COMSYS is invested in interdisciplinary research activities that tackle life sciences for several years. In this context, our research activities are not limited to a specific theme. Instead, we look at a wide range of research challenges (with our applied cooperation partners). In particular, we have prior experience with the following topics:

• Interoperability: FAIRifying medical (research) data and ensuring interoperability between different processing steps are timely challenges. Addressing them promises to advance Big Data applications and boost privacy research.
• Consent: For healthcare research, informed consent is a key principle. Unfortunately, obtaining consent is a challenging endeavor given the lack of usable and accepted solutions in the area. Thus, novel solutions are needed.
• Confidentiality: Privacy is a critical aspect when handling (sensitive) patient data. Exploiting data globally and handling different data types calls for future research activities. Specifically, we apply well-known concepts from information security to provide confidentiality guarantees for involved stakeholders.
• Representation: Given the diversity of medical research data (e.g., *-omics) and data formats (tabular data, image data, etc.), finding, linking, and joining (sparse) data is not a trivial task. Accordingly, COMSYS is looking into promising approaches and new directions in the area.
• Distributed Analytics: Concepts like federated learning are particularly important for medical contexts, where data might be scattered across institutions. Hence, we look into these concepts to identify attack vectors, close privacy leaks, and showcase new application areas.
• Data Quality: New findings depend on a solid foundation. In the life sciences setting, data quality and corresponding guarantees are essential (particularly in distributed settings). Consequently, we also research technical building blocks that promise to improve data quality (in distributed settings).