A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
XIMSA: eXtended Interactive Multimedia System for Auto-medication
CBMS '04 Proceedings of the 17th IEEE Symposium on Computer-Based Medical Systems
Data logistics as a means of integration in healthcare applications
Proceedings of the 2005 ACM symposium on Applied computing
Towards automatic merging of domain ontologies: The HCONE-merge approach
Web Semantics: Science, Services and Agents on the World Wide Web
Semi-automatic data migration in a self-medication knowledge-based system
WM'05 Proceedings of the Third Biennial conference on Professional Knowledge Management
A survey of schema-based matching approaches
Journal on Data Semantics IV
Data integration targeting a drug related knowledge base
EDBT'06 Proceedings of the 2006 international conference on Current Trends in Database Technology
A conceptual modeling and execution framework for process based scientific applications
Proceedings of the ACM first workshop on CyberInfrastructure: information management in eScience
An ontology based approach to automating data integration in scientific workflows
Proceedings of the 7th International Conference on Frontiers of Information Technology
Ontology consolidation in bioinformatics
APCCM '10 Proceedings of the Seventh Asia-Pacific Conference on Conceptual Modelling - Volume 110
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Data integration has become an essential issue in the development of information systems, especially in the biomedical and healthcare domain. Thereby it is required to have methods and tools available to support this effort in a systematic and structured manner, i.e. to have a conceptual, model based approach. We present such an approach; it is constituted by two components which are coping with the two main challenges of data integration: Data Logistics copes with the technical task of data transmission and data exchange; an ontology-based transformation copes with the semantic issues of data integration by dealing with the heterogeneity of formats, terminologies and ontologies. This paper shows how the synergetic combination of these concepts provides an adequate solution to data integration in healthcare applications.