Drawing Dynamic Graphs Without Timeslices
This addresses a visualization challenge for researchers and practitioners working with dynamic graph data, offering an incremental improvement over existing timeslice-based methods.
The paper tackles the problem of visualizing dynamic graphs without relying on timeslices, which can miss temporal features or slow computation, by introducing a new model and algorithm called DynNoSlice that shows advantages over timeslicing on continuous datasets.
Timeslices are often used to draw and visualize dynamic graphs. While timeslices are a natural way to think about dynamic graphs, they are routinely imposed on continuous data. Often, it is unclear how many timeslices to select: too few timeslices can miss temporal features such as causality or even graph structure while too many timeslices slows the drawing computation. We present a model for dynamic graphs which is not based on timeslices, and a dynamic graph drawing algorithm, DynNoSlice, to draw graphs in this model. In our evaluation, we demonstrate the advantages of this approach over timeslicing on continuous data sets.