Robust Module-based Data Management

François Goasdoué 1, 2 Marie-Christine Rousset 3
2 OAK - Database optimizations and architectures for complex large data
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
3 LIG Laboratoire d'Informatique de Grenoble - HADAS
LIG - Laboratoire d'Informatique de Grenoble
Abstract : The current trend for building an ontology-based data management system (DMS) is to capitalize on efforts made to design a preexisting well-established DMS (a reference system). The method amounts to extracting from the reference DMS a piece of schema relevant to the new application needs -- a module --, possibly personalizing it with extra-constraints wrt the application under construction, and then managing a dataset using the resulting schema. In this paper, we extend the existing definitions of modules and we introduce novel properties of robustness that provide means for checking easily that a robust module-based DMS evolves safely wrt both the schema and the data of the reference DMS. We carry out our investigations in the setting of description logics which underlie modern ontology languages, like RDFS, OWL, and OWL2 from W3C. Notably, we focus on the DL-lite_A dialect of the DL-lite family, which encompasses the foundations of the QL profile of OWL2 (ie DL-lite_R): the W3C recommendation for efficiently managing large datasets.
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François Goasdoué, Marie-Christine Rousset. Robust Module-based Data Management. IEEE Transactions on Knowledge and Data Engineering, Institute of Electrical and Electronics Engineers, 2013, Transactions on Knowledge and Data Engineering, 25 (3), pp.648-661. ⟨10.1109/TKDE.2011.255⟩. ⟨hal-00671004⟩

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