Principles of Data Integration

How do you approach answering queries when your data is stored in multiple databases that were designed independently by different people? This is first comprehensive book on data integration and is written by three of the most respected experts in the field.

This book provides an extensive introduction to the theory and concepts underlying today’s data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts. Data integration is the problem of answering queries that span multiple data sources (e.g., databases, web pages). Data integration problems surface in multiple contexts, including enterprise information integration, query processing on the Web, coordination between government agencies and collaboration between scientists. In some cases, data integration is the key bottleneck to making progress in a field.

The authors provide a working knowledge of data integration concepts and techniques, giving you the tools you need to develop a complete and concise package of algorithms and applications.

*Offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand.

*Enables you to build your own algorithms and implement your own data integration applications

*Companion website with numerous project-based exercises and solutions and slides. Links to commercially available software allowing readers to build their own algorithms and implement their own data integration applications. Facebook page for reader input during and after publication.

Table of Contents

Chapter 1. Introduction

Part I: Foundational Data Integration Techniques
Chapter 2. Manipulating Query Expressions
Chapter 3. Describing Data Sources
Chapter 4. String Matching
Chapter 5. Schema Matching and Mapping
Chapter 6. General Schema Manipulation Operators
Chapter 7. Data Matching
Chapter 8. Query Processing
Chapter 9. Wrappers
Chapter 10. Data Warehousing and Caching

Part II: Integration with Extended Data Representations
Chapter 11. XML
Chapter 12. Ontologies and Knowledge Representation
Chapter 13. Incorporating Uncertainty into Data Integration
Chapter 14. Data Provenance

Part III: Novel Integration Architectures
Chapter 15. Data Integration on the Web
Chapter 16. Keyword Search: Integration on Demand
Chapter 17. Peer-to-Peer Integration
Chapter 18. Integration in Support of Collaboration
Chapter 19. The Future of Data Integration