwanzia L;Juarez H;Bonaiuti E;Chiputwa B;Obileye O;Auzoux S;Yeumo ED;Mueller LA;Silverstein K;Lafargue A;Antezana E;Devare M;King B
可持续全球农业和农业食品系统研究产生的异构和多学科数据需要高质量的数据标记或注释，以便互操作。根据FAIR原则的建议，数据、标签和元数据必须使用受控词汇表和本体，这些词汇表和本体在知识领域中很流行，并且被社区普遍使用。尽管生命科学中存在健壮的本体论，但目前还没有一套全面的本体论推荐用于跨农业研究学科的数据注释。在本文中，我们讨论了CGIAR农业大数据平台的本体实践社区（CoP）在利用本体开发的相关专业知识和确定支持高质量数据注释的创新解决方案方面的附加价值。ontology CoP促进利益相关者之间的知识共享，例如研究人员、数据管理人员、领域专家、本体设计专家和平台开发团队。公平的农业数据必须使用知识领域中流行的本体CGIAR本体实践共同体拥有农业数据注释的专业知识共同体选择创新的解决方案来帮助用本体进行数据注释共同体为农业数据开发多学科开源本体农业和农业食品系统研究中的数字技术使用加速了多学科数据的生产，这些数据跨越了基因学，环境、农业生态学、生物学和社会经济学。通过将受控词汇表组织成有意义且计算机可读的知识领域（称为本体），数据的高质量标记确保了数据的在线可查找性、可重用性、互操作性和可靠的解释。目前还没有一整套推荐的农业研究本体，因此数据科学家、数据管理人员和数据库开发人员很难找到经过验证的术语。CGIAR农业大数据平台的本体实践社区利用知识表示和本体开发方面的国际专业知识来生成缺失的本体，确定最佳实践，并指导管理多学科信息平台的团队进行数据标记，以发布支持研究影响证据的FAIR数据。数字技术在农业和食品科学领域的应用加速了大量多学科数据的产生。CGIAR农业大数据平台的本体实践社区（CoP）利用国际本体专业知识，可以指导管理多学科农业信息平台的团队提高数据的互操作性和可重用性。CoP开发并促进了本体，以支持跨领域的高质量数据标记，例如农学本体、作物本体、环境本体、植物本体和社会经济本体。
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. FAIR agricultural data must use ontologies that are popular in the knowledge domain CGIAR Ontologies Community of Practice holds expertise for agricultural data annotation The Community selects innovative solutions to assist the data annotation with ontologies The Community develops multidisciplinary open-source ontologies for agricultural data 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. The deployment of digital technology in Agriculture and Food Science accelerates the production of large quantities of multidisciplinary data. The Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture harnesses the international ontology expertise that can guide teams managing multidisciplinary agricultural information platforms to increase the data interoperability and reusability. The CoP develops and promotes ontologies to support quality data labeling across domains, e.g., Agronomy Ontology, Crop Ontology, Environment Ontology, Plant Ontology, and Socio-Economic Ontology.
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影响因子：
14.9
作者：
The Gene Ontology Consortium
通讯作者：
The Gene Ontology Consortium
影响因子：
1.9
作者：
Buttigieg PL;Morrison N;Smith B;Mungall CJ;Lewis SE;ENVO Consortium
通讯作者：
ENVO Consortium
影响因子：
14.9
作者：
Federhen S
通讯作者：
Federhen S
影响因子：
1.9
作者：
Buttigieg PL;Pafilis E;Lewis SE;Schildhauer MP;Walls RL;Mungall CJ
通讯作者：
Mungall CJ
影响因子：
4.9
作者：
Cooper L;Walls RL;Elser J;Gandolfo MA;Stevenson DW;Smith B;Preece J;Athreya B;Mungall CJ;Rensing S;Hiss M;Lang D;Reski R;Berardini TZ;Li D;Huala E;Schaeffer M;Menda N;Arnaud E;Shrestha R;Yamazaki Y;Jaiswal P
通讯作者：
Jaiswal P