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

Authors:
Manachaya Jamadhvaja;Twittie Senivongse
Affiliations:
Chulalongkorn University, Bangkok, Thailand;Chulalongkorn University, Bangkok, Thailand
Venue:
Proceedings of the first international workshop on Interoperability of heterogeneous information systems
Year:
2005

Citing 10
Cited 0

A translation approach to portable ontology specifications

Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Query processing in the SIMS information mediator

Readings in agents
Context interchange: new features and formalisms for the intelligent integration of information

ACM Transactions on Information Systems (TOIS)
OBSERVER: An Approach for Query Processing in Global Information Systems Based on Interoperation Across Pre-Existing Ontologies

Distributed and Parallel Databases
Data integration: a theoretical perspective

Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
OIL: An Ontology Infrastructure for the Semantic Web

IEEE Intelligent Systems
PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment

Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
An Integration Method for the Specification of Rule-Oriented Mediators

DANTE '99 Proceedings of the 1999 International Symposium on Database Applications in Non-Traditional Environments
Semantic Conflict Resolution Ontology (SCROL): An Ontology for Detecting and Resolving Data and Schema-Level Semantic Conflicts

IEEE Transactions on Knowledge and Data Engineering
FCA-MERGE: bottom-up merging of ontologies

IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1

Quantified Score

Hi-index	0.00

Visualization

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.