Visualization plays an important role in understanding and in knowledge advancement. In initial stages of research, visualization helps to interactively explore the data, to get an overview and to create meaningful hypotheses; in later stages, it helps to control and to steer partially automated analyses; and in final stages, where fully automated data analysis procedures are available, it provides summaries of the results that foster our understanding. Visualization is also instrumental in design, being it e.g. the design of a pharmaceutically active compound or of a suitable clinical therapy.

The Visual Data Analysis department develops tools for extracting relevant information from data sets such as time series, spatiotemporal data and high-dimensional data. The data may result from observations or simulations, they may cover single or multiple scales, and they may be crisp or unsharp. We are interested in application-relevant structures hidden in the data; to reveal these structures, we develop methods for identifying, extracting, classifying, quantifying and visualizing them. Only in simple cases they are of pure mathematical character; typically the structures have to be modeled based on domain knowledge, considering the specific analysis questions and the data properties.

Therefore all research projects are embedded into applications. We work on problems in biology, biophysics, neuroscience, medicine, materials science, fluid mechanics and climate research. Furthermore, we develop solutions for simulation-based therapy planning to advance individualized medicine.

To build practically useful analysis systems, we develop, adapt and combine methods of data analysis, image analysis, geometry processing, computer graphics, data visualization, and human-computer interaction.

The software solutions are interactive, semi-automatic or fully automatic, depending on factors like complexity of the analysis tasks, achievable degree of automation and the amount of data to be analyzed. This open-minded approach enables us to solve complex tasks that cannot be fully automated and that require the human in the loop.

The developed research software is made available to application partners, with whom we collaborate closely to work out the analysis tasks, to evaluate the quality of the methods and to improve them. Mature solutions are transferred to industrial partners to make them widely available.