5 research outputs found
Visualizing Evolving Trees
Evolving trees arise in many real-life scenarios from computer file systems
and dynamic call graphs, to fake news propagation and disease spread. Most
layout algorithms for static trees, however, do not work well in an evolving
setting (e.g., they are not designed to be stable between time steps). Dynamic
graph layout algorithms are better suited to this task, although they often
introduce unnecessary edge crossings. With this in mind we propose two methods
for visualizing evolving trees that guarantee no edge crossings, while
optimizing (1) desired edge length realization, (2) layout compactness, and (3)
stability. We evaluate the two new methods, along with four prior approaches
(two static and two dynamic), on real-world datasets using quantitative
metrics: stress, desired edge length realization, layout compactness,
stability, and running time. The new methods are fully functional and available
on github