Food transformation process description using PO2 and FoodOn

Patrice Buche (1, 2) , Julien Cufi (3) , Stéphane Dervaux (4) , Juliette Dibie (4) , Liliana L. Ibanescu (4) , Alrick Oudot (3) , Magalie Weber (5)

1 LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
2 GRAPHIK - Graphs for Inferences on Knowledge
3 UMR IATE - Ingénierie des Agro-polymères et Technologies Émergentes
4 MIA Paris-Saclay - Mathématiques et Informatique Appliquées
5 BIA - Unité de recherche sur les Biopolymères, Interactions Assemblages

The food production and processing sector are facing sustainability challenges of growing complexity. To tackle these challenges, data and knowledge from many different domains may be structured and stored using an ontol-ogy, a semantic model. In this paper we present a core ontology designed to model processes and observations from food domains. Three datasets struc-tured according with this ontology are stored into a repository. Dedicated tools were designed to assist domain experts in integrating and querying data. Semantic integration of data from food transformation domains may enable new decision support tools for new products with good qualities and eco-friendly properties.

Keywords: food component modeling; ontology ecosystem; semantic integration; domain ontology; food transformation process; observation

Domains: Artificial Intelligence [cs.AI]

Patrice Buche, Julien Cufi, Stéphane Dervaux, Juliette Dibie, Liliana L. Ibanescu, et al.. Food transformation process description using PO2 and FoodOn. IFOW 2020 - Integrated Food Ontology Workshop @ ICBO, Sep 2020, Bolzano (virtual), Italy. ⟨hal-03013147⟩