A Programmatic Definition of Visualization Insights, Objectives, and Tasks

Researchers have devised many theoretical models for specifying users' objectives, tasks, and insights as they interact with a visualization system. These representations are essential for understanding the insight discovery process, such as when inferring user interaction patterns that lead to insight or assessing the rigor of reported insights. However, many theoretical models can be notoriously difficult to translate into code, limiting their applicability across multiple studies. This paper calls attention to the consistent structures that recur across the visualization literature and describes how they connect multiple theoretical representations of insight. We present a toolkit called Pyxis that makes it easy to specify insights, tasks, and objectives using these consistent structures, enabling a wider audience of researchers and developers to adopt the corresponding models. Furthermore, our evaluation scenarios show that Pyxis enables a broader and deeper understanding of the structure and properties of insight compared to theoretical representations alone