SideKnot: Revealing relation patterns for graph visualization

Graph is an intuitive and powerful tool to present relationships between entities. Efficiently visualizing graphs with node-link diagrams is a great challenge due to visual clutter induced by edge crossing and node-edge overlapping. Many edge bundling methods are proposed to disclose high-level edge patterns. Though previous methods can successfully reveal the coarse graph structure, the relation patterns at individual node level can be overlooked. In addition, many edge bundling algorithms are computationally complex to prevent them from scaling up for extremely large graphs. In this paper, we propose SideKnot, an efficient node-based bundling method to cluster and knot edges. SideKnot is light, runs faster than most existing algorithms, and can disclose the relation patterns of an individual node such as its standing in the graph and pattern of relations with its neighbors.