ChartStory: Automated Partitioning, Layout, and Captioning of Charts into Comic-Style Narratives

TL;DR

ChartStory automates the creation of data-driven comic-style narratives from charts by applying design principles, characterizing charts, and recommending partitioning, layout, and captioning, supported by user interactions and extensive evaluation.

Contribution

This paper introduces ChartStory, a novel system that automates the generation of comic-style data stories from charts, integrating design principles into an advanced pipeline with user refinement.

Findings

ChartStory produces data comics that compare favorably to manual creations.

Automated recommendations effectively support narrative generation.

User interactions enhance visual refinement of data comics.

Abstract

Visual data storytelling is gaining importance as a means of presenting data-driven information or analysis results, especially to the general public. This has resulted in design principles being proposed for data-driven storytelling, and new authoring tools being created to aid such storytelling. However, data analysts typically lack sufficient background in design and storytelling to make effective use of these principles and authoring tools. To assist this process, we present ChartStory for crafting data stories from a collection of user-created charts, using a style akin to comic panels to imply the underlying sequence and logic of data-driven narratives. Our approach is to operationalize established design principles into an advanced pipeline which characterizes charts by their properties and similarity, and recommends ways to partition, layout, and caption story pieces to serve a narrative. ChartStory also augments this pipeline with intuitive user interactions for visual refinement of generated data comics. We extensively and holistically evaluate ChartStory via a trio of studies. We first assess how the tool supports data comic creation in comparison to a manual baseline tool. Data comics from this study are subsequently compared and evaluated to ChartStory's automated recommendations by a team of narrative visualization practitioners. This is followed by a pair of interview studies with data scientists using their own datasets and charts who provide an additional assessment of the system. We find that ChartStory provides cogent recommendations for narrative generation, resulting in data comics that compare favorably to manually-created ones.