Temporal Semantic Assumptions and Their Use in Database Query Evaluation

Temporal data explicitly stored in a temporal database are often associated with certain semantic assumptions. Each assumption can be viewed as a way of deriving implicit information from the explicitly stored data. Rather than leaving the task of deriving (possibly in nite) implicit data to application programs, as is the case currently, it is desirable that this be handled by the database management systems. To achieve this, this paper formalizes and studies two types of semantic assumptions: point-based and interval-based. The point-based assumptions include those assumptions that use interpolation methods, while the interval-based assumptions include those that involve different temporal types (time granularities). In order to incorporate semantic assumptions into query evaluation, this paper introduces a translation procedure that converts a user query into a system query such that the answer of this system query over the explicit data is the same as that of the user query over the explicit and the implicit data. The paper also investigates the niteness (safety) of user queries and system queries.