Overplotting: Unified solutions under Abstract Rendering

It is impossible to directly visualize all of the items of a large dataset at once. Often, the number of items exceeds the number of pixels. Since direct representation is not a reliable option, a variety of methods have been developed for dealing with indirect representation. Such methods include clustering and intelligent filtering to reduce the number of items being considered in the first place. However, these techniques impose a high computational and interpretation costs. The alternative is to employ techniques to directly deal with the over-plotting that occurs. that occurs when there are too many items to display without overlapping. Over-plotting techniques include alpha composition, color weaving and selective plotting. Each of these has variants that yield different cognitive or computational optimizations. Unfortunately, most advanced over-plotting techniques are wrapped up in specific libraries. Experimenting with different techniques is cumbersome because they have not been provided with uniform interfaces or in a single runtime. This paper presents Abstract Rendering, a recasting of the rendering process that enables concise expression of many over-plotting techniques. Furthermore, the Abstract Rendering formulation yields efficient execution strategies. Combined, it is practical to explore different over-plotting techniques for large data without requiring significant alteration to existing pipelines.