Visualization plays two essential roles in data-driven scientific discovery. First, visualization is a key tool for data exploration and hypothesis generation. Second, visualization facilitates communication of insights and findings. In a typical analysis scenario, however, visualization for exploration and visualization for communication are two separate processes. They often involve different software tools and data representations. Even though sophisticated interactive visualization tools are available to explore data sets, findings are usually shared in form of static images or functionally limited interactive visualizations. While these capture a particular state, they do not include any information about the exploration process that lead to the finding.
In this talk I will describe how by capturing the visual exploration process, visualizations can be made reproducible and sharable. My collaborators and I leverage such data about the analysis process to allow analysts to create "vistories", which are interactive and annotated figures, that communicate insights and findings.