Data Cleaning and Semantic Improvement in Biological Databases

Public genomic and proteomic databases can be affected by a variety of errors. These errors may involve either the description or the meaning of data (namely, syntactic or semantic errors). We focus our analysis on the detection of semantic errors, in order to verify the accuracy of the stored information. In particular, we address the issue of data constraints and functional dependencies among attributes in a given relational database. Constraints and dependencies show semantics among attributes in a database schema and their knowledge may be exploited to improve data quality and integration in database design, and to perform query optimization and dimensional reduction.