RHoMIS, SEONT and OIMS: how do we progress and digitally connect these elements?
Channel: Ontologies In Agriculture
Date: 20/10/2020

During this cross-CoP meeting with the Socio-economic data CoP (https://bigdata.cgiar.org/communities-of-practice/socio-economic-data/) 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.

Tools mentionned:
- SEONT: https://github.com/AgriculturalSemantics/SEONT?mc_cid=df978c232f&mc_eid=4c55a33775
- 100Q: https://bigdata.cgiar.org/blog-post/100q-boosting-household-survey-data-usability-with-100-core-questions/?mc_cid=df978c232f&mc_eid=4c55a33775
- RHoMIS: https://www.rhomis.org/


Speakers:
- Soohno Kim, senior data manager at IFPRI;
- Xingyi Song, research associate in NLP at the University of Sheffield;
- Gideon Kruseman, foresight and ex-ante research leader at CIMMYT;
- Mark van Wijk, senior scientist at ILRI.

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