Not As Easy As You Think-Experiences and Lessons Learnt from Creating a Visualization Image Typology

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 visual designs and several image characteristics. The categorization process required much more time and was more difficult than we anticipated. 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 research or teaching, to identify visual design styles, 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. The tool and data set enable a close examination of the diverse visualizations used and how they are published and communicated in our community.