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dc.contributor.authorTrautner, Thomasen_US
dc.contributor.authorBolte, Fabianen_US
dc.contributor.authorStoppel, Sergejen_US
dc.contributor.authorBruckner, Stefanen_US
dc.contributor.editorViola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatianaen_US
dc.date.accessioned2020-05-24T13:01:56Z
dc.date.available2020-05-24T13:01:56Z
dc.date.issued2020
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14001
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14001
dc.description.abstractScatter plots are a powerful and well-established technique for visualizing the relationships between two variables as a collection of discrete points. However, especially when dealing with large and dense data, scatter plots often exhibit problems such as overplotting, making the data interpretation arduous. Density plots are able to overcome these limitations in highly populated regions, but fail to provide accurate information of individual data points. This is particularly problematic in sparse regions where the density estimate may not provide a good representation of the underlying data. In this paper, we present sunspot plots, a visualization technique that communicates dense data as a continuous data distribution, while preserving the discrete nature of data samples in sparsely populated areas. We furthermore demonstrate the advantages of our approach on typical failure cases of scatter plots within synthetic and real-world data sets and validate its effectiveness in a user study.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/]
dc.subjectHuman centered computing
dc.subjectVisualization techniques
dc.subjectInformation visualization
dc.subjectEmpirical studies in visualization
dc.titleSunspot Plots: Model-based Structure Enhancement for Dense Scatter Plotsen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersMultivariate Data Visualization
dc.description.volume39
dc.description.number3
dc.identifier.doi10.1111/cgf.14001
dc.identifier.pages551-563


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  • 39-Issue 3
    EuroVis 2020 - Conference Proceedings

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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License