Erato: Cooperative Data Story Editing via Fact Interpolation

TL;DR

Erato is a cooperative system that simplifies data story creation by allowing users to provide keyframes and using interpolation to generate smooth, coherent narratives, thus making data storytelling more accessible and efficient.

Contribution

This work introduces a novel interpolation algorithm and a human-machine system for cooperative data story editing using keyframes, enhancing efficiency and coherence in data storytelling.

Findings

Interpolation generates coherent story content.

System helps users create stories more efficiently.

Evaluation confirms effectiveness and usefulness.

Abstract

As an effective form of narrative visualization, visual data stories are widely used in data-driven storytelling to communicate complex insights and support data understanding. Although important, they are difficult to create, as a variety of interdisciplinary skills, such as data analysis and design, are required. In this work, we introduce Erato, a human-machine cooperative data story editing system, which allows users to generate insightful and fluent data stories together with the computer. Specifically, Erato only requires a number of keyframes provided by the user to briefly describe the topic and structure of a data story. Meanwhile, our system leverages a novel interpolation algorithm to help users insert intermediate frames between the keyframes to smooth the transition. We evaluated the effectiveness and usefulness of the Erato system via a series of evaluations including a Turing test, a controlled user study, a performance validation, and interviews with three expert users. The evaluation results showed that the proposed interpolation technique was able to generate coherent story content and help users create data stories more efficiently.