Kolloquium WiSe 2022/23

Research in visualization is often motivated by the endeavor to improve on the illustration of data: in order to better communicate data to others and to gain deeper insights into complex datasets, possibly from a variety of data sources. In the medical domain, the data can include for example patient data, health records as well as biologic data such as genome. Insights to be obtained from data may relate inter alia to the spreading of diseases, evolutionary analysis and virus mutations. The tasks include both retrospective analysis for finding the patient zero and modelling the spreading of a disease, as well predictive modelling of virus mutations and future disease spreading. The COVID-19 pandemic has confronted this general motivation for our research to a need for practical solutions. Infection control experts needed to quickly gain insights into novel datasets and to communicate the insights to colleagues and to a broader public, requiring quick and efficient visualization solutions.

New methods, tools, and methodologies have popped up from basic and from applied research. New data was collected, model results were produced that required rapid analysis. Multi-disciplinary teams worked and applied solutions to the new challenges resulting from the pandemic. The rapid response was only possible by leveraging on the experience and past research. Thus, the talk will take a larger historical perspective and present specific solutions from own experience, including reflections on data, task and user triangle as well as the challenges of multidisciplinary working styles.