As complex networks receive increasing interest by network analysts, there is a strong need for appropriate network visualizations that allow for visual analysis and exploration. This particularly holds for dynamic networks, comprising a sequence of graphs. The challenge here is to find coherent representations of successive networks that respect qualitative criteria of the drawing, while at the same time preserving the mental map the viewer has built from a previous drawing in the sequence.
Existing layout algorithms for static graphs have to be adapted to integrate constraints on maintaining stability between indiviual drawings. We modify the well-known energy-based graph layout method called stress-minimization to implement different strategies for dynamic graph drawing, e.g., aggregation to obtain one single layout for all individual graphs, or anchoring to constrain movement of vertices w.r.t. a given reference layout.
These fundamental strategies need to be systematically compared with respect to their ability to trade off between displaying structural properties and complying with the mental map. We evaluate them on structured randomly-generated graph sequences and real-world data sets, by means of their realization in the stress-minimization framework.
publications
The following list of publications covers only those, which are or were published during participation at the Graduiertenkolleg / PhD program.
Submitted Publications / Publications in Press
Brandes, U., Mader, M., Stress-Minimization Approaches for Offline Dynamic Graph Drawing. Proc., 19. International Symposium on Graph Drawing (GD), Springer-Verlag, September 2011, Springer-Verlag, in press.
Berthold, M., Brandes, U., Kötter, T., Mader, M., Nagel, U., Thiel, K., Pure spreading activation is pointless, 18. Conference on Information and Knowledge Management (CIKM), pp. 1915-1919, November 2009.
Internship at the National ICT Australia (NICTA) in Sydney, Australia, in the Visualisation and Analysis of Large and Complex Networks (VALACON) project
