An integration of data sources with UML class models based on ontological analysis. Jamadhvaja, M. & Senivongse, T. In IHIS'05 - Proceedings of the First International Workshop on Interoperability of Heterogeneous Information Systems, pages 1-8, 2005.
abstract   bibtex   
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. Copyright 2005 ACM.
@inProceedings{
 id = {33420567-4d0e-3fae-8d60-1fb3ac74c636},
 title = {An integration of data sources with UML class models based on ontological analysis},
 type = {inProceedings},
 year = {2005},
 keywords = {Data integration,Heterogeneous data sources,Ontology integration,Semantic integration,UML class model},
 created = {2014-11-04T17:16:58.000Z},
 pages = {1-8},
 websites = {http://www.scopus.com/inward/record.url?eid=2-s2.0-33749001725&partnerID=tZOtx3y1},
 file_attached = {false},
 profile_id = {6b46cd49-f8a1-3799-91ac-6861cf9a050e},
 group_id = {f76fdab6-f3b3-324f-8ded-1f7ff6220077},
 last_modified = {2014-11-14T19:47:21.000Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 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. Copyright 2005 ACM.},
 bibtype = {inProceedings},
 author = {Jamadhvaja, Manachaya and Senivongse, Twittie},
 booktitle = {IHIS'05 - Proceedings of the First International Workshop on Interoperability of Heterogeneous Information Systems}
}

Downloads: 0