2026-07-25T06:45:39Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:21299 2024-10-28T09:51:05Z ddc:004 open_access

Bundling-Aware Graph Drawing Archambault, Daniel Liotta, Giuseppe Nöllenburg, Martin Piselli, Tommaso Tappini, Alessandra Wallinger, Markus Edge Bundling Experimental Comparison Graph Sparsification Edge bundling algorithms significantly improve the visualization of dense graphs by reducing the clutter of many edges visible on screen by bundling them together. As such, bundling is often viewed as a post-processing step applied to a drawing, and the vast majority of edge bundling algorithms consider a graph and its drawing as input. Another way of thinking about edge bundling is to simultaneously optimize both the drawing and the bundling. In this paper, we investigate methods to simultaneously optimize a graph drawing and its bundling. We describe an algorithmic framework which consists of three main steps, namely Filter, Draw, and Bundle. We then propose two alternative implementations and experimentally compare them against the state-of-the-art approach and the simple idea of drawing and subsequently bundling the graph. The experiments confirm that bundled drawings created by our framework outperform previous approaches according to standard quality metrics for edge bundling. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Daniel Archambault and Giuseppe Liotta and Martin Nöllenburg and Tommaso Piselli and Alessandra Tappini and Markus Wallinger 2024 Is Part Of LIPIcs, Volume 320, 32nd International Symposium on Graph Drawing and Network Visualization (GD 2024) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.GD.2024.15 urn:nbn:de:0030-drops-212995 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GD.2024.15 eng https://creativecommons.org/licenses/by/4.0/legalcode