Computing NodeTrix Representations of Clustered Graphs
Giordano Da Lozzo, Giuseppe Di Battista, Fabrizio Frati, Maurizio, Patrignani
TL;DR
This paper investigates the computational complexity of creating NodeTrix visualizations for clustered graphs, providing NP-completeness results and polynomial algorithms, and introduces a JavaScript library to improve visual clarity.
Contribution
It offers new complexity insights into NodeTrix planarity and presents algorithms and a tool to enhance visualization quality.
Findings
NP-completeness results for planarity testing
Polynomial-time algorithms for specific cases
A JavaScript library to reduce edge crossings
Abstract
NodeTrix representations are a popular way to visualize clustered graphs; they represent clusters as adjacency matrices and inter-cluster edges as curves connecting the matrix boundaries. We study the complexity of constructing NodeTrix representations focusing on planarity testing problems, and we show several NP-completeness results and some polynomial-time algorithms. Building on such algorithms we develop a JavaScript library for NodeTrix representations aimed at reducing the crossings between edges incident to the same matrix.
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Taxonomy
TopicsData Management and Algorithms · Data Visualization and Analytics · Advanced Graph Theory Research