Computing Schematic Layouts for Spatial Hypergraphs on Concentric Circles and Grids

Set systems can be visualized in various ways. An important distinction between techniques is whether the elements have a spatial location that is to be used for the visualization; for example, the elements are cities on a map. Strictly adhering to such location may severely limit the visualization...

Full description

Saved in:

Bibliographic Details
Published in:	Computer graphics forum 2022-09, Vol.41 (6), p.316-335
Main Authors:	Bekos, M.A., Dekker, D.J.C., Frank, F., Meulemans, W., Rodgers, P., Schulz, A., Wessel, S.
Format:	Article
Language:	eng
Subjects:	Bends Clutter Computation computational geometry Criteria Graph theory Graphs hypergraph drawing information visualization Layouts modelling Optimization Visualization
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	Set systems can be visualized in various ways. An important distinction between techniques is whether the elements have a spatial location that is to be used for the visualization; for example, the elements are cities on a map. Strictly adhering to such location may severely limit the visualization and force overlay, intersections and other forms of clutter. On the other hand, completely ignoring the spatial dimension omits information and may hide spatial patterns in the data. We study layouts for set systems (or hypergraphs) in which spatial locations are displaced onto concentric circles or a grid, to obtain schematic set visualizations. We investigate the tractability of the underlying algorithmic problems adopting different optimization criteria (e.g. crossings or bends) for the layout structure, also known as the support of the hypergraph. Furthermore, we describe a simulated‐annealing approach to heuristically optimize a combination of such criteria. Using this method in computational experiments, we explore the trade‐offs and dependencies between criteria for computing high‐quality schematic set visualizations. Three set visualizations of the same dataset. Current techniques either fix the positions of elements on a map (left) or discard all spatial information (right). We investigate techniques to generate schematic, roughly spatial drawings (middle).
ISSN:	0167-7055 1467-8659