  Visualizations themselves have become a data format. Akin to other data
formats such as text and images, visualizations are increasingly created,
stored, shared, and (re-)used with artificial intelligence (AI) techniques. In
this survey, we probe the underlying vision of formalizing visualizations as an
emerging data format and review the recent advance in applying AI techniques to
visualization data. We define visualization data as the digital representations
of visualizations in computers and focus on visualizations in information
visualization and visual analytic. We build our survey upon a corpus spanning
ten different fields in computer science with an eye toward identifying
important common interests. Our resulting taxonomy is organized around WHAT is
visualization data and its representation, WHY and HOW to apply AI to
visualization data. We highlight a set of common tasks that researchers apply
to the visualization data and present a detailed discussion of AI approaches
developed to accomplish those tasks. Drawing upon our literature review, we
discuss several important research questions surrounding the management and
exploitation of visualization data, as well as the role of AI in support of
those processes. We make the list of surveyed papers and related material
available online at ai4vis.github.io.
