Data integration is the process that gives users access to multiple data sources though queries against a global schema. Semantic heterogeneity has been identified as the most important and toughest problem when integrating various data sources. Several approaches were proposed to deal with this problem. These approaches can be classified using three criteria: (1) data representation which means whether data of sources will be materialized in a warehouse at the integrated system level or accessed via a mediator, (2) the sense of the mapping between global and local schemas (e.g., Global as View, Local as View) and (3) the nature of the mapping (manual, semi automatic and automatic). Mapping is manual each time when ontologies are not used to make explicit data meaning. It is semi automatic when ontology and ontology mapping are defined at integration level. In this paper, we propose a fully automatic integration process based on ontologies. It supposes that each data source contains...