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.

翻译：可视化在处理复杂网络数据中扮演着关键角色。近年研究表明，扩展现实（XR）在沉浸式网络探索方面具有巨大潜力。与传统桌面环境相比，XR提供的额外深度线索有助于用户在特定任务中表现更优。然而，现有沉浸式网络可视化研究大多采用静态图布局来呈现数据。由于不存在适用于所有任务的通用最优布局，这带来了显著问题——布局的选择高度依赖网络类型及具体任务。我们提出了一种多布局方法，使用户能够在沉浸式空间中高效探索层次化网络数据。该成果系统整合了多种布局技术与交互方式，充分利用虚拟现实（VR）中的可用空间，根据任务需求及所需解析精度提供数据的最优视图。为评估该方法，我们开展了用户研究，将其与当前最先进的沉浸式网络可视化方案进行对比。受试者在不同空间范围内执行任务。结果表明，在空间聚焦场景及需整体观察网络时，我们的方法均优于基准方案。