Interactive Data Exploration with Plotscaper and the Hidden Algebra of Interactive Graphics

Music City Center 

Interactive data visualization has become a staple of modern data presentation. However, despite the abundance of interactive data visualization packages, creating rich and sophisticated interactive figures still remains a challenging task. Notably, certain advanced interactive features such as generalized linked selection are lacking in many existing tools. This gap may stem from a subtle yet profound issue: the underlying interconnectedness of visualization components. Specifically, while many current systems based on the Grammar of Graphics strive to treat graphics, statistics, and interaction as independent, modular components (which can be freely combined), I instead argue for the inherent inadequacy of this approach due to the existence of deep links between all of these elements.

In this talk, I will explore the interconnectedness of interactive figure components and the challenges it presents for building interactive data visualization systems. I will also present plotscaper, a new R package developed to investigate and refine some of these ideas, as well as to provide a practical tool for data exploration. My goal is to convince you that, if we want to build truly general and robust interactive data visualization systems, we need to ground our thinking in some fundamental algebraic concepts, particularly ones from category theory.

Interactive data visualization

Data visualization

R

Linked selection

Category theory