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Sunspot Plots: Model‐based Structure Enhancement for Dense Scatter Plots
Author(s) -
Trautner T.,
Bolte F.,
Stoppel S.,
Bruckner S.
Publication year - 2020
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.14001
Subject(s) - scatter plot , computer science , representation (politics) , visualization , data mining , plot (graphics) , interpretation (philosophy) , data point , algorithm , mathematics , statistics , machine learning , politics , political science , law , programming language
Scatter 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.