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An integration of data sources with UML class models based on ontological analysis

Published: 04 November 2005 Publication History

Abstract

Data integration is an effective method to interoperate data that reside in different sources for the purpose of providing users with a single point of access to those data. Due to data heterogeneity, data correctness and consistency are significant for integration. Richer semantics of data is a major factor in resolving conflicts among heterogeneous data sources. As UML class model represents only schema-based semantics of data (e.g. classes, attributes, and class structures), alternative methods such as ontology is useful for representing additional semantics (e.g. data values, data units, and synonym and hypernym lists). This paper proposes a method for integrating two data sources with UML class models by using an analysis of their ontologies. In our framework, ontology will be applied to describe semantics of data in each source. Then the ontologies are analysed and compared to determine their similarities and differences. The result of the comparison is used to devise an integrated ontology that will enable querying on the integrated information.

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Cited By

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  • (2018)Towards Enterprise Data Management: Data Model Mapping2018 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)10.1109/WIECON-ECE.2018.8783035(72-74)Online publication date: Dec-2018
  • (2012)Bitmap Index in Ontology Mapping for Data IntegrationArabian Journal for Science and Engineering10.1007/s13369-012-0373-438:4(859-873)Online publication date: 5-Oct-2012
  • (2007)Ontology-based integration of data sources2007 10th International Conference on Information Fusion10.1109/ICIF.2007.4408086(1-8)Online publication date: Jul-2007

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cover image ACM Conferences
IHIS '05: Proceedings of the first international workshop on Interoperability of heterogeneous information systems
November 2005
90 pages
ISBN:1595931848
DOI:10.1145/1096967
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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Publication History

Published: 04 November 2005

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Author Tags

  1. UML class model
  2. data integration
  3. heterogeneous data sources
  4. ontology integration
  5. semantic integration

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View all
  • (2018)Towards Enterprise Data Management: Data Model Mapping2018 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)10.1109/WIECON-ECE.2018.8783035(72-74)Online publication date: Dec-2018
  • (2012)Bitmap Index in Ontology Mapping for Data IntegrationArabian Journal for Science and Engineering10.1007/s13369-012-0373-438:4(859-873)Online publication date: 5-Oct-2012
  • (2007)Ontology-based integration of data sources2007 10th International Conference on Information Fusion10.1109/ICIF.2007.4408086(1-8)Online publication date: Jul-2007

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