Semantic assumptions and query evaluation in temporal databases

When querying a temporal database, a user often makes certain semantic assumptions on stored temporal data. 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). Each assumption is viewed as a way to derive certain implicit data from the explicit data stored in the database. The database system must use all explicit as well as (possibly infinite) implicit data to answer user queries. This paper introduces a new method to facilitate such query evaluations. A user query is translated 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 gives such a translation procedure and studies the properties (safety in particular) of user queries and system queries.