BIG DATA Ontologies Community of Practice – Work Plan 2019
CGSpace
View Archive InfoField | Value | |
Title |
BIG DATA Ontologies Community of Practice – Work Plan 2019
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Creator |
CGIAR Platform for Big Data in Agriculture
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Subject |
big data
agricultural research ontology report data interoperability |
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Description |
Given the multi-disciplinary nature of the CGIAR Big Data For Agriculture, the Ontologyies Community of Practice (CoP) will span the knowledge domains of importance for the platform with the objective of establishing best practices, guidelines in the selection, use and application of semantics for data harmonization at the collect and storage levels, for data interoperability and data discovery following the FAIR principles. In 2019, as discussed during the Convention, the CoP will put in place thematic interest groups reflecting the science domains that the ontologies should address to support integration and interoperability of data ( F.A.I.R) : livestock ontology if the Livestock CoP decides to adopt the idea, a Fish ontology, Socio-economic ontology, Plant ontologies, Agronomy Ontology, Water Management ontology. Selection of most used ontologies in agriculture will be performed by the members of the CoP. Guidance to the creation of the working groups will be provided by the CGIAR Ontology Working Group chaired by Bioveristy and IFPRI. The CoP will contribute to the project on 'architecture for decision farming' . Big Data Objectives included in MARLO will be mapped to SDG Interface Ontology to support the monitoring framework. Communication activities will be strengthened. Ontology sessions will be organized during the 2019 Convention to communicate about the prodcuts, progress on the activities and plan priorites for the following year.Communication products will be produced. |
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Date |
2019
2019-06-13T21:09:20Z 2019-06-13T21:09:20Z |
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Type |
Internal Document
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Identifier |
BIG DATA (2019). BIG DATA Ontologies Community of Practice – Work Plan. CGIAR Platform for Big Data in Agriculture, 30 p.
https://hdl.handle.net/10568/101569 |
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Language |
en
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Rights |
CC-BY-4.0
Open Access |
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Format |
30 p.
application/pdf |
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Publisher |
CGIAR Platform for Big Data in Agriculture
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