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Structuring ontologies from natural language for collaborative scenario modeling in agri-food systems
Prospective studies require discussing and collaborating with the stakeholders to create scenarios of the possible evolution of the studied value-chain. However, stakeholders do not always use the same words when referring to one idea. Constructing an ontology and homogenizing vocabularies is thus c...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815793/ https://www.ncbi.nlm.nih.gov/pubmed/36620754 http://dx.doi.org/10.3389/frai.2022.1056989 |
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author | Chaib, Romy Lynn Macombe, Catherine Thomopoulos, Rallou |
author_facet | Chaib, Romy Lynn Macombe, Catherine Thomopoulos, Rallou |
author_sort | Chaib, Romy Lynn |
collection | PubMed |
description | Prospective studies require discussing and collaborating with the stakeholders to create scenarios of the possible evolution of the studied value-chain. However, stakeholders do not always use the same words when referring to one idea. Constructing an ontology and homogenizing vocabularies is thus crucial to identify key variables, which serve in the construction of the needed scenarios. Nevertheless, it is a very complex and time-consuming task. In this paper we present the method we used to manually build ontologies adapted to the needs of two complementary system-analysis models (namely the “Godet” and the “MyChoice” models), starting from interviews of the agri-food system's stakeholders. The objective of the paper is to explore whether and how prospective studies may have to gain from complementing the methodologies used (here Godet) with formal approaches from other disciplines, such as knowledge engineering (here MyChoice), which is usually not the case currently. |
format | Online Article Text |
id | pubmed-9815793 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98157932023-01-06 Structuring ontologies from natural language for collaborative scenario modeling in agri-food systems Chaib, Romy Lynn Macombe, Catherine Thomopoulos, Rallou Front Artif Intell Artificial Intelligence Prospective studies require discussing and collaborating with the stakeholders to create scenarios of the possible evolution of the studied value-chain. However, stakeholders do not always use the same words when referring to one idea. Constructing an ontology and homogenizing vocabularies is thus crucial to identify key variables, which serve in the construction of the needed scenarios. Nevertheless, it is a very complex and time-consuming task. In this paper we present the method we used to manually build ontologies adapted to the needs of two complementary system-analysis models (namely the “Godet” and the “MyChoice” models), starting from interviews of the agri-food system's stakeholders. The objective of the paper is to explore whether and how prospective studies may have to gain from complementing the methodologies used (here Godet) with formal approaches from other disciplines, such as knowledge engineering (here MyChoice), which is usually not the case currently. Frontiers Media S.A. 2022-12-22 /pmc/articles/PMC9815793/ /pubmed/36620754 http://dx.doi.org/10.3389/frai.2022.1056989 Text en Copyright © 2022 Chaib, Macombe and Thomopoulos. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Artificial Intelligence Chaib, Romy Lynn Macombe, Catherine Thomopoulos, Rallou Structuring ontologies from natural language for collaborative scenario modeling in agri-food systems |
title | Structuring ontologies from natural language for collaborative scenario modeling in agri-food systems |
title_full | Structuring ontologies from natural language for collaborative scenario modeling in agri-food systems |
title_fullStr | Structuring ontologies from natural language for collaborative scenario modeling in agri-food systems |
title_full_unstemmed | Structuring ontologies from natural language for collaborative scenario modeling in agri-food systems |
title_short | Structuring ontologies from natural language for collaborative scenario modeling in agri-food systems |
title_sort | structuring ontologies from natural language for collaborative scenario modeling in agri-food systems |
topic | Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815793/ https://www.ncbi.nlm.nih.gov/pubmed/36620754 http://dx.doi.org/10.3389/frai.2022.1056989 |
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