Translating electronic health records (EHRs) into ontologies and then into other forms of electronic information is a challenging task. This paper focuses on the transformation of openEHR and Health Level Seven (HL7) standards. This process is mainly done to enable the sharing of health information between various healthcare systems. The authors first familiarize the reader with the HL7 and openEHR models. The paper then presents some information on the existing systems that are applied to this problem of translation: the Jini Health Interoperability Framework (HIF-J), Artemis, and plug and play electronic patient records (PPEPR).

The authors provide a software architecture of their own to solve the aforementioned challenge; this architecture uses open-source ontology matching tools. They propose using manual ontology matching and present four algorithms used for mapping. The proposal to perform some amount of ontology mapping manually is a very interesting approach. The authors claim that the manual process increases the accuracy of the mapping technique.

Overall, I found this to be a very well-written paper. It attempts to provide a solution to a very complex problem in health informatics. The presented architecture should be used to develop at least a prototype of a real system, which can be tested with the aim of developing effective ontology transformation software.