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Comparing Nodes of Multivariate Graphs Through Dynamic Layout Adaptations

Philip Berger, Sebastian Beleites, Christian Tominski

TL;DR

This work tackles the difficulty of visually comparing multivariate graph attributes within node-link diagrams by introducing a comparison lens that performs dynamic, local layout adaptations. Starting from a topology-driven base layout, the lens injects an attribute-driven arrangement for nodes near a selected focus node, while preserving the global graph structure through focus+context semantics and smooth transitions. Visual enhancements such as color-coded similarity, radial guides, and edge-clutter reduction support intuitive comparison inside the lens. The approach enables targeted, cognitive-friendly comparisons in large, multivariate graphs and is demonstrated on a soccer-player network, with avenues for richer in-lens representations and formal user studies as future work.

Abstract

Visual comparison is an important task in the analysis of multivariate graphs. However, comparison of topological features of a graph with respect to its data attributes for different portions of the data remains challenging because there is no single visual representation that would suit the dynamic nature of comparative analyses. To facilitate the visual comparison in node-link diagrams, we propose the comparison lens as a focus+context approach for dynamic layout adaptation. The core idea is to start with a topology-driven layout and locally inject an attribute-driven layout based on the multivariate similarity of node attributes. This facilitates comparison tasks on a local level while preserving the user's overall mental map of the graph topology. Additional visual enhancements, including color-coding, reduction of edge clutter, and radial guides, further support the comparison. To fit the lens to different comparison situations, it can be configured via user-controllable parameters. To demonstrate the utility of our approach, we use it for comparison in a real-world dataset of soccer players.

Comparing Nodes of Multivariate Graphs Through Dynamic Layout Adaptations

TL;DR

This work tackles the difficulty of visually comparing multivariate graph attributes within node-link diagrams by introducing a comparison lens that performs dynamic, local layout adaptations. Starting from a topology-driven base layout, the lens injects an attribute-driven arrangement for nodes near a selected focus node, while preserving the global graph structure through focus+context semantics and smooth transitions. Visual enhancements such as color-coded similarity, radial guides, and edge-clutter reduction support intuitive comparison inside the lens. The approach enables targeted, cognitive-friendly comparisons in large, multivariate graphs and is demonstrated on a soccer-player network, with avenues for richer in-lens representations and formal user studies as future work.

Abstract

Visual comparison is an important task in the analysis of multivariate graphs. However, comparison of topological features of a graph with respect to its data attributes for different portions of the data remains challenging because there is no single visual representation that would suit the dynamic nature of comparative analyses. To facilitate the visual comparison in node-link diagrams, we propose the comparison lens as a focus+context approach for dynamic layout adaptation. The core idea is to start with a topology-driven layout and locally inject an attribute-driven layout based on the multivariate similarity of node attributes. This facilitates comparison tasks on a local level while preserving the user's overall mental map of the graph topology. Additional visual enhancements, including color-coding, reduction of edge clutter, and radial guides, further support the comparison. To fit the lens to different comparison situations, it can be configured via user-controllable parameters. To demonstrate the utility of our approach, we use it for comparison in a real-world dataset of soccer players.
Paper Structure (10 sections, 2 figures)

This paper contains 10 sections, 2 figures.

Table of Contents

  1. Introduction
  2. Related Work
  3. Approach
  4. Requirements
  5. Approach Overview
  6. Lens-based Dynamic Layout Adaptation
  7. Visual Enhancements
  8. User-controllable Lens Parameters
  9. Use Case
  10. Conclusion

Figures (2)

  • Figure 1: Schematic illustration of the lens-based dynamic layout adaptation (left) and visual enhancements (right) for comparison of nodes. Left: The focus node is centered (red arrow), nodes that meet the similarity threshold are placed according to their similarity with respect to the focus (green arrows), and nodes that do not meet the similarity threshold are moved out of the lens (blue arrows). Right: Different shades of green indicate attribute-based node similarity and radial guides are embedded in the lens to further support the visual comparison.
  • Figure 2: Applying the comparison lens to a graph of soccer players. (a) Basic node-link diagram showing the graph topology. (b) Activating the lens pushing irrelevant nodes out of the lens, whereas similar, and hence, relevant nodes are positioned inside the lens based on their similarity. (c) Through edge clutter reduction and radial guides, the comparison inside the lens is enhanced.