Information visualization limits itself, per definition, to the domain of symbolic information. This paper discusses arguments why the field should also consider forms of data that are not symbolically encoded, including physical traces and material indicators. Continuing a provocation presented by Pat Hanrahan in his 2004 IEEE Vis capstone address, this paper compares physical traces to visualizations and describes the techniques and visual practices for producing, revealing, and interpreting them. By contrasting information visualization with a speculative counter model of autographic visualization, this paper examines the design principles for material data. Autographic visualization addresses limitations of information visualization, such as the inability to directly reflect the material circumstances of data generation. The comparison between the two models allows probing the epistemic assumptions behind information visualization and uncovers linkages with the rich history of scientific visualization and trace reading. The paper begins by discussing the gap between data visualizations and their corresponding phenomena and proceeds by investigating how material visualizations can bridge this gap. It contextualizes autographic visualization with paradigms such as data physicalization and indexical visualization and grounds it in the broader theoretical literature of semiotics, science and technology studies (STS), and the history of scientific representation. The main section of the paper proposes a foundational design vocabulary for autographic visualization and offers examples of how citizen scientists already use autographic principles in their displays, which seem to violate the canonical principles of information visualization but succeed at fulfilling other rhetorical purposes in evidence construction. The paper concludes with a discussion of the limitations of autographic visualization, a roadmap for the empirical investigation of trace perception, and thoughts about how information visualization and autographic visualization techniques can contribute to each other.

中文翻译：

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按代理的数据-作为自动图形化的材料痕迹。

根据定义，信息可视化将自身限制在符号信息的范围内。本文讨论了为什么该字段还应考虑未经过符号编码的数据形式（包括物理迹线和物质指示符）的争论。继Pat Hanrahan在2004年IEEE Vis顶点演讲中提出的挑衅之后，本文将物理痕迹与可视化进行了比较，并描述了产生，揭示和解释它们的技术和视觉实践。通过将信息可视化与自动可视化的推测计数器模型进行对比，本文研究了材料数据的设计原理。签名可视化解决了信息可视化的局限性，例如无法直接反映数据生成的实质情况。两种模型之间的比较可以探究信息可视化背后的认知假设，并揭示与科学可视化和痕迹读取的丰富历史之间的联系。本文首先讨论数据可视化及其对应现象之间的鸿沟，然后通过研究材料可视化如何弥合这一鸿沟来进行探讨。它通过诸如数据物理化和索引可视化等范式将自动图形化可视化，并将其基于符号学，科学技术研究（STS）以及更广泛的科学表示历史的更广泛的理论文献中。本文的主要部分提出了用于自动图像可视化的基本设计词汇，并提供了有关公民科学家如何在其显示器中使用自动图像原理的示例，这似乎违反了信息可视化的规范原则，但成功地实现了证据构建中的其他修辞目的。本文最后讨论了自动图像可视化的局限性，实证研究痕迹感知的路线图，以及有关信息可视化与自动图像可视化技术如何相互促进的思想。