Gemini: A Grammar and Recommender System for AnimatedTransitions in Statistical Graphics

TL;DR

Gemini introduces a declarative grammar and recommendation system that simplifies designing animated transitions in statistical graphics, reducing effort and improving consistency through staged specifications and perceptually-informed ranking.

Contribution

This work presents Gemini, a novel grammar and recommendation system for animated transitions, enabling easier and more effective design of animations in statistical graphics.

Findings

Most Gemini-designed animations are exactly replicable.

Many animations can be achieved with minimal edits to Gemini suggestions.

Gemini's suggestions reduce common errors in animation design.

Abstract

Animated transitions help viewers follow changes between related visualizations. Specifying effective animations demands significant effort: authors must select the elements and properties to animate, provide transition parameters, and coordinate the timing of stages. To facilitate this process, we present Gemini, a declarative grammar and recommendation system for animated transitions between single-view statistical graphics. Gemini specifications define transition "steps" in terms of high-level visual components (marks, axes, legends) and composition rules to synchronize and concatenate steps. With this grammar, Gemini can recommend animation designs to augment and accelerate designers' work. Gemini enumerates staged animation designs for given start and end states, and ranks those designs using a cost function informed by prior perceptual studies. To evaluate Gemini, we conduct both a formative study on Mechanical Turk to assess and tune our ranking function, and a summative study in which 8 experienced visualization developers implement animations in D3 that we then compare to Gemini's suggestions. We find that most designs (9/11) are exactly replicable in Gemini, with many (8/11) achievable via edits to suggestions, and that Gemini suggestions avoid multiple participant errors.