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RHoMIS, SEONT and OIMS: how do we progress and digitally connect these elements?

Year: 2020
URI: https://hdl.handle.net/10883/21255
Format: MP4
Language: English
Publisher: CGIAR Plataform for Big Data in Agriculture
Type: Video
Place of Publication: France
Description: Convention: Digital Dynamism for Adaptive Food Systems, 19-23 October 2020. During this cross-CoP meeting with the Socio-economic data CoP we learnt about the advancements of the SEONT ontology, the extraction of concepts for SEONT using Machine Learning, discovered OIMS and discussed how to integrate these elements with RHoMIS.
Description: Presentations: The progress of socio-economic ontology; Machine LEarning Extraction of the Concepts; OIMS and Rural Household Multi Indicator Survey (RHoMIS): link to ontology work in the Big Data Platform.
Personages: Céline Aubert
Personages: Soohno Kim
Personages: Xingyi Song
Personages: Gideon Kruseman
Personages: Mark van Wijk
Personages: Elizabeth Arnaud
Agrovoc: ONTOLOGY
Agrovoc: MACHINE LEARNING
Agrovoc: DATA
Access Rights: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International § CIMMYT manages Intellectual Assets as International Public Goods. In case you want to make non-exclusive commercial use of this item or you want to adapt it in any manner and use such adaptation, please contact cimmyt-knowledge-center@cgiar.org indicating the code/name of this item and the kind of use you intend; CIMMYT will contact you with the terms and conditions for such use.
Notes: Video also available in YouTube: https://www.youtube.com/watch?v=9Mh-puDJYSY
Corporative Creator: CGIAR Platform for Big Data in Agriculture
Duration: 97:11 min.


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