Dataset Information

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]

PMID: 33205138

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Project description:In 2017-2018, a group of international development funding agencies launched the Crops to End Hunger initiative to modernize public plant breeding in lower-income countries. To inform that initiative, USAID asked the International Food Policy Research Institute and the United States Department of Agriculture's Economic Research Service to estimate the impacts of faster productivity growth for 20 food crops on income and other indicators in 106 countries in developing regions in 2030. We first estimated the value of production in 2015 for each crop using data from FAO. We then used the IMPACT and GLOBE economic models to estimate changes in the value of production and changes in economy-wide income under scenarios of faster crop productivity growth, assuming that increased investment will raise annual rates of yield growth by 25% above baseline growth rates over the period 2015-2030. We found that faster productivity growth in rice, wheat and maize increased economy-wide income in the selected countries in 2030 by 59 billion USD, 27 billion USD and 21 billion USD respectively, followed by banana and yams with increases of 9 billion USD each. While these amounts represent small shares of total GDP, they are 2-15 times current public R&D spending on food crops in developing countries. Income increased most in South Asia and Sub-Saharan Africa. Faster productivity growth in rice and wheat reduced the population at risk of hunger by 11 million people and 6 million people respectively, followed by plantain and cassava with reductions of about 2 million people each. Changes in adequacy ratios were relatively large for carbohydrates (already in surplus) and relatively small for micronutrients. In general, we found that impacts of faster productivity growth vary widely across crops, regions and outcome indicators, highlighting the importance of identifying the potentially diverse objectives of different decision makers and recognizing possible tradeoffs between objectives.

Dataset Information

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

Publications

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

Similar Datasets

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