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Towards a semantic-driven automatic staging area design for heterogeneous data integration

Published: 03 December 2012 Publication History

Abstract

Nowadays, the volume of information increases exponentially, forcing the corporations to keep their business information distributed under several heterogeneous sources such as relational databases, spread sheets, XML documents and Web pages, and stored under different structures and formats. Integrating heterogeneous sources is recently acknowledged as an important vision on semantic web research. The concept of heterogeneity arises at different levels: from the lexical level to the semantic or structural level. For discovering and consolidating the semantic relationships among the semantically related data present in different types of databases and files, this paper presents the enhancements obtained due to the use of available online large lexical databases, combined with lexical and structural similarity models and the available source metadata. Finally, we reveal the experimental results that demonstrate the applicability and usability of our approach.

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D. Beneventano and S. Bergamaschi, 2004. The MOMIS methodology for integrating heterogeneous data sources, Building the Information Society, vol. 156, 2004.
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P. Zieg, 2007. The SIRUP approach to personal semantic data integration", Doctoral Thesis, University of Zurich, 2007.
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N. Chatterjee and M. Krishna, 2007. Semantic integration of heterogeneous databases on the web, Computing: Theory and Applications, pp. 325--329, 2007.
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F. Hao, 2005. Investigating a heterogeneous data integration approach for data warehousing," PhD Dissertation, University of London, 2005.

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IIWAS '12: Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services
December 2012
432 pages
ISBN:9781450313063
DOI:10.1145/2428736
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • @WAS: International Organization of Information Integration and Web-based Applications and Services

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 December 2012

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Author Tags

  1. heterogeneous data sources
  2. lexical similarity
  3. semantic integration
  4. semantic similarity
  5. similarity function
  6. structural similarity

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IIWAS '12
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  • @WAS

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