  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.
