Skip to main content
SpringerLink
Log in

View-based Data Integration

  • Reference work entry
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...

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 2,500.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Recommended Reading

  1. Abiteboul S. and Duschka O.M. Complexity of answering queries using materialized views. In Proc. 17th ACM SIGACT-SIGMOD-SIGART Symp. on Principles of Database Systems, 1998, pp. 254–263.

    Google Scholar 

  2. Carey M.J., Haas L.M., Schwarz P.M., Arya M., Cody W.F., Fagin R., Flickner M., Luniewski A., Niblack W., Petkovic D., Thomas II J., Williams J.H., and Wimmers E.L. Towards heterogeneous multimedia information systems: The Garlic approach. In Proc. 5th Int. Workshop on Research Issues on Data Eng., 1995, pp. 124–131.

    Google Scholar 

  3. Fagin R., Kolaitis P.G., Miller R.J., and Popa L. Data exchange: Semantics and query answering. In Proc. Int. Conf. on Database Theory, 2002. pp. 207–224.

    Google Scholar 

  4. Friedman M., Levy A., and Millstein T. Navigational plans for data integration. In Proc. 16th National Conf. on AI and 11th Innovative Applications of AI Conf., 1999.

    Google Scholar 

  5. Garcia-Molina H.K., Papakonstantinou Y.K., Quass D.K., Rajaraman A.K., Sagiv Y.K., Ullman J.K., Vassalos V.K., and Widom J.K. The TSIMMIS approach to mediation: data models and languages. J. Intell. Inf. Syst., 8(2):117–132, 1997.

    Article  Google Scholar 

  6. Genesereth M.R., Keller A.M., and Duschka O.M. Infomaster: An information integration system. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1997.

    Google Scholar 

  7. Halevy A. Logic-based techniques in data integration. In Logic Based Artif. Intell., 2000.

    Google Scholar 

  8. Halevy A.Y. Answering queries using views: A survey. VLDB J., 10(4):270–294, 2001.

    Article  MATH  Google Scholar 

  9. Katsis Y., Deutsch A., and Papakonstantinou Y. interactive source registration in community-oriented information integration. In Proc. 34th Int. Conf. on Very Large Data Bases, 2008.

    Google Scholar 

  10. Kirk T., Levy A.Y., Sagiv Y., and Srivastava D. The information manifold. In Information Gathering from Heterogeneous, Distributed Environments, 1995.

    Google Scholar 

  11. Landers T. and Rosenberg R.L. An overview of MULTIBASE. Distributed systems, Vol. II: distributed data base systems table of contents, 1986, pp. 391–421.

    Google Scholar 

  12. Lenzerini M. Data integration: A theoretical perspective. In Proc. 21st ACM SIGACT-SIGMOD-SIGART Symp. on Principles of Database Systems, 2002.

    Google Scholar 

  13. Manolescu I., Florescu D., and Kossmann D. Answering XML queries over heterogeneous data sources. In Proc. 27th Int. Conf. on Very Large Data Bases, 2001.

    Google Scholar 

  14. Widom J. Research problems in data warehousing. In Proc. 27th Int. Conf. on Very Large Data Bases, 1995.

    Google Scholar 

  15. Yu C. and Popa L. Constraint-based XML query rewriting for data integration. In Proc. 27th Int. Conf. on Very Large Data Bases, 2004.

    Google Scholar 

Download references

Author information

Authors and Affiliations

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

    Yannis Katsis & Yannis Papakonstantinou

Authors
  1. Yannis Katsis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yannis Papakonstantinou
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. College of Computing, Georgia Institute of Technology, 266 Ferst Drive, 30332-0765, Atlanta, GA, USA

    LING LIU (Professor) (Professor)

  2. Database Research Group David R. Cheriton School of Computer Science, University of Waterloo, 200 University Avenue West, N2L 3G1, Waterloo, ON, Canada

    M. TAMER ÖZSU (Professor and Director, University Research Chair) (Professor and Director, University Research Chair)

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer Science+Business Media, LLC

About this entry

Cite this entry

Katsis, Y., Papakonstantinou, Y. (2009). View-based Data Integration. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_1072

Download citation

Publish with us

Policies and ethics

Search

Navigation