HCDec 19, 2021

A Multi-Layout Design for Immersive Visualization of Network Data

arXiv:2112.10272v3
Originality Incremental advance
AI Analysis

This addresses the challenge of optimizing network exploration in virtual reality for users, though it is incremental as it builds on existing immersive visualization methods.

The paper tackles the problem of static graph layouts in immersive network visualization by introducing a multi-layout approach, which outperforms the state-of-the-art baseline in user studies for tasks at varying spatial scopes.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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