Improved Visual Saliency of Graph Clusters with Orderable Node-Link Layouts - Archive ouverte HAL
Article Dans Une Revue IEEE Transactions on Visualization and Computer Graphics Année : 2025

Improved Visual Saliency of Graph Clusters with Orderable Node-Link Layouts

Une meilleure saillance visuelle des clusters de graphes avec les diagrammes nœuds-liens ordonnables

Résumé

Graphs are often used to model relationships between entities. The identification and visualization of clusters in graphs enable insight discovery in many application areas, such as life sciences and social sciences. Force-directed graph layouts promote the visual saliency of clusters, as they bring adjacent nodes closer together, and push non-adjacent nodes apart. At the same time, matrices can effectively show clusters when a suitable row/column ordering is applied, but are less appealing to untrained users not providing an intuitive node-link metaphor. It is thus worth exploring layouts combining the strengths of the node-link metaphor and node ordering. In this work, we study the impact of node ordering on the visual saliency of clusters in orderable node-link diagrams, namely radial diagrams, arc diagrams and symmetric arc diagrams. Through a crowdsourced controlled experiment, we show that users can count clusters consistently more accurately, and to a large extent faster, with orderable node-link diagrams than with three state-of-the art force-directed layout algorithms, i.e., `Linlog', `Backbone' and `sfdp'. The measured advantage is greater in case of low cluster separability and/or low compactness. A free copy of this paper and all supplemental materials are available at https://osf.io/kc3dg/
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hal-04668352 , version 1 (06-08-2024)

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  • HAL Id : hal-04668352 , version 1

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Nora Al-Naami, Nicolas Médoc, Matteo Magnani, Mohammad Ghoniem. Improved Visual Saliency of Graph Clusters with Orderable Node-Link Layouts. IEEE Transactions on Visualization and Computer Graphics, In press. ⟨hal-04668352⟩

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