Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Information Integration

  • Alon HalevyEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_1069


Data integration; Enterprise information integration


Information integration systems offer uniform access to a set of autonomous and heterogeneous data sources. Sources can range from database systems and legacy systems to forms on the Web, web services and flat files. The data in the sources need not be completely structured as in relational databases. The number of sources in an information integration application can range from a handful to thousands.

Historical Background

Database applications are typically heavily designed and tuned for a specific context. But as data management needs in enterprises change and the information economy evolves, the need to combine information from multiple sources arises frequently. Examples of such scenarios include mergers and acquisitions, internal restructuring, the need to interoperate with third parties and to expose data on the web. Since the early 1980s the need to combine multiple heterogeneous data sources has become a...

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Recommended Reading

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    Deshpande A, Ives Z, Raman V. Adaptive query processing. Foundations and Trends in Databases. Now Publishers. 2007. http://www.nowpublishers.com/dbs.
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    Franklin M, Halevy A, Maier D. Dataspaces: a new abstraction for data management. ACM SIGMOD Rec. 2005;34(4):27–33.CrossRefGoogle Scholar
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    Haas L. Beauty. The beast: the theory and practice of information integration. In: Proceedings of the 11th International Conference on Database Theory; 2007. p. 28–43.Google Scholar
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    Halevy AY. Answering queries using views: a survey. VLDB J. 2001;10(4):270–94.zbMATHCrossRefGoogle Scholar
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    Halevy AY, Ashish N, Bitton D, Carey MJ, Draper D, Pollock J, Rosenthal A, Sikka V. Enterprise information integration: successes, challenges and controversies. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2005. p. 778–87.Google Scholar
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    Lenzerini M. Data integration: a theoretical perspective. In: Proceedings of the 21st ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems; 2002. p. 233–46.Google Scholar
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    Rahm E, Bernstein PA. A survey of approaches to automatic schema matching. VLDB J. 2001;10(4):334–50.zbMATHCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.The Recruit Institute of TechnologyMountain ViewUSA
  2. 2.Google Inc.Mountain ViewUSA

Section editors and affiliations

  • Kevin Chang
    • 1
  1. 1.Dept. of Computer ScienceUniv. of Illinois at Urbana-ChampaignUrbanaUSA