Most of what we do at SynoSys is based on data. We share an affection for large scale, heterogeneous datasets obtained in natural experiments, so data that was not generated with a scientific intention but rather as a byproduct of typically digital technologies, like cell phones, individual mobility patterns, online platforms, social media and citizen science projects. In data science we emphasize the explorative nature of science. Metaphorically speaking, we do data sciences without a map - just with a compass, curiosity and intuition.

Almost all systems we investigate at SynoSys are dynamic. We are interested in complex dynamical systems, e.g. the spread of infections in a population, evolutionary processes, behavior and adaptation, collective behavior, pattern formation, to name a few. Unsurprisingly, dynamical systems science is a core methodological area at the center. Particularly in conjunction with network science we are trying to understand the connection between network structures and their imprint on dynamical phenomena that are driven by them.

Network science pervades our research. It offers new perspectives on many complex systems in biology, social science and technology. Network science can reveal hidden structures in complex systems and, more importantly, point out similiarities beween systems that may seem unrelated at first glance and identify universalities and fundamental design principles. Network science plays a key role in our research on human mobility, infectious disease dynamics, and computational social science.

SynoSys is not only about bridging gaps between traditionally disconnected scientific disciplines. We are also about removing barriers between the scientific community and the public. Digital technologies of today permit the creating of citizen science projects and citizen science experiments in which citizens contribute in large scale data donation projects, engage in the scientific discourse, participate on all levels in the knowledge creating process. A good example is the Corona Data Donation Project which we launched during the COVID-19 pandemic.

Research into the complexity of social systems is represented by the young investigators group. New types of data enable the quantitative description and modelling of social phenomena on a large scale, such as social network structures, public opinion formation, collective behaviour or longitudinal societal; at the same time, digitalization is also changing the mechanisms at work, e.g. through digital communication on social media or algorithmic curation of information. Our aim is to view these systems and developments through the lens of complex systems, but with a strong empirical and experimental perspective from the social sciences.