Cross-Querying LOD Datasets Using Complex Alignments: An Application to Agronomic Taxa (regular paper)

Elodie Thiéblin (1) , Fabien Amarger (1) , Nathalie Jane Hernandez (1, 2) , Catherine Roussey (3) , Cassia Trojahn dos Santos (1, 2)

1 IRIT-MELODI - MEthodes et ingénierie des Langues, des Ontologies et du DIscours
2 UT2J - Université Toulouse - Jean Jaurès
3 IRSTEA - Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture

Farmers have new information needs to change their agricultural practices. The Linked Open Data is a considerable source of knowledge, separated into several heterogeneous and complementary datasets. This paper presents a process to query LOD datasets from a known ontology using complex alignments. The approach was applied on AgronomicTaxon, a taxonomic classification ontology, to query Agrovoc and DBpedia.

Mots clés: Query Rewriting; Complex Alignments; Linked Open Data; Agronomic Sources

Domaines: Intelligence artificielle [cs.AI]

Elodie Thiéblin, Fabien Amarger, Nathalie Jane Hernandez, Catherine Roussey, Cassia Trojahn dos Santos. Cross-Querying LOD Datasets Using Complex Alignments: An Application to Agronomic Taxa (regular paper). 11th International Conference on Metadata and Semantics Research (MTSR 2017), Nov 2017, Tallinn, Estonia. pp.25-37, ⟨10.1007/978-3-319-70863-8_3⟩. ⟨hal-02102384⟩