Combining Extended Table Lens and Treemap Techniques for Visualizing Tabular Data

摘要

We present a framework for visualizing large tabular data that combines two views: the table view and the treemap view. The table view extends the known table lens as follows: We cluster related elements to reduce subsampling artifacts and achieve table size independent rendering time; we use multiple-column sorting to create scenario-specific data hierarchies on the fly; and we use shaded cushions to show data structure and variation. Hierarchies built in the table view are shown in a customizable treemap view. One can choose both layout and rendering by a few clicks, effectively creating visual scenarios on-the-fly. We illustrate our framework on real-life stock data.