We define formal notions of temporal domain and temporal database, and use them to survey a wide spectrum of temporal query languages. We distinguish between an abstract temporal database and its concrete representations, and accordingly between abstract and concrete temporal query languages. We also address the issue of incomplete temporal information. 1 Introduction A temporal database is a repository of temporal information. A temporal query language is any query language for temporal databases. In this paper we propose a formal notion of temporal database and use this notion in surveying a wide spectrum of temporal query languages. The need to store temporal information arises in many computer applications. Consider, for example, records of various kinds: financial [37], personnel, medical [98], or judicial. Also, monitoring data, e.g., in telecommunications network management [4] or process control, has often a temporal dimension. There has been a lot of research in temporal dat...

: We present an efficient implementation method for temporal integrity constraints formulated in Past Temporal Logic. Although the constraints can refer to past states of the database, their checking does not require that the entire database history be stored. Instead, every database state is extended with auxiliary relations that contain the historical information necessary for checking constraints. Auxiliary relations can be implemented as materialized relational views. 1 Introduction Integrity constraints form an essential part of every database application. It is customary to distinguish between two kinds of constraints: static and temporal (or dynamic). Static constraints refer to the current state of the database, e.g.,"every manager is also an employee ", while temporal constraints may refer to past and future states in addition to the current state, e.g., "salaries of employees should never decrease" or "once a student drops out of the Ph.D. program, she should not be readmit...

. This paper presents an overview of the development of the field of temporal and modal logic programming. We review temporal and modal logic programming languages under three headings: (1) languages based on interval logic, (2) languages based on temporal logic, and (3) languages based on (multi)modal logics. The overview includes most of the major results developed, and points out some of the similarities, and the differences, between languages and systems based on diverse temporal and modal logics. The paper concludes with a brief summary and discussion. Categories: Temporal and Modal Logic Programming. 1 Introduction In logic programming, a program is a set of Horn clauses representing our knowledge and assumptions about some problem. The semantics of logic programs as developed by van Emden and Kowalski [96] is based on the notion of the least (minimum) Herbrand model and its fixed-point characterization. As logic programming has been applied to a growing number of problem domai...

Temporal logic is obtained by adding temporal connectives to a logic language. Explicit references to time are hidden inside the temporal connectives. Different variants of temporal logic use different sets of such connectives. In this chapter, we survey the fundamental varieties of temporal logic and describe their applications in information systems. Several features of temporal logic make it especially attractive as a query and integrity constraint language for temporal databases. First, because the references to time are hidden, queries and integrity constraints are formulated in an abstract, representationindependent way. Second, temporal logic is amenable to efficient implementation. Temporal logic queries can be translated to an algebraic language. Temporal logic constraints can be efficiently enforced using auxiliary stored information. More general languages, with explicit references to time, do not share these properties. Recent research has proposed various implementation t...

We propose constraint databases as an intermediate level facilitating the interoperability of spatiotemporal data models. Constraint query languages are used to express translations between different data models. We illustrate our approach in the context of a number of temporal, spatial, and spatiotemporal data models. 1 Introduction Very large temporal and spatial databases are a common occurrence nowadays. Although they are usually created with a specific application in mind, they often contain data of potentially broader interest, e.g., historical records or geographical data. By database interoperability we mean the problem of making the data from one database usable to the users of another. Data sharing between different applications and different sites is often An early version of some of the results in this paper appeared in [CR97]. The work of the first author was supported by NSF grant IRI-9632870. The work of the second author was supported by NSF grants IRI-9632871 and ...

Traditionally, dependency theory has been developed for uninterpreted data. Specifically, the only assumption that is made about the data domains is that data values can be compared for equality. However, data is often interpreted and there can be advantages in considering it as such, for instance obtaining more compact representations as done in constraint databases. This paper considers dependency theory in the context of interpreted data. Specifically, it studies constraint-generating dependencies. These are a generalization of equality-generating dependencies where equality requirements are replaced by constraints on an interpreted domain. The main technical results in the paper are a general decision procedure for the implication and consistency problems for constraint-generating dependencies, and complexity results for specific classes of such dependencies over given domains. The decision procedure proceeds by reducing the dependency problem to a decision problem for the constraint theory of interest, and is applicable as soon as the underlying constraint theory is decidable. The complexity results are, in some cases, directly lifted from the constraint theory; in other cases, optimal complexity bounds are obtained by taking into account the specific form of the constraint decision problem obtained by reducing the dependency implication problem.

An important feature of many advanced active database prototypes is support for rules triggered by complex patterns of events. Their composite event languages provide powerful primitives for event-based temporal reasoning. In fact, with one important exception, their expressive power matches and surpasses that of sophisticated languages offered by Time Series Management Systems (TSMS), which have been extensively used for temporal data analysis and knowledge discovery. This exception pertains to temporal aggregation, for which, current active database systems offer only minimal support, if any. In this paper, we introduce the language TREPL, which addresses this problem. The TREPL prototype, under development at UCLA, offers primitives for temporal aggregation that exceed the capabilities of state-of-the-art composite event languages, and are comparable to those of TSMS languages. TREPL also demonstrates a rigorous and general approach to the definition of composite event language sema...

This paper introduces a generalization of Datalog based on the notion of integer periodicity constraints. A closed form evaluation procedure running in PTIME for this class of constraints is developed. The periodicity constraints are then combined with integer (gap-)order constraints and an evaluation procedure for the combination is developed. A general method for combining different classes of constraints in the framework of Datalog is also discussed. 1 Introduction Generalized databases [1, 10, 12] are infinite databases that can be represented using finite sets of generalized (or constraint) tuples. A number of query languages over such databases have been studied. The proposed query languages differ with respect to: ffl the underlying inference mechanism (first order vs. deductive) ffl the constraint language used. In this paper we study generalized Datalog programs (function-free logic programs) that operate on constraint tuples in the place of ground atoms. This idea comes fr...

The work of Mannila et al. [4] of finding frequent episodes in sequences is extended to finding temporal logic patterns in temporal databases. It is argued that temporal logic provides an appropriate formalism for expressing temporal patterns defined over categorical data. It is also proposed to use Temporal Logic Programming as a mechanism for the discovery of frequent patterns expressible in temporal logic. It is explained in the paper how frequent temporal patterns can be discovered by constructing temporal logic programs. To test these methods , temporal logic programs were constructed for certain classes of patterns and were implemented in OPS5. Introduction In this paper, we address the problem of finding interesting patterns in temporal databases [1,2] defined over categorical (symbolic) data. This is an important problem that frequently occurs in various applications such as molecular biology (finding patterns in genetic sequences), telecommunications (finding pat...

Representation and querying of temporal information can benefit from the integration of techniques from constraint databases, database models for indefinite information and reasoning about temporal constraints. With this perspective in mind, we present a hierarchy of temporal data models: temporal relations, generalized temporal relations and temporal tables. We study the semantics of these models and develop algebraic and calculus query languages for them. The proposed models can be useful to several novel applications include planning, scheduling, project management, medical information systems, geographical information systems and natural language processing systems. 1 Introduction Research in temporal databases has mostly concentrated on temporal models with definite temporal information (e.g., "the salary of Jones was $20,000 from January 1989 to April 1989") [62, 58]. There are few exceptions to this general rule. [11] was the first paper to investigate infinite periodic data (e...