Persistent Homology Guided Force-Directed Graph Layouts
arXiv:1712.05548 · doi:10.1109/TVCG.2019.2934802
Abstract
Graphs are commonly used to encode relationships among entities, yet their abstractness makes them difficult to analyze. Node-link diagrams are popular for drawing graphs, and force-directed layouts provide a flexible method for node arrangements that use local relationships in an attempt to reveal the global shape of the graph. However, clutter and overlap of unrelated structures can lead to confusing graph visualizations. This paper leverages the persistent homology features of an undirected graph as derived information for interactive manipulation of force-directed layouts. We first discuss how to efficiently extract 0-dimensional persistent homology features from both weighted and unweighted undirected graphs. We then introduce the interactive persistence barcode used to manipulate the force-directed graph layout. In particular, the user adds and removes contracting and repulsing forces generated by the persistent homology features, eventually selecting the set of persistent homology features that most improve the layout. Finally, we demonstrate the utility of our approach across a variety of synthetic and real datasets.
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Cited by in corpus (6)
- Knowledge Graphs in Practice: Characterizing their Users, Challenges, and Visualization Opportunities
- ZigzagNetVis: Suggesting temporal resolutions for graph visualization using zigzag persistence
- Discrete Morse Sandwich: Fast Computation of Persistence Diagrams for Scalar Data -- An Algorithm and A Benchmark
- TopoAct: Visually Exploring the Shape of Activations in Deep Learning
- Stable and Discriminative Topological Graph Analysis
- Topological Simplifications of Hypergraphs