A Formal Model of Dynamic Identification of Correspondence Assertions for E-Commerce Data Integration

Data integration involves merging two or more schemas into a global schema based on the identification of common concepts, and also the set of different concepts that are mutually related by some semantic properties. Identifying semantic relationships that exist between a set of objects in one schema and a different set of objects in another schema is crucial to the integration process. Earlier integration strategies depend on significant manual input from the users and the ingenuity of the database administrators (DBAs) for the identification and declaration of correspondence assertions. We argue that it would be exceedingly difficult for users / DBAs to identify, declare, and specify the assertions that exist between objects, especially a mapping between two different attributes, for all attributes in the local databases. In this paper, we design an integration algorithm that leverages a simple semistructured data model and a common ontology to dynamically identify correspondence assertions. We exploit set theory and logic to formally specify the assertions. We show how different users across diverse platforms can query the global integrated schema.