DocumentCode
1189
Title
Robust Module-Based Data Management
Author
Goasdoue, Francois ; Rousset, Marie-Christine
Author_Institution
INRIA Saclay & Lab. de Rech. en Inf. (LRI), Univ. Paris-Sud, Orsay, France
Volume
25
Issue
3
fYear
2013
fDate
Mar-13
Firstpage
648
Lastpage
661
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 w.r.t. the application under construction, and then managing a data set 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 w.r.t. 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-liteA dialect of the DL-lite family, which encompasses the foundations of the QL profile of OWL2 (i.e., DL-liteR): the W3C recommendation for efficiently managing large data sets.
Keywords
data handling; ontologies (artificial intelligence); W3C recommendation; description logics; ontology based data management system; ontology language; reference system; robust module based DMS; robust module based data management; Artificial intelligence; Data models; Knowledge management; Resource description framework; Semantic Web; Models and principles; Semantic Web; algorithms for data and knowledge management; artificial intelligence; database management; intelligent web services; personalization;
fLanguage
English
Journal_Title
Knowledge and Data Engineering, IEEE Transactions on
Publisher
ieee
ISSN
1041-4347
Type
jour
DOI
10.1109/TKDE.2011.255
Filename
6104046
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