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Computer Science - Database Management & Information Retrieval | Introduction to Databases - From Biological to Spatio-Temporal

Introduction to Databases

From Biological to Spatio-Temporal

Revesz, Peter

2010, XVIII, 744 p. 173 illus.

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  • Provides a comprehensive coverage of the field of databases

Developments in modern computers and applications have resulted in a shift away from relational databases into a chaotic proliferation of specialized database systems. As many of these advanced databases are unable to communicate with each other, database interoperability and data integration have become important challenges. The search for a suitable common standard for the numerous varieties of current databases has generated renewed interest in extensions of relational databases, such as constraint databases.

This unique, reader-friendly textbook/reference provides a comprehensive coverage of the field of databases. Introduction to Databases reveals a deep insight into the workings of numerous database systems, enabling readers to develop complex and rewarding database applications. Students will gain hands-on experience by following the suggested exercises, and are offered the support to begin their own research projects in database systems. The theory covered is complemented by a detailed examination of specific applications from a broad range of diverse areas. The text assumes as prerequisite only basic discrete mathematics, linear algebra, and programming knowledge.

Topics and features:

• Provides chapter-by-chapter descriptions of eleven different types of databases, and presents the MLPQ and the DISCO database systems that implement several different types of databases

• Concludes each chapter with bibliographic notes and an extensive set of exercises

• Examines database design, including advanced database application issues of database interoperability, data integration, interpolation and approximation, and prediction and data mining

• Presents the MLPQ system, together with slides, solutions (for instructors), and other course aids at the supporting website: http://cse.unl.edu/~revesz

• Covers topics on indexing methods, data visualization, the safety of queries, general evaluation algorithms, the efficient implementation of evaluation algorithms, and the complexity of the evaluation of different types of queries

• Structured to allow for flexible course design, with courses suggested in the Preface

An essential resource for advanced undergraduate students, even non-computer science students with little prior exposure to databases will find this a clear introduction to the theory, the various types of databases and their applications. Professional database experts will also find this a valuable reference.

Dr. Peter Revesz is a professor in the Department of Computer Science and Engineering at the University of Nebraska-Lincoln and has held visiting appointments at, among other places, the IBM T.J. Watson Research Center, INRIA, and the Max Planck Institute for Computer Science. Other titles by this author include the successful Springer textbook Introduction to Constraint Databases.

Content Level » Professional/practitioner

Keywords » algorithm - algorithms - complexity - computational complexity - data mining - data model - database - database systems - deductive database - genome - knowledge - mathematics - programming - relational database - verification

Related subjects » Artificial Intelligence - Database Management & Information Retrieval - Software Engineering

Table of contents 

Data Models, Queries, Evaluation

Propositional Databases

Relational Databases

Constraint Databases

Temporal Databases

Geographic Databases

Moving Objects Databases

Image Databases

Constraint Objects Databases

Genome Databases

Set Databases

Constraint Deductive Databases

The MLPQ System

The DISCO System

Database Design

Interoperability

Data Integration

Interpolation and Approximation

Prediction and Data Mining

Indexing

Data Visualization

Safe Query Languages

Evaluation of Queries

Implementation Methods

Computational Complexity

Software Verification

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