On Data Representation and Use in a Temporal Relational Dbms

Numerous proposals for extending the relational data model to incorporate the temporaldimension of data have appeared over the past decade. It has long been known that theseproposals have adopted one of two basic approaches to the incorporation of time into theextended relational model. Recent work formally contrasted the expressive power of these twoapproaches, termed temporally ungrouped and temporally grouped, and demonstrated that thetemporally grouped models are more expressive. IN the temporally ungrouped models, thetemporal dimension is added through the addition of some number of distinguished attributes tothe schema of each relation, and each tuple is quot;stampedquot; with temporal values for these attributes.By contrast, in temporally grouped models the temporal dimension is added to the types of valuesthat serve as the domain of each ordinary attribute, and the application's schema is left intact.The recent appearance of TSQL2, a temporal extension to the SQL-92 standard based upon thetemporally ungrouped paradigm, means that it is likely that commercial DBMS's will be extendedto support time in this weaker way. Thus the distinction between these two approaches - and itsimpact on the day-to-day user of a DBMS - is of increasing relevance to the database practitionerand the database user community. In this paper we address this issue from the practicalperspective of such a user. Through a series of example queries and updates, we illustrate thedifferences between these two approaches and demonstrate that the temporally grouped approachmore adequately captures the semantics of historical data