Visualizing high-dimensional data on a 2D canvas is generally challenging. It becomes significantly more difficult when multiple time-steps are to be presented, as the visual clutter quickly increases. Moreover, the challenge to perceive the significant temporal evolution is even greater. In this paper, we present a method to plot temporal high-dimensional data in a static scatterplot; it uses the established PCA technique to project data from multiple time-steps. The key idea is to extend each individual displacement prior to applying PCA, so as to skew the projection process, and to set a projection plane that balances the directions of temporal change and spatial variance. We present numerous examples and various visual cues to highlight the data trajectories, and demonstrate the effectiveness of the method for visualizing temporal data.

在 2D 画布上可视化高维数据通常具有挑战性。当要呈现多个时间步时，这变得更加困难，因为视觉混乱迅速增加。此外，感知显着时间演变的挑战更大。在本文中，我们提出了一种在静态散点图中绘制时间高维数据的方法；它使用已建立的 PCA 技术来投影来自多个时间步的数据。关键思想是在应用 PCA 之前扩展每个单独的位移，从而使投影过程发生倾斜，并设置一个平衡时间变化和空间变化方向的投影平面。我们提供了许多示例和各种视觉提示来突出数据轨迹，并展示了可视化时间数据方法的有效性。