Master theses

Sensitive genomics data is increasing in its usefulness for research and clinical use. In the KNoWS group, we are investigating how storing and sharing personal genomic and health data can be achieved while maintaining data privacy. A crucial challenge for privacy protection is in defining and implementing policies over such data, especially when trying to make those policies granular and flexible. To address these challenges, we aim to leverage cutting-edge data storage technologies such as Solid Pods and actively evolving standards such as the Open Digital Rights Language (ODRL). Specifically, by synergizing these technologies, we will build a proof-of-concept solution that implements granular privacy policies over sensitive health and genomics data.

The student will be part of our core team at IDLab in the KNoWS group. They will develop and implement a data policy enforcement schema for health care data stored in Solid Pods. This schema will include various roles and levels of authentication. The student will work with ODRL to define this schema and develop an interface to apply it to a test data set of Solid Pods containing example clinical and genomic data. They will learn how to work with Solid Pods, RDF and non-RDF clinical and genomic data, Solid Pod interfaces, and semantic web ontologies and schemas. The ultimate goal is to implement a framework for labelling genomics and health data within multiple Solid Pods with granular, flexible data ODRL privacy policy definitions along with a set of user roles that dictate authorization levels. We will evaluate our implementation on schema completeness, implementation functionality, as well as data labelling and policy enforcement capabilities via querying the Solid Pods.