Some problems related to keys and the Boyce-Codd normal form

The aim of this paper is to investigate the connections between minimal keys and antikeys for special Sperner-systems by hypergraphs. The Boyce-Codd normal form and some related problems are also studied in this paper

Justification for inclusion dependency normal form

Functional dependencies (FDs) and inclusion dependencies (INDs) are the most fundamental integrity constraints that arise in practice in relational databases. In this paper, we address the issue of normalization in the presence of FDs and INDs and, in particular, the semantic justification for Inclusion Dependency Normal Form (IDNF), a normal form which combines Boyce-Codd normal form with the restriction on the INDs that they be noncircular and key-based. We motivate and formalize three goals of database design in the presence of FDs and INDs: noninteraction between FDs and INDs, elimination of redundancy and update anomalies, and preservation of entity integrity. We show that, as for FDs, in the presence of INDs being free of redundancy is equivalent to being free of update anomalies. Then, for each of these properties, we derive equivalent syntactic conditions on the database design. Individually, each of these syntactic conditions is weaker than IDNF and the restriction that an FD not be embedded in the righthand side of an IND is common to three of the conditions. However, we also show that, for these three goals of database design to be satisfied simultaneously, IDNF is both a necessary and sufficient condition

Clarifying Normalization

Confusion exists among database textbooks as to the goal of normalization as well as to which normal form a designer should aspire. This article discusses such discrepancies with the intention of simplifying normalization for both teacher and student. This author’s industry and classroom experiences indicate such simplification yields quicker learning and more complete understanding by students

Relational databases: design and use

Relational databases: design and us

Issues and Guidelines in Modeling Decomposition of Minimum Participation in Entity-Relationship Diagrams

The entity-relationship model has long been employed for conceptual modeling of databases. Methodologies and heuristics have been developed, both for effective modeling and for translating entity-relationship models into relational models. One aspect of modeling that is often overlooked in design methodologies is the use of optional versus mandatory participation (i.e., minimum participation) on the development of relational databases. This tutorial complements existing instructional material on database design by analyzing the syntactic implications of minimum participation in binary, unary, and n-ary relationship sets and for the special case where the E-R diagram depicts a database where 3NF is not in BCNF. It then presents design modeling guidelines which demonstrate that (1) for binary 1:1 and 1:M relationship sets, the presence of optional participation sometimes means that the relationship set should be represented in the relational model by a separate relation, (2) unary relationship sets cannot have a (1,1) participation, (3) n-ary relationship sets that have a (1,1) participation can be simplified to be of lower connectivity, and (4) decomposition is not a substitute for normalization. Illustrative examples and modeling guidelines are provided

Master of Science

thesisData quality has become a significant issue in healthcare as large preexisting databases are integrated to provide greater depth for research and process improvement. Large scale data integration exposes and compounds data quality issues latent in source systems. Although the problems related to data quality in transactional databases have been identified and well-addressed, the application of data quality constraints to large scale data repositories has not and requires novel applications of traditional concepts and methodologies. Despite an abundance of data quality theory, tools and software, there is no consensual technique available to guide developers in the identification of data integrity issues and the application of data quality rules in warehouse-type applications. Data quality measures are frequently developed on an ad hoc basis or methods designed to assure data quality in transactional systems are loosely applied to analytic data stores. These measures are inadequate to address the complex data quality issues in large, integrated data repositories particularly in the healthcare domain with its heterogeneous source systems. This study derives a taxonomy of data quality rules from relational database theory. It describes the development and implementation of data quality rules in the Analytic Health Repository at Intermountain Healthcare and situates the data quality rules in the taxonomy. Further, it identifies areas in which more rigorous data quality iv should be explored. This comparison demonstrates the superiority of a structured approach to data quality rule identification

On redundancy, anomalies and on the question "what do normal forms really do"

In this paper we first survey various examples for anomalies given in the literature [1,3,8]. We discuss the formalizations and relate them to each other and the examples. We give arguments that show that decomposition of a relation scheme can help in getting rid of deletion/insertion anomalies and can fail in getting rid of update anomalies in the decomposed case