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：我们呈现并讨论了基于图像的可视化表征的定性分析结果。我们对每幅图像的关键刺激要素进行标注——若去除这些要素，则该可视化将变得不可解读。据此，我们推导出包含10种可视化类型的分类体系。本文描述了这一分类体系的推导过程。该分类体系及图像分析可服务于多重目的：帮助研究者研究该领域及其研究成果随时间的演变过程；为研究与教学场景下的可视化图像分类提供便利；使研究人员与从业人员能够识别视觉设计风格，进一步统一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；同时促进可视化领域中标准化的讨论。除基于图像的可视化分类体系外，我们还提供了一个包含6,833张标注图像的数据集，以及一个用于探索与分析大规模标注图像的在线工具。该工具与数据集使学者能够深入检视所使用的多样化视觉设计，以及这些设计在该领域中的发表与传播方式。预注册信息、本文免费副本及所有补充材料均可在osf.io/dxjwt获取。