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.

翻译：我们介绍并讨论在IEEE视觉化(VIS)文件中公布的图像的两年定性分析结果。具体地说,我们从13种可视化图像类型中得出了分类方法,用于区分可视化图像和若干图像特征。分类过程需要的时间比我们最初想象的要长得多,而且比我们最初想象的要困难得多。由此产生的分类和图像分析可以达到若干目的:研究社区的发展及其研究产出,便利为教学目的对可视化图像进行分类,为评估目的确定可视化设计,或推动在可视化标准化方面取得进展。除了分类和图像定性之外,我们还提供了6,833个有标签的图像数据集和一个在线工具,可用于探索和分析大套有标签的图像。因此,我们为讨论所使用的多种可视化方法及其在我们社区中如何出版和传播提供了便利。