Data Comics: Sequential Art for Data-Driven Storytelling

Data comics are a novel method for storytelling using sequential art constructed from data-driven visualizations.

In this paper, Zhenpeng Zhao, Rachael Marr, and Niklas Elmqvist draw on the visual language of comic books to tell stories about data and visualize information in ways that are familiar and comprehensible to every-day readers. Data comics can be created as snapshots or live visualizations, and embellished with speech  bubbles and motion lines, among other symbols. The web-based Data Comics app allows users to capture data-driven content on the web, arrange and decorate panels illustrating their findings, and view their finished comics.

The full article is available here.