Articles

An ontology to consider the multiple dimensions of agri-food systems in a circular and more sustainable approach

Magalie Weber, Patrice Buche, Liliana Ibanescu, Stéphane Dervaux, Hervé Guillemin, Julien Cufi, Michel Visalli, Caroline Pénicaud, Jean-Cédric Reninger, Sophie Aubin
Published : 13 November 2025
DOI: https://doi.org/10.20870/Revue-NOVAE.2025.9752

Abstract

Faced with the challenges of the agri-food transition and the demands of sustainability, it is essential to combine data covering multiple dimensions. Today, these data are often dispersed and difficult to interconnect, limiting their exploitation and reuse. The management and opening up of scientific data is becoming essential to structure and share knowledge effectively. The construction of the PO²/TransformON ontology responds to this need by proposing an approach based on the FAIR (Easy to Find, Accessible, Interoperable and Reusable) principles and the Semantic Web. The ontology aims to organize and model data linked to the transformation processes and characterization of food and non-food products. The aim is to facilitate their sharing and exploitation by the scientific community. With this in mind, the FAIRification process is based on the development of the PO²Manager and SPO²Q software solutions. These solutions enable information to be structured as soon as it is acquired, and represented in the form of graphs searchable thanks to the Web Semantic standards RDF, OWL and SPARQL. The integration of this FAIR-compliant data in open warehouses such as Recherche Data Gouv encourages its reuse and enhancement. Ultimately, this approach opens up new perspectives, particularly in artificial intelligence and predictive modeling for decision support. The enrichment of ontologies and increased interoperability of information systems will facilitate sustainable resource management and innovation in the agri-food and environmental fields.

References

  • Allard, T., Guichard, E., Perret, B., Guillemin, H., & Pénicaud, C. (2018). Mise en relation de données relatives aux procédés de fabrication, écoconception, composition et qualité des produits laitiers à l’aide d’une base de données guidée par une ontologie. NOV’AE (Cahier des techniques), Spécial 02, 1-11. https://revue-novae.fr/article/view/8802
  • Andrés-Hernández, L., Blumberg, K., Walls, R. L., Dooley, D., Mauleon, R., Lange, M., Weber, M., Chan, L., Malik, A., Møller, A., Ireland, J., Segovia, L., Zhang, X., Burton-Freeman, B., Magelli, P., Schriever, A., Forester, S. M., Liu, L., & King, G. J. (2022). Establishing a Common Nutritional Vocabulary - From Food Production to Diet. Frontiers In Nutrition, 9, 928837. https://doi.org/10.3389/fnut.2022.928837
  • Auberger, J., Gésan-Guiziou, G., Malnoë, C., Rostain, G., Weber, M., Guillemin, H., Dervaux, S., & Pénicaud, C. (2022). Adapting MEANS-InOut LCA software to food engineering, in relation to the PO2 food ontology and PO2-BaGaTel food engineering database. 13th International Conference on Life Cycle Assessment of Food 2022 (LCA Foods 2022), Octobre 2022, Lima, Perou. https://hal.inrae.fr/hal-03837121v1
  • Aubin, S., Bernard, É., Bravo, S., Cadiou, C., Girard, A., & Weber, M. (2025). Révéler et valoriser vos données avec le thésaurus INRAE. HAL (le Centre Pour la Communication Scientifique Directe). https://doi.org/10.17180/novae-2024-no-art03
  • Bondu, C., Salles, C., Weber, M., Guichard, E., & Visalli, M. (2022). Construction of a Generic and Evolutive Wheel and Lexicon of Food Textures. Foods, 11(19), 3097. https://doi.org/10.3390/foods11193097
  • Buche, P., Cufi, J., Dervaux, S., Dibie, J., Ibanescu, L., Oudot, A., & Weber, M. (2021). How to Manage Incompleteness of Nutritional Food Sources ? International Journal Of Agricultural And Environmental Information Systems, 12(4), 1 26. https://doi.org/10.4018/ijaeis.20211001.oa4
  • Buche, P., Reau, A., Oudot, A., Sablayrolles, C., Baudrit, C., Fernandez, C., Mayer-Laigle, C., Vialle, C., Belaud, J., Cufi, J., Lhomond, L., Weber, M., Ibanescu, L., Ouaret, R., & Dervaux, S. (2024). Projet ICAM (2024-26) : Ingénierie des Connaissances et Analyse Multidimensionnelle de la Durabilité pour valoriser les données, les connaissances et l’expertise scientifique des plateformes de bioraffinerie. Séminaire chercheurs Institut Carnod 3BCAR 2024, Janvier 2024, Montpellier, France. https://hal.science/hal-04475584
  • Clés, Q., & Aubin, S. (2021). Rédiger une définition, quelques clés. Institut national de la recherche pour l’agriculture, l’alimentation et l’environnement. HAL (le Centre Pour la Communication Scientifique Directe). https://doi.org/10.15454/93xg-p646
  • Cortesi, A., Dijoux, L., Bris, G. Y., & Pénicaud, C. (2022a). Data related to the life cycle assessment of 44 artisanally produced french protected designation of origin (PDO) cheeses. Data In Brief, 43, 108403. https://doi.org/10.1016/j.dib.2022.108403
  • Cortesi, A., Dijoux, L., Bris, G. Y., & Pénicaud, C. (2022b). Explaining the Differences between the Environmental Impacts of 44 French Artisanal Cheeses. Sustainability, 14(15), 9484. https://doi.org/10.3390/su14159484
  • Dervaux, S., Cufi, J., Guillemin, H., Weber, M., Ibanescu, L., Oudot, A., & Buche, P. (2024a). Simple PO2 Query (SPO2Q), a querying tool to retrieve biomass transformation and characterization itineraries using the Process and Observation (PO2) Ontology, 2024. https://hal.science/hal-04501660
  • Dervaux, S., Guillemin, H., Cufi, J., Buche, P., Weber, M., & Ibanescu, L. (2023). PO2 Manager, an annotation tool to edit biomass transformation and characterization itineraries using the Process and Observation (PO2) Ontology. https://hal.science/hal-04313202
  • Dervaux, S., Guillemin, H., Cufi, J., Buche, P., Weber, M., Ibanescu, L., & Oudot, A. (2024b). PO2 Engine, an application programming interface associated with the Process and Observation (PO2) software ecosystem, 2024. https://hal.science/hal-04387669
  • Dooley, D., Andres-Hernandez, L., Bordea, G., Carmody, L., Cavalieri, D., Chan, L., Castellano-Escuder, P., Lachat, C., Mougin, F., Vitali, F., Yang, C., Weber, M., McGinty, H. K., & Lange, M. (2024). OBO Foundry food ontology interconnectivity. Semantic Web, 15(4), 1239 1258. https://doi.org/10.3233/sw-233458
  • Dooley, D. M., Griffiths, E. J., Gosal, G. S., Buttigieg, P. L., Hoehndorf, R., Lange, M. C., Schriml, L. M., Brinkman, F. S. L., & Hsiao, W. W. L. (2018). FoodOn : a harmonized food ontology to increase global food traceability, quality control and data integration. Npj Science Of Food, 2(1), 23. https://doi.org/10.1038/s41538-018-0032-6
  • Fabre, C., Buche, P., Rouau, X., & Mayer-Laigle, C. (2020). Milling itineraries dataset for a collection of crop and wood by-products and granulometric properties of the resulting powders. Data In Brief, 33, 106430. https://doi.org/10.1016/j.dib.2020.106430
  • Guichard, E., Thomas-Danguin, T., Buchin, S., Perret, B., Guillemin, H., Pénicaud, C., & Salles, C. (2021a). Compilation of data on model cheeses composition, rheological and sensory properties, from six research projects exported from the BaGaTel database. Data In Brief, 36, 106971. https://doi.org/10.1016/j.dib.2021.106971
  • Guichard, E., Thomas-Danguin, T., Buchin, S., Perret, B., Guillemin, H., Pénicaud, C., & Salles, C. (2021b). Relationships between cheese composition, rheological and sensory properties highlighted using the BaGaTel database. International Dairy Journal, 118, 105039. https://doi.org/10.1016/j.idairyj.2021.105039
  • Ibanescu, L., Dibie-Barthelemy, J., Dervaux, S., Guichard, E., & Raad, J. (2016). PO2. A Process and Observation Ontology in Food Science. Application to Dairy Gels. MTSR. 155-165. https://doi.org/10.1007/978-3-319-49157-8_13
  • Münch, M., Buche, P., Dervaux, S., Dibie, J., Ibanescu, L., Manfredotti, C., Wuillemin, P., & Angellier-Coussy, H. (2022a). Combining ontology and probabilistic models for the design of bio-based product transformation processes. Expert Systems With Applications, 203, 117406. https://doi.org/10.1016/j.eswa.2022.117406
  • Münch, M., Buche, P., Manfredotti, C., Wuillemin, P., & Angellier-Coussy, H. (2022b). Une approche d’ingénierie inverse combinant ontologies et modèles relationnels probabilistes : application aux emballages bio-composites. IC@PFIA 2022 - Plate-Forme Intelligence Artificielle, Juin 2022, Saint-Etienne, France. https://hal.science/hal-03682416
  • Münch, M., Buche, P., Manfredotti, C., & Wuillemin, P. H. (2022c). Formalising contextual expert knowledge for causal discovery in linked knowledge graphs about transformation processes : application to processing of bio-composites for food packaging. International Journal Of Metadata Semantics And Ontologies, 16(1), 1 15. https://doi.org/10.1504/ijmso.2022.131129
  • Pénicaud, C., Ibanescu, L., Allard, T., Fonseca, F., Dervaux, S., Perret, B., Guillemin, H., Buchin, S., Salles, C., Dibie, J., & Guichard, E. (2019). Relating transformation process, eco-design, composition and sensory quality in cheeses using PO2 ontology. International Dairy Journal, 92, 1 10. https://doi.org/10.1016/j.idairyj.2019.01.003
  • Poveda-Villalón, M., Fernández-Izquierdo, A., Fernández-López, M., & García-Castro, R. (2022). LOT : An industrial oriented ontology engineering framework. Engineering Applications Of Artificial Intelligence, 111, 104755. https://doi.org/10.1016/j.engappai.2022.104755
  • Visalli, M., Schlich, P., Mahieu, B., Thomas, A., Weber, M., & Guichard, E. (2022). First steps towards FAIRization of product-focused sensory data. Food Quality And Preference, 104, 104765. https://doi.org/10.1016/j.foodqual.2022.104765
  • Weber, M., Buche, P., Ibanescu, L., Dervaux, S., Guillemin, H., Cufi, J., Visalli, M., Guichard, E., & Pénicaud, C. (2023). PO2/TransformON, an ontology for data integration on food, feed, bioproducts and biowaste engineering. Npj Science Of Food, 7(1), 47. https://doi.org/10.1038/s41538-023-00221-2
  • Weber, M., Duclos, F., Guillemin, H., Dervaux, S., Cufi, J., & Visalli, M. (2025). ConsomON, an ontology for structuring knowledge and modeling consumer food behavior. Joint Ontology Workshops (JOWO) - Episode XI: The Sicilian Summer under the Etna, co-located with the 15th International Conference on Formal Ontology in Information Systems (FOIS 2025), IFOW- Integrated Food Ontology Workshop, Sep 2025, Catania, Italy. https://hal.inrae.fr/hal-05146634v2
  • Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., Da Silva Santos, L. B., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., … Mons, B. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3(1), 160018. https://doi.org/10.1038/sdata.2016.18

Authors

Magalie Weber

magalie.weber@inrae.fr

Affiliation : INRAE, UR BIA, 44316, Nantes, France

Country : France

Patrice Buche

Affiliation : INRAE, UMR IATE, 34060 Montpellier, France

Country : France

Liliana Ibanescu

Affiliation : Université Paris-Saclay, AgroParisTech, INRAE, UMR MIA Paris-Saclay, 91120, Palaiseau, France

Country : France

Stéphane Dervaux

Affiliation : Université Paris-Saclay, AgroParisTech, INRAE, UMR MIA Paris-Saclay, 91120, Palaiseau, France

Country : France

Hervé Guillemin

Affiliation : INRAE, UMR PAM, Site de Poligny, 21000, Dijon, France

Country : France

Julien Cufi

Affiliation : INRAE, Département TRANSFORM, UMR IATE, 34060 Montpellier, France

Country : France

Michel Visalli

Affiliation : INRAE, PROBE, Plateforme ChemoSens, UMR CSGA, 21000, Dijon, France

Country : France

Caroline Pénicaud

Affiliation : Université Paris-Saclay, INRAE, AgroParisTech, UMR SayFood, 91120, Palaiseau, France

Country : France

Jean-Cédric Reninger

Affiliation : ANSES, 94701, Maisons-Alfort, France

Country : France

Sophie Aubin

Affiliation : INRAE, DipSO, 49007, Angers, France

Country : France

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