SEONT: Semantics & mapping exercise to add structure to messy socio-economic data

Webinar- SEONT, the Socio-Economic Ontology

dc.date2021-02-12T21:41:44Z
dc.date2021-02-12T21:41:44Z
dc.date2020
dc.date.accessioned2023-07-17T20:07:01Z
dc.date.available2023-07-17T20:07:01Z
dc.identifierhttps://hdl.handle.net/10883/21256
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7513042
dc.descriptionThis session is the fifth webinar of the series: All about our products and their uses, organised by the Ontologies Community of Practice. During this webinar, Gideon Kruseman and Soohno Kim guide us in the conception, development and content of SEONT, the Socio-Economic Ontology built by the CGIAR and partners to annotate agricultural household surveys. Xingyi Song presents the machine learning tool, based on natural language processing, developed by the University of Sheffield to extract SEONT terms from 100 core socio-economic questions. Finally, Berta Miro closes the webinar by unfolding a story about annotating CGIAR survey data using SEONT and other ontologies via the machine learning tool developed by the University of Sheffield.
dc.descriptionCéline Aubert
dc.descriptionGideon Kruseman
dc.descriptionSoohno Kim
dc.descriptionXingyi Song
dc.descriptionBerta Miro
dc.descriptionElizabeth Arnaud
dc.descriptionVideo also available in YouTube: https://youtu.be/gGqTIN4Cx0Q
dc.description1:15:03
dc.formatMP4
dc.languageEnglish
dc.publisherCGIAR Platform 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.subjectWebinar
dc.subjectSocioeconomic Data
dc.subjectStandardization
dc.subjectBig Data
dc.subjectONTOLOGY
dc.subjectMACHINE LEARNING
dc.subjectDATA
dc.subjectAGRICULTURAL RESEARCH
dc.subjectDATA ANALYSIS
dc.subjectSTANDARDIZING
dc.subjectSURVEYS
dc.titleSEONT: Semantics & mapping exercise to add structure to messy socio-economic data
dc.titleWebinar- SEONT, the Socio-Economic Ontology
dc.typeVideo
dc.typeAccepted Version
dc.coverageFrance


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