Visualization Methods for Graphs&Networks
Inevitably, the projection of most graph structures on two-dimensional screens will create errors and therefore visually wrong impressions. In the past, two types of methods have been developed to minimize projection errors and distribute them in a visually pleasing way. The first group of methods, force-directed layouts, interpret the links of a graph as physical springs, while stress-based methods minimize an energy function, which aims to map graph distances faithfully.
Overview
Abstract
Inevitably, the projection of most graph structures on two-dimensional screens will create errors and therefore visually wrong impressions. In the past, two types of methods have been developed to minimize projection errors and distribute them in a visually pleasing way. The first group of methods, force-directed layouts, interpret the links of a graph as physical springs, while stress-based methods minimize an energy function, which aims to map graph distances faithfully. A unified description of both method types allows to create optimal parameters for both and even to specify new, better methods for most graphs. The addition of vector-based constraints enable systems to render graphs with different layouts and under varying perspectives. Finally, I will show that deviating from all kinds of physical metaphors is a good idea to create even better projection methods.
Brief Biography
Prof. Deussen graduated at Karlsruhe Institute of Technology and is a professor at University of Konstanz, one of the Excellence Universities in Germany. 2008-2020 he was a visiting professor at the Chinese Academy of Science in Shenzhen (SIAT). 2019-2020 he served as President of the Eurographics Association. His areas of interest are Information Visualization, non-photorealistic rendering techniques, sampling theory. He also contributed papers to geometry processing and image-based modeling methods. Currently he is one of the speakers of the Excellence Cluster "Centre for the Advanced Study of Collective Behaviour” at University of Konstanz. In this endeavor animal collectives ranging from insects, fish, birds up to bonobos and humans are measured and quantitatively analyzed to find and formulate rules that constitute swarm behaviour. To this end he creates virtual environments in order to study how animals react to visual signals and visualizes results from various experiments using methods form information visualization.
