Long-Term Temporal Data Representation of Personal Health Data

Abstract

The demand for timely, accurate personal health data is continuously growing. The increasing volume of generated health data from different sources creates new needs for a national, or international, future intergraded personal electronic health record (EHR). The database plays an important role in such a future health system. All kinds of personal health data must be stored and represented for a very long-term access. For this purpose we are working on a temporal object model in order to represent different versions of health data content, schemas and ontologies. Mappings between versions of these concepts are used for a temporal search in the stored data. In this paper we are introducing the use and purpose of the temporal model related to the examples of data and schema updates. A contribution of this work is to solve the EHR-case by using solutions from temporal databases, schema versioning and ontologies.