Temporal extensions to the relational data model

Database designers have devoted considerable attention in the past few years to developing database systems which incorporate the temporal dimension. The relational data model is a popular model for standard snapshot database design. The popularity of the relational data model has made it the focus of considerable effort in the development of techniques to integrate the temporal dimension into database systems. We have developed a new set-valued temporal logic. This temporal logic provided the foundation for the development of both a temporal relational calculus query language and a temporal relational algebra query language. Both query languages are efficient, elegant, and can be incorporated in most temporal relational data models.; To provide a more complete integration of the temporal domain, we have extended the standard view mechanism to the temporal relational data model. We have developed definitions for three types of temporal views. We have developed an algorithm for handling the maintenance of the view relations as the underlying base relation experiences updates as well as an algorithm for reflecting view level updates back into the base relation. Support for hypothetical temporal relations has also been developed.; Database systems which model real-world situations should incorporate reality as closely as possible. Many situations involve an imprecise knowledge of when events have happened or will happen. To integrate this temporal imprecision into the temporal relational data model, we have developed a fuzzy temporal logic which handles temporal intervals in which the temporal values are not well defined. The temporal fuzzy logic is a generalized temporal logic. The non-fuzzy temporal logic is shown to be a special case of the fuzzy logic in which all time points are well-defined. Our fuzzy temporal logic can provide a framework for temporal database systems which more accurately model the real world.