The visual analysis of graphs includes a diversity of different aspects (structure, attributes, spatial and temporal context). Because of their increasing size and a shifting analysis focus, their visualization becomes more and more difficult and necessitates a multitude of different visualization techniques. This thesis aims at solving these challenges by introducing novel solutions regarding the visualization of the different aspects, the reduction of the size using abstraction and selection approaches as well as the combination and switch between different visualizations.
