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.
1. 1. Introduction 2. Part I: Foundational Data Integration Techniques 3. 2. Manipulating Query Expressions 4. 3. Describing Data Sources 5. 4. String Matching 6. 5. Schema Matching and Mapping 7. 6. General Schema Manipulation Operators 8. 7. Data Matching 9. 8. Query Processing 10. 9. Wrappers 11. 10. Data Warehousing and Caching 12. Part II: Integration with Extended Data Representations 13. 11. XML 14. 12. Ontologies and Knowledge Representation 15. 13. Incorporating Uncertainty into Data Integration 16. 14. Data Provenance 17. Part III: Novel Integration Architectures 18. 15. Data Integration on the Web 19. 16. Keyword Search 20. 17. Peer-to-Peer Integration 21. 18. Integration in Support of Collaboration 22. 19. The Future of Data Integration 23. Bibliography 24. Index
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.
1. 1. Introduction 2. Part I: Foundational Data Integration Techniques 3. 2. Manipulating Query Expressions 4. 3. Describing Data Sources 5. 4. String Matching 6. 5. Schema Matching and Mapping 7. 6. General Schema Manipulation Operators 8. 7. Data Matching 9. 8. Query Processing 10. 9. Wrappers 11. 10. Data Warehousing and Caching 12. Part II: Integration with Extended Data Representations 13. 11. XML 14. 12. Ontologies and Knowledge Representation 15. 13. Incorporating Uncertainty into Data Integration 16. 14. Data Provenance 17. Part III: Novel Integration Architectures 18. 15. Data Integration on the Web 19. 16. Keyword Search 20. 17. Peer-to-Peer Integration 21. 18. Integration in Support of Collaboration 22. 19. The Future of Data Integration 23. Bibliography 24. Index
