In temporal (or event-based) networks, time is a continuous axis, with real-valued time coordinates for each node and edge. Computing a layout for such graphs means embedding the node trajectories and edge surfaces over time in a 2D + t space, known as the space-time cube. Currently, these space-time cube layouts are visualized through animation or by slicing the cube at regular intervals. However, both techniques present problems ranging from sub-par performance on some tasks to loss of precision. In this paper, we present TimeLighting, a novel visual analytics approach to visualize and explore temporal graphs embedded in the space-time cube. Our interactive approach highlights the node trajectories and their mobility over time, visualizes node "aging", and provides guidance to support users during exploration. We evaluate our approach through two case studies, showing the system's efficacy in identifying temporal patterns and the role of the guidance features in the exploration process.

翻译：在时序（或基于事件）网络中，时间是一个连续轴，每个节点和边都拥有实值时间坐标。为此类图计算布局，意味着将节点轨迹和边曲面随时间嵌入到二维加时间（2D + t）空间中，该空间被称为时空立方体。目前，这些时空立方体布局通过动画或按固定间隔切片立方体进行可视化。然而，这两种技术都存在从部分任务表现欠佳到精度损失等问题。本文提出TimeLighting——一种在时空立方体中可视化并探索时序图的新型视觉分析方法。该交互式方法突出显示节点轨迹及其随时间变化的移动性，可视化节点"老化"过程，并提供引导以支持用户探索。我们通过两个案例研究评估该方法，展示了系统识别时序模式的有效性以及引导特征在探索过程中的作用。