  Overplotting of data points is a common problem when visualizing large
datasets in a scatterplot, particularly when mapping nominal dimensions to one
of the scatterplot axes. Transparency, aggregation, and jittering have
previously been suggested to address this issue, but these solutions all have
drawbacks for assessing the data distribution in the plot. We propose
gatherplots, an extension of scatterplots that eliminates overplotting,
particularly for nominal variables. In gatherplots, every data point that maps
to the same position coalesces to form a stacked entity, thereby making it
easier to compare the absolute and relative sizes of data groupings. The size
and aspect ratio of data points can also be changed dynamically to make it
easier to compare the composition of different groups. Furthermore, several
embedded interaction techniques support slicing and dicing the gatherplot by
pivoting on particular dimensions, ranges, and values in the dataset. Our
evaluation shows that gatherplots enable users from the general public to judge
the relative portion of subgroups more quickly and more correctly than when
using conventional scatterplots with jittering. Furthermore, a review conducted
by a group of visualization experts evaluated and commented on the gatherplot
design.
