dc.date2021-02-12T21:13:41Z
dc.date2021-02-12T21:13:41Z
dc.date2020
dc.date.accessioned2023-07-17T20:07:01Z
dc.date.available2023-07-17T20:07:01Z
dc.identifierhttps://hdl.handle.net/10883/21255
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7513041
dc.descriptionConvention: 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.
dc.descriptionPresentations: 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.
dc.descriptionCéline Aubert
dc.descriptionSoohno Kim
dc.descriptionXingyi Song
dc.descriptionGideon Kruseman
dc.descriptionMark van Wijk
dc.descriptionElizabeth Arnaud
dc.descriptionVideo also available in YouTube: https://www.youtube.com/watch?v=9Mh-puDJYSY
dc.description97:11 min.
dc.formatMP4
dc.languageEnglish
dc.publisherCGIAR Plataform for Big Data in Agriculture
dc.rightsOpen Access
dc.rightsCreative 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.
dc.subjectAGRICULTURAL SCIENCES AND BIOTECHNOLOGY
dc.subjectONTOLOGY
dc.subjectMACHINE LEARNING
dc.subjectDATA
dc.titleRHoMIS, SEONT and OIMS: how do we progress and digitally connect these elements?
dc.typeVideo
dc.typeAccepted Version
dc.coverageFrance


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