Conventional dot plots use a constant dot size and are typically applied to show the frequency distribution of small data sets. Unfortunately, they are not designed for a high dynamic range of frequencies. We address this problem by introducing nonlinear dot plots. Adopting the idea of nonlinear scaling from logarithmic bar charts, our plots allow for dots of varying size so that columns with a large number of samples are reduced in height. For the construction of these diagrams, we introduce an efficient two-way sweep algorithm that leads to a dense and symmetrical layout. We compensate aliasing artifacts at high dot densities by a specifically designed low-pass filtering method. Examples of nonlinear dot plots are compared to conventional dot plots as well as linear and logarithmic histograms. Finally, we include feedback from an expert review.
%0 Journal Article
%1 888e7816f6314cbeb56a29b239b290f7
%A Rodrigues, Nils
%A Weiskopf, Daniel
%D 2018
%J IEEE Transactions on Visualization and Computer Graphics
%K B01 visus:weiskopf 2018 sfbtrr161 from:mueller vis(us) visus:rodrigns visus
%N 1
%P 616-625
%R 10.1109/TVCG.2017.2744018
%T Nonlinear Dot Plots
%U http://dx.doi.org/10.1109/TVCG.2017.2744018
%V 24
%X Conventional dot plots use a constant dot size and are typically applied to show the frequency distribution of small data sets. Unfortunately, they are not designed for a high dynamic range of frequencies. We address this problem by introducing nonlinear dot plots. Adopting the idea of nonlinear scaling from logarithmic bar charts, our plots allow for dots of varying size so that columns with a large number of samples are reduced in height. For the construction of these diagrams, we introduce an efficient two-way sweep algorithm that leads to a dense and symmetrical layout. We compensate aliasing artifacts at high dot densities by a specifically designed low-pass filtering method. Examples of nonlinear dot plots are compared to conventional dot plots as well as linear and logarithmic histograms. Finally, we include feedback from an expert review.
@article{888e7816f6314cbeb56a29b239b290f7,
abstract = {Conventional dot plots use a constant dot size and are typically applied to show the frequency distribution of small data sets. Unfortunately, they are not designed for a high dynamic range of frequencies. We address this problem by introducing nonlinear dot plots. Adopting the idea of nonlinear scaling from logarithmic bar charts, our plots allow for dots of varying size so that columns with a large number of samples are reduced in height. For the construction of these diagrams, we introduce an efficient two-way sweep algorithm that leads to a dense and symmetrical layout. We compensate aliasing artifacts at high dot densities by a specifically designed low-pass filtering method. Examples of nonlinear dot plots are compared to conventional dot plots as well as linear and logarithmic histograms. Finally, we include feedback from an expert review.},
added-at = {2020-10-09T12:34:20.000+0200},
author = {Rodrigues, Nils and Weiskopf, Daniel},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2a07cfd886f078e61372f4127c3d5b266/visus},
description = {Nonlinear Dot Plots},
doi = {10.1109/TVCG.2017.2744018},
interhash = {be3c265c223fc9f47fb22572053e3651},
intrahash = {a07cfd886f078e61372f4127c3d5b266},
journal = {IEEE Transactions on Visualization and Computer Graphics},
keywords = {B01 visus:weiskopf 2018 sfbtrr161 from:mueller vis(us) visus:rodrigns visus},
number = 1,
pages = {616-625},
timestamp = {2020-10-09T10:34:20.000+0200},
title = {Nonlinear Dot Plots},
url = {http://dx.doi.org/10.1109/TVCG.2017.2744018},
volume = 24,
year = 2018
}
