Title: Semantic integration of traditional and heterogeneous data sources (UML, XML and RDB) in OWL2 triplestore

Authors: Oussama El Hajjamy; Hajar Khallouki; Larbi Alaoui; Mohamed Bahaj

Addresses: Laboratory LITEN, University Hassan 1, 26000 Settat, Morocco; TIC Research Laboratory, International University of Rabat, 11100, Sala Al Jadida, Morocco ' Laboratory LITEN, University Hassan 1, 26000 Settat, Morocco; TIC Research Laboratory, International University of Rabat, 11100, Sala Al Jadida, Morocco ' Laboratory LITEN, University Hassan 1, 26000 Settat, Morocco; TIC Research Laboratory, International University of Rabat, 11100, Sala Al Jadida, Morocco ' Laboratory LITEN, University Hassan 1, 26000 Settat, Morocco; TIC Research Laboratory, International University of Rabat, 11100, Sala Al Jadida, Morocco

Abstract: With the success of the internet and the expansion of the amount of data in the web, the exchange of information from various heterogeneous and classical data sources becomes a critical need. In this context, researchers must propose integration solutions that allow applications to simultaneously access several data sources. In this perspective, we propose a semi-automatic integration approach of classical data sources via a global schema located in database management systems of RDF or OWL data, called triplestore. Our contribution is subdivided into three axes: 1) an automatic mapping solution that converts classical data sources such as UML, XML and RDB to local ontologies based on OWL2 language; 2) an alignment system of local ontologies based on syntactic, semantic and structural similarity measurement techniques in order to increase the probability of having real correspondences and real differences; 3) a fusion system of pre-existing local ontologies into a global ontology based on the alignment found in the previous step.

Keywords: semantic integration; UML; XML; RDB; semantic web; OWL2; RDF; triplestore; ontologies; mapping; alignment; fusion.

DOI: 10.1504/IJDATS.2021.114667

International Journal of Data Analysis Techniques and Strategies, 2021 Vol.13 No.1/2, pp.36 - 58

Received: 09 Nov 2018
Accepted: 05 Mar 2019

Published online: 23 Apr 2021 *

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