NeatSankey: Sankey diagrams with improved readability based on node positioning and edge bundling

Abstract

Sankey diagrams are widely used to visualize event sequence data. However, when the data volume is large, its readability is affected by dense edge crossings, excessive swing amplitude, and small crossover angles, while it is computationally intensive to obtain an optimal layout. In this paper, we propose NeatSankey, a balanced method that generates Sankey diagrams smoothly. It can be laid out quickly with good readability when Sankey diagrams are very complex. At the same time, to comprehensively evaluate the readability of Sankey diagrams, we use three evaluation metrics: crossing number, swing amplitude, and layout coverage. Firstly, we use a heuristic layout algorithm and a force-directed algorithm to adjust the node layout to minimize the edge crossings and swing amplitude with edge widths considered. Secondly, to better reduce the dense confusion caused by edge crossings, we introduce a edge bundling algorithm based on attribute similarity. We present three evaluations: a comprehensive comparison of our results with state-of-the-art techniques, user studies with thirty volunteers, and a case study of two datasets. Our evaluations demonstrate the effectiveness and practicability of the NeatSankey.