RDF data evolution: efficient detection and semantic representation of changes

Nathalie Pernelle (1, 2) , Fatiha Saïs (2, 1) , Daniel Mercier (2) , Sujeeban Thuraisamy (2)

1 LaHDAK - LRI - Données et Connaissances Massives et Hétérogènes (LRI)
2 LRI - Laboratoire de Recherche en Informatique

Many RDF data sources are constantly changing for both data and vocabulary (ontology) levels. Many integration tasks are impacted by these changes. In this context, it is important to develop approaches to detect and represent these changes. Many studies have focused on the detection , the representation and the management of changes at the ontology level. In this paper, we present an approach which allows to detect and represent elementary and complex changes that can be detected when we focus only on the data level. A first experiment was conducted on di↵er-ent versions of DBpedia.

Keywords: CCS Concepts •Information systems ! Information integration; Keywords Data evolution; Data changes; RDF; Ontologies

Domains: Artificial Intelligence [cs.AI]

Nathalie Pernelle, Fatiha Saïs, Daniel Mercier, Sujeeban Thuraisamy. RDF data evolution: efficient detection and semantic representation of changes. Semantic Systems - SEMANTiCS2016, Sep 2016, Leipzig, Germany. 4 p., Proceedings of the Posters and Demos Track of the 12th International Conference on Semantic Systems - SEMANTiCS2016. ⟨10.1145/1235⟩. ⟨hal-01476021⟩