In today’s data-driven world, visual data storytelling is enjoying increasing popularity, which communicates insights backed by data and illustrated with visualization. Among a variety of data stories, there is a recent surge of interest in enhancing storytelling with animated visualizations, which attracts a broad audience and elevates stories beyond static narration. However, despite the growing use and desirable properties, there is still little understanding of what designs are featured in animated data stories and what makes them understandable. Prior research has rarely investigated the effective way to create animated data stories for general users.

This thesis aims to explore the design space and guidance for animated data stories, and support the authoring of narrative visuali...[ Read more ]

In today’s data-driven world, visual data storytelling is enjoying increasing popularity, which communicates insights backed by data and illustrated with visualization. Among a variety of data stories, there is a recent surge of interest in enhancing storytelling with animated visualizations, which attracts a broad audience and elevates stories beyond static narration. However, despite the growing use and desirable properties, there is still little understanding of what designs are featured in animated data stories and what makes them understandable. Prior research has rarely investigated the effective way to create animated data stories for general users.

This thesis aims to explore the design space and guidance for animated data stories, and support the authoring of narrative visualization with short animations. The first work investigates design patterns in animated data stories, particularly focusing on a short and concise form named data-GIFs. GIFs embed simple visual messages in short animations that usually last less than 15 seconds and are played in automatic repetition. A structured design space and a list of design suggestions are summarized by a systematic review of real-world data-GIFs and two user studies. The second work takes a step further to investigate how to support authoring of data-GIFs, and propose a lightweight authoring tool for tabular data, namely, DataGifify. Inspired by short video effects and tools, DataGifify leverages the design space of data-GIFs and applies narrative effects to animated visualization. It follows a preview-based authoring paradigm and integrates a step-wise interface in the creation process. Finally, the third work explores the authoring tool for text data, and presents DancingWords that allows users to create animated word clouds with story-oriented interactions and automatic layouts. The galleries of generated examples and feedback from user studies demonstrate the expressiveness and usefulness of the proposed tools.