The purpose of this paper is to show that logic provides a convenient formalism for studying classical database problems. There are two main parts to the paper, devoted respectively to conventional databases and deductive databases. In the first part, we focus on query languages, integrity modeling and maintenance, query optimization, and data

A new type of dependency, which includes the well-known functional dependencies as a special case, is defined for relational databases. By using this concept, a new (“fourth”) normal form for relation schemata is defined. This fourth normal form is strictly stronger than Codd’s “im-proved third normal form ” (or “Boyce-Codd normal form”). It is shown that, every relation schema can be decomposed into a family of relation schemata in fourth normal form without loss of information (that is, the original relation can be obtained from the new relations by taking joins). Key words and phrases: database design, multivalued dependency, functional dependency, fourth normal form, 4NF, third normal form, 3NF, Boyce-Codd normal form, normalization, decomposition, relational database

The implication problem is to test whether a given set of independencies logically implies another independency. This problem is crucial in the design of a probabilistic reasoning system. We advocate that Bayesian networks are a generalization of standard relational databases. On the contrary, it has been suggested that Bayesian networks are different from the relational databases because the implication problem of these two systems does not coincide for some classes of probabilistic independencies. This remark, however, does not take into consideration one important issue, namely, the solvability of the implication problem.

Functional dependencies are an integral part of database theory and they form the basis for normalizing relational tables up to BCNF.

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Biologists are increasingly using databases for storing and managing their data. Biological databases typically consist of a mixture of raw data, metadata, sequences, annotations, and related data obtained from various sources. Current database technology lacks several functionalities that are needed by biological databases. In this paper, we introduce bdbms, an extensible prototype database management system for supporting biological data. bdbms extends the functionalities of current DBMSs with: (1) Annotation and provenance management including storage, indexing, manipulation, and querying of annotation and provenance as first class objects in bdbms, (2) Local dependency tracking to track the dependencies and derivations among data items, (3) Update authorization to support data curation via content-based authorization, in contrast to identity-based authorization, and (4) New access methods and their supporting operators that support pattern matching on various types of compressed biological data types. This paper presents the design of bdbms along with the techniques proposed to support these functionalities including an extension to SQL. We also outline some open issues in building bdbms. 1.

This paper addresses the problem of database schema design in the framework of the relational data model and functional dependencies. It suggests that both Third Normal Form (3NF) and BoyceCodd Normal Form (BCNF) supply an inadequate basis for relational schema design. The main problem with 3NF is that it is too forgiving and does not enforce the separation principle as strictly as it should. On the other hand, BCNF is incompatible with the principle of representation and prone to computational complexity. Thus a new normal form, which lies between these two and captures the salient qualities of both is proposed. The new normal form is stricter than 3NF, but it is still compatible with the representation principle. First a simpler definition of 3NF is derived, and the analogy of this new definition to the definition of BCNF is noted. This analogy is used to derive the new normal form. Finally, it is proved that Bernstein's algorithm for schema design synthesizes schemata that are already in the new normal form

In the context of CASE tool development for relational database design, this paper develops a methodology that maps an enhanced EntityRelationship (ER) schema into a relational schema and normalizes the latter into inclusion normal form (IN-NF). Unlike classical normalization that characterizes individual relations only, IN-NF concerns interrelational redundancies. The paper formalizes sources such redundancies in ER schemas. Our methodology enhances several other proposals, in particular [10]. The paper briefly presents our implementation of the methodology using Prolog.

In this paper we address the problem of how to extend the definition of functional dependencies (FDs) in incomplete relations to XML documents. There are two complementary approaches to defining functional dependencies (FDs) in incomplete relational databases. The first approach, called the weak satisfaction approach, defines a FD to be weakly satisfied in an incomplete relation if there is at least one complete relation, obtained by replacing all null values by data values, which satisfies the FD in the ordinary sense. The second approach, called the strong satisfaction approach, defines a FD to be strongly satisfied in an incomplete relation if every complete relation, obtained by replacing all null values by data values, satisfies the FD in the ordinary sense. In this paper we consider the extension of the strong satisfaction approach to defining FDs in XML (referred to as XFDs).

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