Ontology-based integration of heterogeneous, incomplete and imprecise data dedicated to a decision support system in food safety

Patrice Buche (1) , Sandrine Contenot (2) , Lydie Soler (3) , Juliette Dibie-Barthelemy (3) , David Doussot (4) , Gaëlle Hignette (4) , Liliana Ibanescu (3)

1 UMR IATE - Ingénierie des Agro-polymères et Technologies Émergentes
2 CTIG - Centre de Traitement de l'Information Génétique
3 MIA-Paris - Mathématiques et Informatique Appliquées
4 AgroParisTech

This chapter presents an application in the field of food safety using an ontology-based data integration approach. An ontology is a vocabulary used to express the knowledge in a given domain of application. In this chapter, the ontology-based data integration approach permits to homogenize data sources which are heterogeneous in terms of structure and vocabulary. This approach is done in the framework of theSemantic Web, an international initiative which proposes annotating data sources using ontologies in order to manage them more efficiently. In this chapter, the authors explore three ways to integrate data according to a domain ontology: (1) a semantic annotation process to extend local data with Web data which have been semantically annotated according to a domain ontology, (2) a flexible querying system to query uniformly both local data and Web data and (3) an ontology alignment process to find correspondences between data from two sources indexed by distinct ontologies.

Mots clés: data integration; ontology; intelligence artificielle; informatique

Domaines: Sciences du Vivant [q-bio]

Patrice Buche, Sandrine Contenot, Lydie Soler, Juliette Dibie-Barthelemy, David Doussot, et al.. Ontology-based integration of heterogeneous, incomplete and imprecise data dedicated to a decision support system in food safety. Data Warehousing Design and Advanced Engineering Applications: Methods for Complex Construction, IGI Global, 336 p., 2009, 9781605667560. ⟨10.4018/978-1-60566-756-0.ch005⟩. ⟨hal-01123454⟩