  We present and discuss the results of a two-year qualitative analysis of
images published in IEEE Visualization (VIS) papers. Specifically, we derive a
typology of 13 visualization image types, coded to distinguish visualizations
and several image characteristics. The categorization process required much
more time and was more difficult than we initially thought. The resulting
typology and image analysis may serve a number of purposes: to study the
evolution of the community and its research output over time, to facilitate the
categorization of visualization images for the purpose of teaching, to identify
visual designs for evaluation purposes, or to enable progress towards
standardization in visualization. In addition to the typology and image
characterization, we provide a dataset of 6,833 tagged images and an online
tool that can be used to explore and analyze the large set of tagged images. We
thus facilitate a discussion of the diverse visualizations used and how they
are published and communicated in our community.
