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Ontology Extraction from Relational Schemata
Details
Describing relational data sources by means of ontologies constitutes the foundation of most of the semantic based approaches to data access and integration. In this work we introduce an automatic procedure for building ontologies starting from the integrity constraints present in the relational sources. The use of a conceptual model to describe relational data sources has been proved to be extremely useful to overcome many important data access problems. However, the task of wrapping relational data sources by means of ontology is mainly done manually. In this work we introduce an automatic procedure for extracting a conceptual view from a relational database. In order to represent the extracted ontology we adopt a variant of the DLR-Lite description logic because of its ability to express the mostly used modelling constraints, and its nice computational properties. The connection with the relational data sources is captured by means of sound views. Moreover, the adoption of this formal language enables us to prove that the extracted ontologies preserve the semantics of the integrity constraints in the relational sources. Therefore, there is no data loss.
Autorentext
Mohammed Mahmudur Rahman received the B.Sc degree in Computer Science & Engineering from International Islamic University Chittagong (IIUC), in 2005, and M.Sc degree in Computing System Engineering from Politecnico di Milano in 2011 with ISU scholarship. Now, He is working as a Lecturer in the department of Computer Science and Engineering at IIUC.
Weitere Informationen
- Allgemeine Informationen
- Sprache Englisch
- Herausgeber LAP LAMBERT Academic Publishing
- Gewicht 107g
- Untertitel Description logic, Extraction, Ontology, Relational Schemata, SPARQL
- Autor Mohammed Mahmudur Rahman
- Titel Ontology Extraction from Relational Schemata
- Veröffentlichung 27.07.2012
- ISBN 3659198595
- Format Kartonierter Einband
- EAN 9783659198595
- Jahr 2012
- Größe H220mm x B150mm x T4mm
- Anzahl Seiten 60
- Auflage Aufl.
- GTIN 09783659198595