VMap: An Interactive Rectangular Space-filling Visualization for Map-like Vertex-centric Graph Exploration
Jiayi Xu, Han-Wei Shen

TL;DR
VMap is an innovative interactive visualization tool that creates map-like, rectangular layouts for graph exploration, optimizing aspect ratios, edge routing, and data encoding for clearer, more effective graph analysis.
Contribution
VMap introduces a novel combination of algorithms for rectangular partitioning, edge routing, and heuristic optimization to improve graph visualization quality and efficiency.
Findings
Better aspect ratio quality on synthetic data.
Improved encoding accuracy on real-world datasets.
Faster layout generation compared to existing methods.
Abstract
We present VMap, a map-like rectangular space-filling visualization, to perform vertex-centric graph exploration. Existing visualizations have limited support for quality optimization among rectangular aspect ratios, vertex-edge intersection, and data encoding accuracy. To tackle this problem, VMap integrates three novel components: (1) a desired-aspect-ratio (DAR) rectangular partitioning algorithm, (2) a two-stage rectangle adjustment algorithm, and (3) a simulated annealing based heuristic optimizer. First, to generate a rectangular space-filling layout of an input graph, we subdivide the 2D embedding of the graph into rectangles with optimization of rectangles' aspect ratios toward a desired aspect ratio. Second, to route graph edges between rectangles without vertex-edge occlusion, we devise a two-stage algorithm to adjust a rectangular layout to insert border space between…
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Taxonomy
TopicsData Visualization and Analytics · Complex Network Analysis Techniques · Human Mobility and Location-Based Analysis
MethodsSPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings
