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A Multi-Layout Design for Immersive Visualization of Network Data

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arxiv 2112.10272 v3 pith:JIQIDP62 submitted 2021-12-19 cs.HC

classification cs.HC
keywords networkdataimmersivevisualizationapproachlayouttasksmulti-layout
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Visualization plays a vital role in making sense of complex network data. Recent studies have shown the potential of using extended reality (XR) for the immersive exploration of networks. The additional depth cues offered by XR help users perform better in certain tasks when compared to using traditional desktop setups. However, prior works on immersive network visualization rely on mostly static graph layouts to present the data to the user. This poses a problem since there is no optimal layout for all possible tasks. The choice of layout heavily depends on the type of network and the task at hand. We introduce a multi-layout approach that allows users to effectively explore hierarchical network data in immersive space. The resulting system leverages different layout techniques and interactions to efficiently use the available space in VR and provide an optimal view of the data depending on the task and the level of detail required to solve it. To evaluate our approach, we have conducted a user study comparing it against the state of the art for immersive network visualization. Participants performed tasks at varying spatial scopes. The results show that our approach outperforms the baseline in spatially focused scenarios as well as when the whole network needs to be considered.

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  1. DP-LENS: A Density-Aware Polyfocal Lens with Topology-Driven Auto-Routing for Occlusion Management in Immersive 3D Analytics

    cs.HC 2026-07 conditional novelty 6.0 of 10

    A density-aware polyfocal fisheye lens with voice-initiated topology-driven auto-routing reduced task time, cognitive load, and physical fatigue in two VR user studies.

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