A Multi-Layout Design For Immersive Visualization of Hierarchical Network Data
David Bauer, Chengbo Zheng, Oh-Hyun Kwon, Kwan‐Liu Ma · 2024
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 mostly on singular, 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 design that promotes more efficient use of the available space in VR environments and allows users to explore hierarchical network data in immersive space effectively. We implement our design with a choice of four distinct views on the network. The resulting system leverages various existing layout techniques 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 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.