Principles of Data Integration

By AnHai Doan, Alon Halevy, and Zachary Ives

Morgan Kaufmann, 1st edition (2012), 520 pages
Available from Amazon in hardcopy or Kindle form, from Google Play store in e-book form, and from Barnes & Noble in hardcopy or Nook form.

This textbook gives a comprehensive academic treatment of the wide range of topics related to research in data integration: mappings and data transformations, query rewriting, schema and data matching, adaptive query processing, XML and streaming data, integration with uncertainty, integration on the Web, keyword search, data provenance, and much more. We also describe research challenges, real systems, and implementation techniques.

The book is ideally suited for graduate courses on data integration, and should also be a great resource for any data integration practitioner in the field.

Contents and Slides

Preface
Chapter 1. Introduction slides

PART I: FOUNDATIONAL DATA INTEGRATION TECHNIQUES

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

PART II: INTEGRATION WITH EXTENDED DATA REPRESENTATIONS

Chapter 11. XML slides
Chapter 12. Ontologies and Knowledge Representation slides
Chapter 13. Incorporating Uncertainty into Data Integration slides
Chapter 14. Data Provenance slides

PART III: NOVEL INTEGRATION ARCHITECTURES

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

Errata