Visualization design techniques to match viewer thinking and goals
Crossing the Chasm: Bridging Visual Augmentations and Designer Intent
Human-Computer Interaction
Summary
Visualizations often use extras like notes or animations to guide what people pay attention to and understand. The authors found that existing rules mainly help with showing data but not with these extras aimed at sharing bigger meanings or ideas. They created a framework that connects the designer's communication goals with how viewers think, showing how different techniques like annotations or animations help achieve these goals. This helps make clearer visual stories and could enable tools to better support designers in the future.
What this means in practice
- •For data visualization designers: Use the design space to select visual augmentations that directly support viewers' cognitive goals and improve communication effectiveness.
- •For visualization software developers: Build visualization tools that suggest or automate augmentations aligned with designer goals and viewer cognition based on the proposed framework.$Commercial implications: Enables creation of smarter design software that helps users create effective augmented visualizations, increasing market value and usability.
Authors
Luke S. Snyder, Maureen C. Stone, Jeffrey Heer
Abstract
To direct attention and communicate context, visualization designers often employ augmentations such as annotations, animated transitions, and stylistic layouts. While graphical perception principles can helpfully prescribe effective low-level representations of data, they lack guidance for augmentations that service higher-level communication goals. To bridge this gap, we contribute a design space that frames designer intent as viewer-oriented cognitive behaviors, grounding communicative aims in actionable visualization design techniques, including both visual encodings and augmentations. This design space consists of common augmentation tactics (annotation, animation, stylized encodings, etc.) that implement design strategies (spotlighting, sequencing, association, etc.) to achieve higher-level design goals (observe, interpret, introspect), often simultaneously. We demonstrate the analytic and generative value of our design space with examples across varied designer objectives. We discuss how our contributions help align designer intent with reader takeaways, pave the way for readers to learn more effectively, and enable future (semi-)automated systems to support visualization designers in achieving their communication goals.