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. For example, when two companies merge, the number of different databases scattered across a company could easily reach 100. Obtaining a complete and organized view of data requires the application of data integration technology (i.e., semantic integration involves resolving the inevitable differences in certain concepts and definitions in their respective schemas, like "earnings," "compliant," etc. This book presents a comprehensive treatment of the issues faced in integrating data from multiple sources, from the theoretical principles to system issues and current challenges raised by the World Wide Web and cloud computing. It allows readers to answer the constantly recurring question: How do I approach answering queries when my data is stored in multiple databases that were designed independently by different people?
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. For example, when two companies merge, the number of different databases scattered across a company could easily reach 100. Obtaining a complete and organized view of data requires the application of data integration technology (i.e., semantic integration involves resolving the inevitable differences in certain concepts and definitions in their respective schemas, like "earnings," "compliant," etc. This book presents a comprehensive treatment of the issues faced in integrating data from multiple sources, from the theoretical principles to system issues and current challenges raised by the World Wide Web and cloud computing. It allows readers to answer the constantly recurring question: How do I approach answering queries when my data is stored in multiple databases that were designed independently by different people?
The first comprehensive textbook of data integration from theoretical principles to implementation issues and current challenges raised by the semantic web and cloud computing
CH 1: Introduction
Part I: Foundational Data Integration Techniques
CH 2: Manipulating Query Expressions
CH 3: Describing Data Sources
CH 4: String MatchingCH 5: Schema Matching and Mapping
CH 6: General Schema Manipulation Operators
CH 7: Data Matching
CH 8: Query Processing
CH 9: Wrappers
CH 10: Data Warehousing and Caching
Part II: Integration with Extended Data Representations
CH 11: XML
CH 12: Ontologies and Knowledge Representation
CH 13: Incorporating Uncertainty into Data Integration
CH 14: Data Provenance
Part III: Novel Integration Architectures
CH 15: Data Integration on the Web
CH 16: Keyword Search: Integration on Demand
CH 17: Peer-to-Peer Integration
CH 18: Integration in Support of Collaboration
CH 19: The Future of Data Integration
AnHai Doan, Associate Professor in Computer Science at the University of Wisconsin-Madison. Consulting work with Microsoft AdCenter Lab and Yahoo Research Lab. Head of the Structured Data Group, Google Research, Mountain View, California. He joined Google in 2005 with the acquisition of his company, Transformic. Associate Professor at the University of Pennsylvania and a Faculty Member of the Penn Center for Bioinformatics. He received his PhD from the University of Washington. His research interests include data integration, data sharing among autonomous and heterogeneous systems, heterogeneous sensor networks, and information provenance and authoritativeness.
"Researchers looking for concise and clear descriptions of the state of the art in data integration will benefit from this noteworthy effort. Graduate students in particular will acquire an excellent blueprint of the field, supplemented by almost 600 up-to-date bibliographic references they can use to further their work."--ComputingReviews.com, October 4, 2013 "Written by three of the field's leading experts, this book manages to address a broad range of topics in its subject domain in a reasonably compact package.The intended audience is primarily academic, specifically graduate and advanced undergraduate students in a university setting. Researchers new to the field will find it to be a helpful introduction."--ComputingReviews.com, August 12, 2013 ".a well-organized and thorough treatment of data integration topics is a welcome addition to the practicing software professional's bookshelf. If that treatment is both academically rigorous and still readable, as is the case with this book, it becomes a valuable resource for researchers and, in particular, for doctoral students."--ComputingReviews.com, July 3, 2013 "This is the definitive book on data integration technology, written by experts who invented much of the technology they write about. It's comprehensive, with lots of technical detail very clearly explained. It's a must-read for anyone involved in the development of data integration solutions."--Philip A. Bernstein, Distinguished Scientist, Microsoft Corporation "Despite having been with us for decades, data integration remains a challenging, multi-faceted problem. This book does an excellent job of bringing together and explaining its many facets along with the technical solutions that have been developed to date. The authors are three of the field's leading contributors, with a mix of both academic and industrial experience, and their presentation includes examples and manages to make even the more theoretical material accessible to readers. All aspects of modern data integration are covered, including different styles of integration, data and schema matching, query processing and wrappers, as well as challenges posed by the Web and the wide variety of data types and formats that must be integrated today. This book should be a great resource for graduate courses on data integration."--Michael Carey, Bren Professor of Information and Computer Sciences, UC Irvine "The days of enterprises/organizations depending on a single, closed database have given way to a Web-dominated world in which multiple databases must interoperate and integrate. Doan (computer science, U. of Wisconsin, Madison) and colleagues at Google and the University of Pennsylvania address how database ideas have broadened to accommodate external sources of structured information, distributed aspects of the Web, and issues of data-sharing. Part I treats topics and techniques for data queries, integration, and warehousing covered in a database course. Part II discusses extended data representations that capture properties not present in the standard relational data model. Then they present novel architectures for, and trends in, addressing specific integration problems, e.g., of Web sources. Includes an extensive bibliography."--Reference and Research Book News, October 2012
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