We present and discuss the results of a qualitative analysis of visual representations from images. We labeled each image's essential stimuli, the removal of which would render a visualization uninterpretable. As a result, we derive a typology of 10 visualization types of defined groups. We describe the typology derivation process in which we engaged. The resulting typology and image analysis can serve a number of purposes: enabling researchers to study the evolution of the community and its research output over time, facilitating the categorization of visualization images for the purpose of research and teaching, allowing researchers and practitioners to identify visual design styles to further align the quantification of any visual information processor, be that a person or an algorithm observer, and it facilitates a discussion of standardization in visualization. In addition to the visualization typology from images, 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 labeled images. The tool and data set enable scholars to closely examine the diverse visual designs used and how they are published and communicated in our community. A pre-registration, a free copy of this paper, and all supplemental materials are available via osf.io/dxjwt.

翻译：我们展示并讨论了一项对图像中视觉表征进行定性分析的结果。我们标注了每幅图像的核心刺激要素——若移除该要素，可视化将无法被解读。由此推导出包含十种可视化类型的分类体系，并详细描述了分类体系的构建过程。该分类体系与图像分析可服务于多重目的：使研究者能够追踪学术共同体及其研究成果的演化轨迹；为研究与教学目的的可视化图像分类提供便利；帮助研究人员与从业者识别视觉设计风格，从而进一步协调任何视觉信息处理器（无论是人类观察者还是算法观察者）的量化标准；同时促进可视化标准化进程的讨论。除基于图像的可视化分类体系外，我们还提供了包含6,833幅标注图像的数据库及在线工具，用于探索分析这批大规模标注图像。该工具与数据集使学者能够细致审视多样化的视觉设计，以及这些设计如何在学术共同体中发表与传播。预注册信息、本文免费副本及所有补充材料可通过osf.io/dxjwt获取。