Edge Bundling in Information Visualization

The edge, which can encode relational data in graphs and multidimensional data in parallel coordinates plots, is an important visual primitive for encoding data in information visualization research. However, when data become very large, visualizations often suffer from visual clutter as thousands of edges can easily overwhelm the display and obscure underlying patterns. Many edge-bundling techniques have been proposed to reduce visual clutter in visualizations. In this survey, we briefly introduce the visual-clutter problem in visualizations. Thereafter, we review the cost-based, geometry-based, and image-based edge-bundling methods for graphs, parallel coordinates, and flow maps. We then describe the various visualization applications that use edge-bundling techniques and discuss the evaluation studies concerning the effectiveness of edge-bundling methods. An edge-bundling taxonomy is proposed at the end of this survey.