Extraction of Data Dependencies

Relational database schemas must be semantically enriched to reflect knowledge about the data, as needed by many applications. One technique is the analysis of the database extension, extracting existing data dependencies. In this paper, new algorithms to extract functional and inclusion dependencies are presented; they are designed to minimize the number of disk accesses. 1. Introduction The relational data model has gained lots of popularity during the last years, one key factor for this success being the simplicity of its structure. However, the price for this simplicity is its being almost devoid of semantics. In the relational model, semantics are specified not in the structure, but thru constraints. Data dependencies are one kind of these constraints, where functional and inclusion dependencies [6, 9] are of particular interest. Nowadays relational databases are spread everywhere, and many applications like reverse engineering, integrated access for interoperable databases, know..