TEMPORAL SPECIALIZATION AND GENERALIZATION

A standard relation has two dimensions: attributes and tuples. A tempo ral relation contains two additional orthogonal time dimensions, namel y, valid time and transaction time. Valid time records when facts are true in the modeled reality, and transaction time records when facts a re stored in the temporal relation. Although, in general, there are no restrictions between the valid time and transaction time associated w ith each fact, in many practical applications, the valid and transacti on times exhibit more or less restricted interrelationships that defin e several types of specialized temporal relations. The paper examines five different areas where a variety of types of specialized temporal relations are present. In application systems with multiple, interconn ected temporal relations, multiple time dimensions may be associated w ith facts as they pow from one temporal relation to another. For examp le, a fact may have an associated transaction time indicating when it was stored in a previous temporal relation. The paper investigates sev eral aspects of the resulting generalized temporal relations, includin g the ability to query a predecessor relation from a successor relatio n. The presented framework for generalization and specialization allow s researchers as well as database and system designers to precisely ch aracterize, compare, and thus better understand temporal relations and the application systems in which they are embedded. The framework's c omprehensiveness and its use in understanding temporal relations are d emonstrated by placing previously proposed temporal data models within the framework. The practical relevance of the defined specializations and generalizations is illustrated by sample realistic applications i n which they occur. The additional semantics of specialized relations are especially useful for improving the performance of query processin g.