Computing Hive Plots: A Combinatorial Framework

TL;DR

This paper introduces a combinatorial framework for computing hive plots that optimizes visual properties like edge length and crossings through vertex partitioning, axis ordering, and vertex arrangement, supported by algorithms and experiments.

Contribution

It extends traditional hive plots by providing a systematic, optimization-based framework addressing key visual quality metrics and implementing algorithms for practical graph visualization.

Findings

Optimized hive plots with fewer edge crossings.

Improved visual clarity through axis and vertex ordering.

Framework applicable to real-world graph visualization tasks.

Abstract

Hive plots are a graph visualization style placing vertices on a set of radial axes emanating from a common center and drawing edges as smooth curves connecting their respective endpoints. In previous work on hive plots, assignment to an axis and vertex positions on each axis were determined based on selected vertex attributes and the order of axes was prespecified. Here, we present a new framework focusing on combinatorial aspects of these drawings to extend the original hive plot idea and optimize visual properties such as the total edge length and the number of edge crossings in the resulting hive plots. Our framework comprises three steps: (1) partition the vertices into multiple groups, each corresponding to an axis of the hive plot; (2) optimize the cyclic axis order to bring more strongly connected groups near each other; (3) optimize the vertex ordering on each axis to minimize edge crossings. Each of the three steps is related to a well-studied, but NP-complete computational problem. We combine and adapt suitable algorithmic approaches, implement them as an instantiation of our framework and show in a case study how it can be applied in a practical setting. Furthermore, we conduct computational experiments to gain further insights regarding algorithmic choices of the framework. The code of the implementation and a prototype web application can be found on OSF.