Collaborative Research Center
Quantitative Methods for Visual Computing
We are living in a data society in which data is generated at amazing speed; individuals, companies, organizations, and governments are on the brink of being drawn into a massive deluge of data. The great challenge is to extract the relevant information from vast amounts of data and communicate it effectively.
Typical scenarios include decision and policy making for urban and environmental planning or understanding relationships and dependencies in complex networks, e.g., social networks or networks from the field of bioinformatics. These scenarios are not only of interest to specialized experts; in fact, there is a trend toward including the broad public, which requires the information to be presented in a reliable, faithful, and easy-to-understand fashion.
Visual computing can play a key role in extracting and presenting the relevant information.
In visual computing research the aspect of quantification is often neglected. The SFB-TRR 161 seeks to close this gap.
The long-term goal is to strengthen the research field by establishing the paradigm of quantitative science in visual computing.