Maria Sokhn, Elena Mugellini, Omar Abou Khaled. Querying Over Heterogeneous And Distributed Data Sources. In AWIC'7 - The 7th Atlantic Web Intelligence Conference. Volume 86 of Advances in Soft Computing series, pages 29-38, Springer, Fribourg, Switzerland, jan 2011.
The current web integrates diverse sources of heterogeneous and distributed data (XML database, relational database, Peer database within a P2P network etc.). Integrating data from multiple heterogeneous sources leads to the coexistence of different data models and consequently different query languages. Hence, there is a strong need to address the issue of handling queries over heterogeneous and distributed data. The structural and semantic heterogeneity of data makes the development of custom solutions for querying a time-consuming and complex task. In this paper we propose a query engine system, Virtual ?Ã Ã Q. The system is based on data semantic categorization concept which assigns levels of importance according to the semantic level of the data sources. This approach is referred in our paper as the ontology-based approach. The Virtual ?Ã Ã Q system aims at providing users a simple and transparent information access. This paper presents also a preliminary prototype validating the proposed architecture.