An RDF based semantic approach to model temporal relations in health records

Progression of diseases may vary for each patient due to genetic makeup, life style, or previous health history. Even for well-known medical conditions, temporal signatures can be different for specific genotypes. Secondary use of health records can help us to identify these signatures. We propose an RDF based approach for modelling the temporal relations in health records. RDF graphs compared to relational data representations provide advantages with their inherent notion of a hierarchy and a temporal model. In this work, we suggest a new approach to representing temporal relations in RDF graphs. The proposed approach will help to improve the efficiency of data mining by including a more relevant set of patient attributes.