Anonymization for sensitive Linked Stream Data in Bio-Surveillance systems

Due to the huge amounts of data being produced at a dramatic pace, privacy becomes one of the biggest issues in our everyday life. Data is often collected from individuals by surveillance systems. They process and analyze large amount of data e.g. to prevent spread of a disease. In this use case, data appears often as streamed data. An improvement of streamed data is standardization or comparability of observed physical phenomenon. Linked Stream Data LSD improves this by publishing and consuming structured data on the web. LSD connects different LSD data sources that allows the re-identification of certain individuals, even the containing data itself is properly anonymized. This is a contradiction to Austrias privacy act DSG, where every individual-related data has to be removed. One possible solution for this problem is an algorithm that anonymizes each data view before it is released. This project tries to solve the problem of privacy in LD to allow automatic processing of it.