Survey on the literature of ontology mapping, alignment and merging

Abstract

Ontology Mapping, Alignment and Merging are a prominent field of research for the AI community. Indeed, an ontology is designed and developed to be shared among multiple applications and working communities. In other words, several ontologies need to be accessed by different information systems. The Mapping, Alignment or Merging of ontologies build a meta-layer that allows different applications to access the resulting ontology and then to share their informations, of course, whith preserving the semantics they contain. This later is done after solving the different forms of heterogeneity presented by the input ontologies. A key challenge is then raised by the researchers in AI community to exploit the potential of these ontological operations in several applications domain such as semantic query processing, data integration, data warehousing, E-Buziness and E-Commerce, etc. The aim of this paper is to provide the reader, who is not very familiar with the ontology domain, an introduction to the three main operations performed on ontologies. These operations provide a prominent basis for several other operations such as translation, reconciliation, coordination and negotiation between ontologies. This prominent basis is supported by the mapping discovery results between input ontologies. Design and develop such operations on ontologies, was the focus of several research communities for several years. In this paper, we have surveyed the literature of the different methods and tools for ontology mapping, alignment and merging and described the different approaches adopted by their designers after detailing the most important module (mappings discovery) and discussed the different heterogeneity forms resolved by their algorithms.