Towards Intelligent Databases

This article is a presentation of the objectives and techniques of deductive databases. The deductive approach to databases aims at extending with intensional definitions other database paradigms that describe applications extensionaUy. We first show how constructive specifications can be expressed with deduction rules, and how normative conditions can be defined using integrity constraints. We outline the principles of bottom-up and top-down query answering procedures and present the techniques used for integrity checking. We then argue that it is often desirable to manage with a database system not only database applications, but also specifications of system components. We present such meta-level specifications and discuss their advantages over conventional approaches

Applying transition rules to bitemporal deductive databases for integrity constraint checking

A bitemporal deductive database is a deductive database that supports valid and transaction time. A set of facts to be inserted and/or deleted in a bitemporal deductive database can be done in a past, present or future valid time. This circumstance causes that the maintenance of database consistency becomes more hard. In this paper, we present a new approach to reduce the difficulty of this problem, based on applying transition and event rules, which explicitly define the insertions and deletions given by a database update. Transition rules range over all the possible cases in which an update could violate some integrity contraint. Although, we have a large amount of transition rules, for each one we argue its utility or we eliminate it. We augment a database with this set of transition and event rules and then standard SLDNF resolution can be used to check satisfaction of integrity constraints.Peer ReviewedPostprint (author's final draft

The Events method for temporal integrity constraint handling in bitemporal deductive databases

A bitemporal deductive database is a deductive database that supports valid and transaction time. A temporal integrity constraint deals with only valid time, only transaction time or both times. A set of facts to be einserted and deleted in a bitemporal deductive database can be done in a past, present or future valid time and at current transaction time. The temporal integrity constraint handling in bitemporal deductive databases causes that the maintenance of consistency becomes more complex than another databases. The $events method$is based on applying transition and event rules, which explicitly define the insertions and deletions given by a database update. In the conceptual model, we augment the database with temporal transition and event rules and then standard SLDNF-resolution can be used to verify that a transaction does not violate any temporal integrity constraint. In the representational data model, we use time point-based intervals to store temporal information. In this paper, we adapt the$$$events method$$$ for handling temporal integrity constraints. Finally, we present the interaction between the above-mentioned conceptual and representational data models.Postprint (published version

Coherent Integration of Databases by Abductive Logic Programming

We introduce an abductive method for a coherent integration of independent data-sources. The idea is to compute a list of data-facts that should be inserted to the amalgamated database or retracted from it in order to restore its consistency. This method is implemented by an abductive solver, called Asystem, that applies SLDNFA-resolution on a meta-theory that relates different, possibly contradicting, input databases. We also give a pure model-theoretic analysis of the possible ways to `recover' consistent data from an inconsistent database in terms of those models of the database that exhibit as minimal inconsistent information as reasonably possible. This allows us to characterize the `recovered databases' in terms of the `preferred' (i.e., most consistent) models of the theory. The outcome is an abductive-based application that is sound and complete with respect to a corresponding model-based, preferential semantics, and -- to the best of our knowledge -- is more expressive (thus more general) than any other implementation of coherent integration of databases