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Uniform timeslicing of dynamic graphs has been used due to its convenienceand uniformity across the time dimension. However, uniform timeslicing does nottake the data set into account, which can generate cluttered timeslices withedge bursts and empty timeslices with few interactions. The graph mining filedhas explored nonuniform timeslicing methods specifically designed to preservegraph features for mining tasks. In this paper, we propose a nonuniformtimeslicing approach for dynamic graph visualization. Our goal is to createtimeslices of equal visual complexity. To this end, we adapt histogramequalization to create timeslices with a similar number of events, balancingthe visual complexity across timeslices and conveying more important details oftimeslices with bursting edges. A case study has been conducted, in comparisonwith uniform timeslicing, to demonstrate the effectiveness of our approach.

Nonuniform Timeslicing of Dynamic Graphs Based on Visual Complexity