What Makes a Data-GIF Understandable?

TL;DR

This paper investigates how design factors influence the understandability of data-GIFs, providing insights and guidelines based on empirical studies with 118 participants.

Contribution

It identifies key design principles for data-GIFs and fills a knowledge gap by systematically analyzing factors affecting their clarity and effectiveness.

Findings

Animation encoding impacts message clarity

Context preservation enhances understanding

Repetition influences viewer comprehension

Abstract

GIFs are enjoying increasing popularity on social media as a format for data-driven storytelling with visualization; simple visual messages are embedded in short animations that usually last less than 15 seconds and are played in automatic repetition. In this paper, we ask the question, "What makes a data-GIF understandable?" While other storytelling formats such as data videos, infographics, or data comics are relatively well studied, we have little knowledge about the design factors and principles for "data-GIFs". To close this gap, we provide results from semi-structured interviews and an online study with a total of 118 participants investigating the impact of design decisions on the understandability of data-GIFs. The study and our consequent analysis are informed by a systematic review and structured design space of 108 data-GIFs that we found online. Our results show the impact of design dimensions from our design space such as animation encoding, context preservation, or repetition on viewers' understanding of the GIF's core message. The paper concludes with a list of suggestions for creating more effective Data-GIFs.