The area of deductive databases has matured in recent years, and it now seems appropriate to re ect upon what has been achieved and what the future holds. In this paper, we provide an overview of the area and briefly describe a number of projects that have led to implemented systems.

The problem of allowing non-monotonic constructs, such as negation and aggregates, in recursive programs represents a difficult challenge faced by current research in deductive databases. In this paper, we present a solution that combines generality with efficiency, as demonstrated by its implementation in the new LDL++ system. A novel and general treatment of set aggregates, allowing for user-defined aggregates, is also presented. 1 Introduction The area of non-monotonic reasoning has benefited significantly from research in deductive databases, as demonstrated by the introduction of the concept of stratified negation and stratified set aggregates [16]. This concept is significant since it removes several of the limitations and problems of Prolog's negationby -failure, and it is conducive to efficient implementation, as demonstrated by systems such as Glue-Nail, LDL and CORAL [15, 22, 3]. However, as experience was gained with real-life applications [23], it became clear that stratif...

The author will not pretend to be unbiased in the matter of comparing the deductive and object-oriented approaches to new database systems; he believes that despite some important concepts originating with the object-oriented approach, the deductive family of systems will ultimately dominate. We shall explore some of the reasons why the two approaches do not mix well. Fortunately, most of the features of object-oriented database systems can be incorporated in deductive systems (but not vice-versa). Then we argue that declarativeness is important for at least some of the new applications, and that declarative languages cannot be object-oriented in a nontrivial way. We next contrast the approaches with regard to the way they classify data elements. We close with an examination of the prospects for "classless" data, which is motivated by the prospect of databases where the number of distinct classes would be too large to name systematically. There are a number of challenges to implementin...

The focus of this paper is semantic query optimization in the presence of integrity constraints (ICs) such as inclusion dependencies (INDs) and context dependencies (CDs). INDs are well known to arise naturally in many applications. CDs, introduced earlier in a different context, can capture natural semantic constraints that cannot be expressed using INDs. Besides, some CDs can also be inferred from given INDs, and further have the advantage of being more directly geared toward semantic query optimization than INDs. We provide an inference mechanism for reasoning with CDs and develop efficient algorithms for semantic query optimization using them. The contributions of this paper are sufficient conditions and algorithms for the detection of redundant atoms and rules in a class of linear recursive programs, arising in deductive databases. We take a program transformation approach to semantic query optimization. As a consequence, our approach has the following advantages: (i) our techniqu...

Currently database researchers are investigating new data models in order to remedy the deficiences of the flat relational model when applied to non-business applications. Herein we concentrate on a recent graph-based data model called the hypernode model. The single underlying data structure of this model is the hypernode which is a digraph with a unique defining label. We present in detail the three components of the model, namely its data structure, the hypernode, its query and update language, called HNQL, and its provision for enforcing integrity constraints. We first demonstrate that the said data model is a natural candidate for formalising hypertext. We then compare it with other graph-based data models and with set-based data models. We also investigate the expressive power of HNQL. Finally, using the hypernode model as a paradigm for graph-based data modelling, we show how to bridge the gap between graph-based and set-based data models, and at what computational cost this can...

The evolution of existing information systems and a new wave of data-intensive applications are creating a strong demand for database-centered programming environments much more sophisticated and intelligent than those supported by current database systems. In this paper, we describe the contributions that deductive databases offer to the evolution of databases and information systems to statisfy said demands. In addition to all database essentials, deductive databases support rule-based logic-oriented languages that allow terse formulations of complete applications, along with reasoning and queries. Thus, they support a rule-based interface that eliminates the impedance mismatch problem (between programming language and query sublanguage) and elevates the design and development of database applications to the level of declarative, knowledge-based specifications. In this paper, we review the evolution of the enabling technology and architectures of deductive database prototypes; then w...

These two rule-oriented paradigms of databases have been the focus of extensive research and are now coming of age in the commercial DBMS world.

Deductive database systems have made major advances on efficient support for nonmonotonic reasoning. A first generation of deductive database systems supported the notion of stratification for programs with negation and set aggregates. Stratification is simple to understand and efficient to implement but it is too restrictive; therefore, a second generation of systems seeks efficient support for more powerful semantics based on notions such as well-founded models and stable models. In this respect, a particularly powerful set of constructs is provided by the recently enhanced LDL++ system that supports (i) monotonic user-defined aggregates, (ii) XY-stratified programs, and (iii) the nondeterministic choice constructs under stable model semantics. This integrated set of primitives supports a terse formulation and efficient implementation for complex computations, such as greedy algorithms and data mining functions, yielding levels of expressive power unmatched by other deductive...

Recent work on load balancing has confirmed its importance when one wants to achieve good performances during the actual evaluation of parallel database queries. Existing work mostly focuses on the join processing for parallel relational databases. We are interested here in more complex queries, such as recursive ones. The main difference is that, in the latter case, the work due to a task cannot be previously determined and, consequently, no method can define at the outset the tasks to be executed in parallel in order to balance the workload at each processor. We propose a dose-driven dynamic strategy that aims at obtaining an improved workload balance and better use of the available resources. We examine the applicability of our strategy with its specialization to the case of the transitive closure query. Preliminary computational results on randomly generated test problems illustrate the efficiency of the proposed method. Keywords: Load Balancing, Dynamic Assignment, Recursive Quer...

This paper describes the system and the research advances that have enabled its design and development. We begin by discussing the new nonmonotonic and nondeterministic constructs that extend the functionality of the language, while preserving its model-theoretic and fixpoint semantics. Then, we describe the execution model and the open architecture designed to support these new constructs and to facilitate the integration with existing DBMSs and applications. Finally, we describe the lessons learned by using on various tested applications, such as middleware and datamining.