Data warehouse evolution: consistent meta data management

Amy J. Lee, Elke A. Rundensteiner

Abstract: Large information spaces such as the WWW face the problem of how to maintain data warehouses (views) defined over information sources (ISs) whenever capabilities of these ISs change. We have developed a novel solution approach to address this problem, called the evolvable view environment (EVE). In EVE, knowledge of both the capabilities of as well as (partial) containment relationships between ISs is collected in a meta knowledge base (MKB). We describe the meta knowledge management problem and focus on issues related to the MKB evolution process. The contributions of this paper are threefold: 1) formally define consistency criteria for the MKB evolution process; 2) use PC constraint evolution to demonstrate our MKB evolution process; and 3) discuss techniques of keeping the MKB as powerful as possible by deriving and preserving minimal implicit knowledge from the affected explicit meta knowledge, before retracting the latter.