Blue Noise Plots

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dc.contributor.authorOnzenoodt, Christian vanen_US
dc.contributor.authorSingh, Gurpriten_US
dc.contributor.authorRopinski, Timoen_US
dc.contributor.authorRitschel, Tobiasen_US
dc.contributor.editorMitra, Niloy and Viola, Ivanen_US
dc.date.accessioned2021-04-09T08:01:07Z
dc.date.available2021-04-09T08:01:07Z
dc.date.issued2021
dc.description.abstractWe propose Blue Noise Plots, two-dimensional dot plots that depict data points of univariate data sets. While often onedimensional strip plots are used to depict such data, one of their main problems is visual clutter which results from overlap. To reduce this overlap, jitter plots were introduced, whereby an additional, non-encoding plot dimension is introduced, along which the data point representing dots are randomly perturbed. Unfortunately, this randomness can suggest non-existent clusters, and often leads to visually unappealing plots, in which overlap might still occur. To overcome these shortcomings, we introduce Blue Noise Plots where random jitter along the non-encoding plot dimension is replaced by optimizing all dots to keep a minimum distance in 2D i. e., Blue Noise. We evaluate the effectiveness as well as the aesthetics of Blue Noise Plots through both, a quantitative and a qualitative user study. The Python implementation of Blue Noise Plots is available here.en_US
dc.description.number2
dc.description.sectionheadersVisualization
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume40
dc.identifier.doi10.1111/cgf.142644
dc.identifier.issn1467-8659
dc.identifier.pages425-433
dc.identifier.urihttps://doi.org/10.1111/cgf.142644
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf142644
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.titleBlue Noise Plotsen_US
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