Biomedical data integration – capturing similarities while preserving disparities

One of the challenges of healthcare data processing, analysis and warehousing is the integration of data gathered from disparate and diverse data sources. Promoting the adoption of worldwide accepted information standards along with common terminologies and the use of technologies derived from semantic web representation, is a suitable path to achieve that. To that end, the HL7 V3 Reference Information Model (RIM) [1] has been used as the underlying information model coupled with the Web Ontology Language (OWL) [2] as the semantic data integration technology. In this paper we depict a biomedical data integration process and demonstrate how it was used for integrating various data sources, containing clinical, environmental and genomic data, within Hypergenes, a European Commission funded project exploring the Essential Hypertension [3] disease model.