标题： 重新定位模式：对复合视觉变量的全面方法 显示英文标题

标题： Reframing Pattern: A Comprehensive Approach to a Composite Visual Variable

摘要： 我们提出了一种新的综合理论，用于解释、探索和利用模式作为可视化中的视觉变量。 尽管模式长期以来一直用于数据编码，并且至今仍然具有价值，但其概念基础却很脆弱：研究文献和实践中使用的概念和术语不一致，使得有效使用模式以及开展相关研究变得困难。 为了解决这个问题，我们进行了一项跨学科的全面文献综述，澄清了“模式”和“纹理”使用中的模糊之处。 结果，我们提出了一个关于模式的新的一致性处理方式，即作为由结构化图形基元组组成的复合视觉变量，这些基元可以单独或共同用于编码数据。 这一新且广泛适用的表述为视觉变量模式开辟了一个较大的设计空间，我们将之形式化为一个新的系统，包括三组变量：基元的空间排列、基元之间的外观关系，以及描述单个基元的视网膜视觉变量。 我们展示了我们的模式系统如何与现有的可视化理论相关联，并突出了可视化设计的机会。 我们进一步探讨了基于复杂空间排列的模式，展示了其解释力，并将我们的概念化与地图和制图学的更广泛理论联系起来。 作者版本和附加材料可在OSF上获取：osf.io/z7ae2。 显示英文摘要

摘要： We present a new comprehensive theory for explaining, exploring, and using pattern as a visual variable in visualization. Although patterns have long been used for data encoding and continue to be valuable today, their conceptual foundations are precarious: the concepts and terminology used across the research literature and in practice are inconsistent, making it challenging to use patterns effectively and to conduct research to inform their use. To address this problem, we conduct a comprehensive cross-disciplinary literature review that clarifies ambiguities around the use of "pattern" and "texture". As a result, we offer a new consistent treatment of pattern as a composite visual variable composed of structured groups of graphic primitives that can serve as marks for encoding data individually and collectively. This new and widely applicable formulation opens a sizable design space for the visual variable pattern, which we formalize as a new system comprising three sets of variables: the spatial arrangement of primitives, the appearance relationships among primitives, and the retinal visual variables that characterize individual primitives. We show how our pattern system relates to existing visualization theory and highlight opportunities for visualization design. We further explore patterns based on complex spatial arrangements, demonstrating explanatory power and connecting our conceptualization to broader theory on maps and cartography. An author version and additional materials are available on OSF: osf.io/z7ae2.