A 3D Visualization Technique for Large Scale Time-Varying Data

We represent time-varying data as polyline charts very often. At the same time, we often need to observe hundreds or even thousands of time-varying values in one chart. However, it is often difficult to understand such large-scale time-varying if all the values are drawn in a single polyline chart. This paper presents a polyline-based 3D time-varying data visualization technique. The technique places a set of polylines in the 3D space, where the X-axis denotes time, the Y-axis denotes values, and the polylines are arranged along the Z-axis. It provides two views: the first viewpoint has a view direction along Y-axis, and the second viewpoint has a view direction along Z-axis. The technique displays the overview of the data from the first viewpoint, and the detail of the specific parts of the data from the second viewpoint. It also detects frequent or outlier patterns by applying SAX (Symbolic Aggregate approXimation), and indicates them so that users can discover such characteristic patterns. This paper shows several interesting visualization examples to demonstrate the effectiveness of the presented technique.