This paper presents a novel deductive object-oriented database language, called ROL (Rule-based Object Language), which is being developed at the University of Regina. ROL effectively integrates important features of object-oriented databases and deductive databases into a uniform framework. It supports object identity, complex objects, classes, class hierarchy, multiple inheritance with overriding, and schema. It also supports structured values such as functor objects and sets, treats them as first class citizens, and provides powerful mechanisms for representing both partial and complete information on sets. It is an extension of pure valued-oriented deductive languages such as Datalog and LDL (without grouping) and subsumes them as special cases. Another novelty is the introduction of a new ordering which can capture the intended semantics of nested sets. The ROL language is given a logical semantics based on this new ordering that accounts in a clean and declarative fashi...

. We present declarative and procedural semantics for a deductive object-oriented language, Gulog. The declarative semantics is based on preferred minimal models. We describe both bottom-up and top-down query evaluation procedures and show that they are sound with respect to the declarative semantics. The results contribute to our understanding of the interaction of inheritance, overriding and deduction in the presence of both functional and set-valued methods, and multiple inheritance. Keywords: complex objects, deductive databases, fixpoint semantics, procedural semantics, knowledge bases, object-oriented databases, rule based 1. Introduction The aim of this paper is to propose a simple mathematical foundation for objectoriented systems with deduction. In particular, we present a declarative and procedural semantics for a simple language that includes classes, objects, functional and set-valued methods, (multiple) inheritance, overriding, and derived methods and predicates with the...

Abstract | This paper tells the story of OQL, the standard query language of the Object Database Management Group (ODMG) [30]. The story starts in 1988, at INRIA in the Alta r Group y. The objective of that group was to develop an object-oriented database system [41]. This objective was reached: in September 1991 the O2 database system started its commercial career as the main product of a company called O2Technology [6]. As opposed to its competitors, O2 featured a full- edged query language named O2SQL [22]. The story goes on with the creation of the ODMG in 1991 and the adoption of O2SQL as the standard object query language under its new and nal name: OQL. During the following years, OQL went through some modi cations, the most important ofwhich resulted in OQL 1.2 that o ers some level of compliance with SQL92. On top of providing the expressive power of the SQL92 query language [54], OQL allows objects to be queried. This is a claim also supported by the upcoming SQL3. However, due to its adequacy to the object oriented type system and its functional nature, OQL is much simpler to learn, use and implement. A goal of this paper is to demonstrate this. This paper tells about the mistakes and pertinent choices we made while designing and implementing OQL. I hope it also conveys the great pleasure I had to be part of this adventure. Key words: Object-oriented database, query language 1.

this paper, by developing a simple logic called

Order-sorted equational logic is extended with dynamic logic to a specification language for dynamic objects. Special attention is paid to different concepts of encapsulation that play a role in object-orientation. It is argued that the resulting language, CMSL, meets those requirements of the object-oriented database system manifesto [6] that are applicable to object-oriented conceptual models (as opposed to OO databases).

This paper presents an approach to the development of a deductive object-oriented database system, describing the key design decisions and their consequences for implementation. The approach is novel, in that it integrates an object-oriented database system manipulated using an imperative programming language (ROCK) with a logic language for expressing queries and methods (ROLL). The integration is made seamless by deriving both the imperative and logic languages from a single formally defined data model, thereby avoiding impedance mismatches when they are integrated. Key words: Deductive Object-Oriented Databases, Deductive Databases, Object-Oriented Databases, Database Programming, Logic Programming. 1. INTRODUCTION The two most prominent of the emerging approaches to database programming build upon the deductive and the object-oriented paradigms. Both of these approaches have significant strengths. Deductive databases (DDBs) have a formal basis in first order logic, support expressi...

A deductive object-oriented database (DOOD) language, QUIXOT E, has been designed and developed for knowledge information processing applications such as natural language processing, legal reasoning, and genetic information processing in the Japanese Fifth Generation Computer System (FGCS) project and the FollowOn project. As knowledge information is different from conventional information, a new framework for database and knowledge-base management systems was required under such an environment. As a result, QUIXOT E has many unique features as a DOOD language and system. Focusing on such aspects in this paper, we describe specific features of QUIXOT E and discuss this approach. Further, we observe very briefly how such features are effective for knowledge information processing by showing some examples of our applications. 1 Introduction The Japanese Fifth Generation Computer System (FGCS) project developed various hardware and software for knowledge information processing systems u...

Deductive databases result from the integration of relational database and logic programming techniques. However, significant problems remain inherent in this simple synthesis from the language point of view. In this paper, we discuss these problems from four different aspects: complex values, object orientation, higherorderness, and updates. In each case, we examine four typical languages that address the corresponding issues.

In this article, we develop a relational algebra for metadata integration, Federated Interoperable Relational Algebra (FIRA). FIRA has many desirable properties such as compositionality, closure, a deterministic semantics, a modest complexity, support for nested queries, a subalgebra equivalent to canonical Relational Algebra (RA), and robustness under certain classes of schema evolution. Beyond this, FIRA queries are capable of producing fully dynamic output schemas, where the number of relations and/or the number of columns in relations of the output varies dynamically with the input instance. Among existing query languages for relational metadata integration, only FIRA provides generalized dynamic output schemas, where the values in any (fixed) number of input columns can determine output schemas. Further contributions of this article include development of an extended relational model for metadata integration, the Federated Relational Data Model, which is strictly downward compatible with the relational model. Additionally, we define the notion of Transformational Completeness for relational query languages and postulate FIRA as a canonical transformationally complete language. We also give a declarative, SQL-like query language that is equivalent to FIRA, called Federated Interoperable Structured Query Language (FISQL). While our main contributions are conceptual, the federated model, FISQL/FIRA, and the notion of transformational completeness nevertheless have important applications to data integration and OLAP. In addition to summarizing these applications, we illustrate the use of FIRA to optimize FISQL queries using rule-based transformations that directly parallel their canonical relational counterparts. We conclude the article with an extended discussion of related work as well as an indication of current and future work on FISQL/FIRA.

Semantic Query Optimization optimize query processing by transforming a query into a semantically equivalent one, i.e. a query whose result is the same for every instance of the database. Semantic query optimization can be obtained by a query rewriting that takes into account the integrity constraints the database must satisfy. In this paper we analyze the possibility of implementing semantic optimization in OODBMs by means of the subsumption relation computation over a database schema. Subsumption relations over a schema includes all the specialization relations between classes (types) both explicitly declared in the schema and entailed by the schema. Subsumption computation has been previously used in the database area to perform schemata acquisition and checking for coherence and query processing optimization. In this paper we extend complex object data models with integrity constraints expressed as rules and propose to apply subsumption computation to perform semantic query optimiz...