Data Illustrator

with John Thompson, Alan Wilson, Mira Dontcheva, James Delorey, Sam Grigg, Bernard Kerr, John Stasko

Try Data Illustrator Now

Graphic designers have been producing infographics and charts well before the recent proliferation of computer generated visualizations. As visualization becomes an increasingly popular medium for storytelling and communication, there is a renewed and growing interest to understand visualization creation from the perspective of graphic design.

Recent work such as Data-Driven Guides and d3-gridding has been experimenting with a “lazy data binding” approach: all visualizations are initially vector graphics. Designers use familiar tools to draw, select and manipulate vector graphics, and apply data encoding only when it is necessary. These attempts are promising, but only work for a limited set of use cases.

We present a novel framework that describes the composition and generation of diverse visualizations based on the "lazy data binding" approach. This framework builds on familiar graphic design concepts such as anchor points and segments, and introduces novel primitives for data-driven authoring.

Informed by this framework, we design and implement the Data Illustrator system. Data Illustrator offers direct manipulation techniques for easy and flexible visualization creation. We demonstrate the expressive power of our approach through a range of well-known, real-world examples.


Data Illustrator: Augmenting Vector Design Tools with Lazy Data Binding for Expressive Visualization Authoring.
PDF (CHI 2018, Best Paper Award)


Web app, demos, and tutorials


Talk at CHI 2018

Related Project

Data-Driven Guides