Proposition of a New Ontology-Based P2P System for Semantic Integration of Heterogeneous Data Sources

Proposition of a New Ontology-Based P2P System for Semantic Integration of Heterogeneous Data Sources

Naïma Souâd Ougouti (Université des Sciences et de la Technologie d'Oran Mohamed Boudiaf, Algeria), Hafida Belbachir (Université des Sciences et de la Technologie d'Oran Mohamed Boudiaf, Algeria) and Youssef Amghar (INSA Lyon, France)
DOI: 10.4018/978-1-5225-5384-7.ch012
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Semantic web offers new opportunities to multi-sources integration field, and many approaches like P2P systems are revisited taking into account the new requirements. In this chapter, the authors present their P2P heterogeneous and distributed data integration system. It is a super-peer system, where peers are regrouped by type of data (relational, image, text, etc.) around a super-peer which contains a domain ontology. Peers data sources are exported in a common format in the form of a semantically rich ontology. Schemas reconciliation is done by matching domain and local ontologies by the use of a similarity function whose contribution is based on the direct and indirect semantic neighborhood. Queries are described using ontologies, then routed towards relevant peers thanks to a semantic topology built on top of the existing physical one.
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State Of The Art

The vertiginous growth of Web information sources leads to revise the way of building information retrieval systems. A new idea consists on using P2P architecture that allows a very great number of connected sources and network dynamicity. Many P2P systems maintain as their principal objective to provide a semantic interoperability between several sources in the absence of a global schema. In what follows, the authors present the most important research on the topic.

Key Terms in this Chapter

Semantic Routing: This process consists of routing queries only to relevant peers. The selection of peers is performed using semantics that are extracted from peers’ content and their behavior.

Data Integration: Is the process that provides a unified view of different data sources in order to share them and give a common response to a posed query.

Ontology Alignment: Is the process of determining correspondences between concepts in different ontologies.

Ontologies: A set of concepts and relations between them representing a domain.

Semantic Web: The semantic web is an extension of the current web in which semantic is added to information in order to give a well-defined meaning to each resource and to enable computers and people to work in cooperation.

Query Management: In data integration domain, the query management is the process that permits writing a query in a common model in order to rewrite it easily in target peer vocabulary and peer local language, then return the results to the source peer.

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