Expressiveness of Temporal Query Languages: On the Modelling of Intervals, Interval Relationships and States

Storing and retrieving time-related information are important, or even critical, tasks on many areas of Computer Science (CS) and in particular for Artificial Intelligence (AI). The expressive power of temporal databases/query languages has been studied from different perspectives, but the kind of temporal information they are able to store and retrieve is not always conveniently addressed. Here we assess a number of temporal query languages with respect to the modelling of time intervals, interval relationships and states, which can be thought of as the building blocks to represent and reason about a large and important class of historic information. To survey the facilities and issues which are particular to certain temporal query languages not only gives an idea about how useful they can be in particular contexts, but also gives an interesting insight in how these issues are, in many cases, ultimately inherent to the database paradigm. While in the area of AI declarative languages are usually the preferred choice, other areas of CS heavily rely on the extended relational paradigm. This paper, then, will be concerned with the representation of historic information in two well known temporal query languages: it Templog in the context of temporal deductive databases, and it TSQL2 in the context of temporal relational databases. We hope the results highlighted here will increase cross-fertilisation between different communities. This article can be related to recent publications drawing the attention towards the different approaches followed by the Databases and AI communities when using time-related concepts

ON THE EXPRESSIVE POWER OF INFINITE TEMPORAL DATABASES

We discuss different techniques for representing infinite temporal data. There are two basic approaches: A procedural description, as used in production systems, and represented, in this paper, by a version of Datalog. The second approach is a more declarative method, using some form of temporal logic programming. We examine several versions of each approach, and compare their expressive power, i.e., what temporal data each formalism can capture.Information Systems Working Papers Serie

On the Representation of Infinite Temporal Data and Queries

Time is unbounded by nature. A temporal predicate (one that varies with time) will thus often have an infinite extension. To store such a predicate in a database, one can either artificially restrict its extension to a finite set or, more desirably, use a formalism that allows the finite representation of at least some infinite temporal extensions. Several such formalisms have been proposed in the past few years. The formalism that extends traditional relational databases most directly is the generalized databases described in [KSW90]. There, database tuples are extended with an arbitrary number of additional columns carrying linear repeating points. These represent periodic sets of time points possibly constrained by linear inequalities. The query language proposed in [KSW90] is a multi-sorted first-order logic in which predicates have..