Abstract:
This talk presents data comics, a way of presenting stories with data inspired by the way traditional comics communicate visually and narrate stories. The lecture will talk though examples from our collection (http://datacomics.net, https://statscomics.github.io) and why data comics are a special format. It will discuss design patterns as tool to analyze existing comics and to create data comics. Eventually, the talk will explain how to explain visualizations in data comics that your readers might not be familiar with (http://visualizationcheatsheets.github.io). The lecture finishes with an outlook into methods and approaches for you to create your own data comics.

Bio:
Benjamin is a Lecturer in Design Informatics and Visualization at the University of Edinburgh. His research designs and investigates interactive information visualization interfaces to help people explore, communicate, and understand data across media such as screens, mixed reality, paper, and physicalizations. Before joining the University of Edinburgh in 2017, Benjamin worked as a postdoc at Harvard University (Visual Computing Group), Monash University, as well as the Microsoft-Research Inria Joint Centre. Benjamin was visiting researcher at the University of Washington and Microsoft Research in 2015. He obtained his PhD in 2014 from the Université Paris Sud where he worked at the Aviz Group at Inria. The PhD thesis entitled Connections, Changes, and Cubes: Unfolding Dynamic Networks for Visual Exploration got awarded an honorable mention as the Best Thesis by the IEEE Visualization Committee. In 2019, Benjamin got awarded the Eurographics Young Researcher Award, and in 2021 the TVCG Significant New Researcher Award (https://virtual.ieeevis.org/year/2021/awards.html).