Using temporal hierarchies to efficiently maintain large temporal databases

Many real-world applications involve the management of largeamounts of time-dependent information. Temporal database systemsmaintain this information in order to support various sorts of inference(e.g., answering questions involving propositions that are true oversome intervals and false over others). For any given proposition, thereare typically many different occasions on which that proposition becomestrue and persists for some length of time. In this paper, theseoccasions are referred to as time tokens. Many routine databaseoperations must search through the database for time tokenssatisfying certain temporal constraints. To expedite these operations,this paper describes a set of techniques for organizing temporalinformation by exploiting the local and global structure inherent in awide class of temporal reasoning problems. The global structure of timeis exemplified in conventions for partitioning time according to thecalendar and the clock. This global structure is used to partition theset of time tokens to facilitate retrieval. The local structure of timeis exemplified in the causal relationships between events and thedependencies between planned activities. This local structure is used aspart of a strategy for reducing the computation required duringconstraint propagation. The organizational techniques described in thispaper are quite general, and have been used to support a variety ofpowerful inference mechanisms. Integrating these techniques into anexisting temporal database system has increased, by an order ofmagnitude or more in most applications, the number of time tokens thatcan be efficiently handled. —Author's Abstract