Dynamic Opacity Optimization for Scatter Plots

Figure 1. Scatter plots for two data sets (left side and right side) with varying numbers of data points rendered. The top row shows the appearance with an individual point opacity of 100%, while the second and third rows show the crowd-sourced results for the opacity scaling task and the results of our technique respectively. Scatterplots are an effective and commonly used technique to show the relationship between two variables. However, as the number of data points increases, the chart suffers from “over-plotting ” which obscures data points and makes the underlying distribution of the data difficult to discern. Reducing the opacity of the data points is an effective way to address over-plotting, however, setting the individual point opacity is a manual task performed by the chart designer. We present a user-driven model of opacity scaling for scatter plots. We built our model based on crowd-sourced responses to opacity scaling tasks using several synthetic data distributions, and then test our model on a collection of real-world data sets