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View-based Data Integration

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Encyclopedia of Database Systems

Definition

Data Integration (or Information Integration) is the problem of finding and combining data from different sources. View-based Data Integration is a framework that solves the data integration problem for structured data by integrating sources into a single unified view. This integration is facilitated by a declarative mapping language that allows the specification of how each source relates to the unified view. Depending on the type of view specification language used, view-based data integration systems (VDISs) are said to follow the Global as View (GAV), Local as View (LAV) or Global and Local as View (GLAV) approach.

Historical Background

Data needed by an application are often provided by a multitude of data sources. The sources often employ heterogeneous data formats (e.g., text files, web pages, XML documents, relational databases), structure the data in different ways and can be accessed through different methods (e.g., web forms, database clients). This makes the task...

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Author information

Authors and Affiliations

  1. University of California-San Diego, La Jolla, CA, USA

    Yannis Katsis & Yannis Papakonstantinou

Authors
  1. Yannis Katsis
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  2. Yannis Papakonstantinou
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Corresponding author

Correspondence to Yannis Katsis .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, Georgia, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, Ontario, Canada

    M. Tamer Özsu

Section Editor information

  1. Dept. of Computer Science, Univ. of Illinois at Urbana-Champaign, 201 N. Goodwin Avenue, 61801-2302, Urbana, IL, USA

    Kevin Chang

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Katsis, Y., Papakonstantinou, Y. (2016). View-based Data Integration. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_1072-2

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  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_1072-2

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4899-7993-3

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