DoughNets: Visualising Networks Using Torus Wrapping

Time-Series & Network Graph VisualizationVisualization Perception & Cognition

We investigate visualisations of networks on a 2-dimensional torus topology, like an opened-up and flattened doughnut. That is, the network is drawn on a rectangular area while "wrapping" specific links around the border. Previous work on torus drawings of networks has been mostly theoretical, limited to certain classes of networks, and not evaluated by human readability studies. We offer a simple interactive layout approach applicable to general graphs. We use this to find layouts affording better aesthetics in terms of conventional measures like more equal edge length and fewer crossings. In two controlled user studies we find that torus layout with either additional context or interactive panning provided significant performance improvement (in terms of error and time) over torus layout without either of these improvements, to the point that it is comparable to standard non-torus layout.

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https://hci.top/en/papers/chi/32089/2020

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DOI: https://doi.org/10.1145/3313831.3376180
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CHI
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2020
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4 authors
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Time-Series & Network Graph Visualization, Visualization Perception & Cognition
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