Improving privacy in health care with an ontology-based provenance management system

Provenanc refers to the origin of information. Therefore, provenance is the metadata that record the history of data. As provenance is the derivation history of an object starting from its original source, the provenance information is used to analyse processes that are performed on an object and to track by whom these processes are performed. Thus, provenance shows the trustworthiness and quality of data. In a provenance management system in order to verify the trustworthy of provenance information, security needs must be also fulfilled. In this work, an ontology-based privacy-aware provenance management model is proposed. The proposed model is based on the Open Provenance Model, which is a common model for provenance. The proposed model aims to detect privacy violations, to reduce privacy risks by using permissions and prohibitions, and also to query the provenance data. The proposed model is implemented with Semantic Web technologies and demonstrated for the health care domain in order to preserve patients' privacy. Also, an infectious disease ontology and a vaccination ontology are integrated to the system in order to track the patients' vaccination history, to improve the quality of medical processes, the reliability of medical data, and the decision making in the health care domain.