Treffer: Introduction to the Cluster on Knowledge and Data Management

The design and analysis of efficient database management systems (DBMSs) and knowledge based systems (KBSs) is an important research area where operations research (OR) methods such as mathematical programming, stochastic modeling, and simulation have a significant role to play. To appreciate this, consider that although relational database technology is about 25 years old, it is only in the last 5 to 10 years that large organizations have started adopting relational DBMSs for critical applications, primarily because of concerns about the efficiency of relational systems. Mathematical programming models that address the significant costs of data processing, and permit OR-based performance analysis of DBMSs, are essential for making the technology more acceptable and reliable. Similarly, relatively few organizations today use KBSs for domains where the knowledge bases are large, or where response time is critical. As with DBMSs, the primary constraint is efficiency and reliability. OR methods for optimization can be used to improve the performance of these systems, and OR methods for performance analysis can help answer critical questions about their efficiency and reliability. The articles in this cluster present interesting examples of the use of OR in data and knowledge management. The articles address issues ranging from established ones such as distributed database design, query optimization, and rule processing to emerging areas such as main memory databases. INFORMS Journal on Computing , ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.