A Privacy-Aware Semantic Model for Provenance Management Ozgu Can and Dilek Yilmazer Ege University, Department of Computer Engineering, 35100 Bornova-Izmir, Turkey ozgu.can@ege.edu.tr, dilekyilmazer@gmail.com Abstract. The history of data has a crucial importance almost in every scientific application. In order to trust the correctness of data, the ability to determine the origin of data becomes an important issue. Provenance information summarizes the origin of items, the history of the ownership of items and the actions performed on them. Ensuring that data is kept safe from corruption or illegal accesses and detecting privacy breaches on data should be achieved by integrating provenance concepts with security concepts. Information such as an individuals infectious disease history is highly sensitive and should not be revealed to an unauthorized user. This historical data needs privacy. We propose a privacy-aware provenance management model by creating policies and querying provenance data to detect policy violations. We illustrate our proposed model by integrating it with infectious disease and vaccination domains. Keywords: Provenance Management, Process Tracking, Semantic Web, Healthcare Information Systems. 1 Introduction In data management, data is continuously being created, updated, copied and deleted. Due to this dynamic nature, the background knowledge of data needs to be trusted in order to determine the quality on query results. Hence, the knowledge of provenance is essential for the integrity of data. As provenance is widely used in art, archeology and archives, it has also an importance in forensics and legal proceedings of data [1]. Provenance information (also called lineage ) describes the origins and the history of data in its life cycle [2]. Thereby, provenance is metadata, not data [3]. Data provenance concerns how the data was processed and by whom. Thus, providing data provenance helps users to value and trust the data. Data provenance has been studied in several fields and researchers have used provenance data to trace data from different sources, such as by whom the file is created, updated or copied. Researchers need to trust that the provenance information associated with the data is accurate. In order to make provenance records trustworthy; completeness, integrity, availability, confidentiality and efficiency should be guaranteed [4]. Therefore, the provenance model should be integrated with a security model. S. Closs et al. (Eds.): MTSR 2014, CCIS 478, pp. 162–169, 2014. c  Springer International Publishing Switzerland 2014