An a Priori Approach for Automatic Integration of Heterogeneous and Autonomous Databases

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 a conceptual ontology that references a shared ontology. The mappings between a local ontology and the shared ontology is defined at database design time and also embedded in each source. This approach is implemented using PLIB-based ontologies (officially ISO 13584). It is assumed that there exists a domain ontology, but each data source may extend it by adding new concepts and properties. Therefore the shared ontology is referenced when ever it is possible. This integration approach was developed for automatic integration of component databases. It is currently prototyped in various environments including OODB, ORDB, and RDB.