Automated visualization design navigates a tension between symbolic systems and generative models. Constraint solvers enforce structural and perceptual validity, but the rules they require are difficult to author and too rigid to capture situated design knowledge. Large language models require no formal rules and can reason about contextual nuance, but they prioritize popular conventions over empirically grounded best practices. We address this tension by proposing a cataloging scheme that structures visualization design knowledge as natural-language guidelines with semantically typed metadata. This allows experts to author knowledge that machines can query. An expert study ($N=18$) indicates that practitioners routinely adapt heuristics to situational factors such as audience and communicative intent. To capture this reasoning, guideline sections specify not only advice but also the contexts where it applies, exceptions that invalidate it, and the sources from which it derives. We demonstrate the scheme's expressiveness by cataloging 744 guidelines drawn from cognitive science, accessibility standards, data journalism, and research on rhetorical aspects of visual communication. We embed guideline sections in a vector space, opening the knowledge itself to structural analysis. This reveals conflicting advice across sources and transferable principles between domains. Rather than replacing constraint-based tools, our scheme provides what they lack: situated guidance that generative systems can retrieve to ground their reasoning, users can verify against cited sources, and experts can author as knowledge evolves.

翻译：自动化可视化设计在符号系统与生成模型之间存在着一种张力。约束求解器能够强制保证结构的有效性和感知的有效性，但其所需的规则难以编写且过于僵化，无法捕捉情境化的设计知识。大语言模型无需形式化规则，能够推理上下文细微差别，但它们优先考虑的是流行的惯例，而非基于实证的最佳实践。我们通过提出一种编目方案来解决这一张力，该方案将可视化设计知识结构化为带有语义类型元数据的自然语言指南。这使得专家能够编写可供机器查询的知识。一项专家研究（N=18）表明，从业者通常会根据受众和沟通意图等情境因素来调整启发式方法。为了捕捉这种推理过程，指南部分不仅规定了建议，还指明了其适用的情境、使其失效的例外情况以及其来源依据。我们通过编目来自认知科学、无障碍标准、数据新闻学以及视觉传达修辞学研究的744条指南，展示了该方案的表达能力。我们将指南部分嵌入向量空间，使得知识本身能够接受结构分析。这揭示了不同来源间的冲突建议以及领域间可迁移的原则。我们的方案并非旨在取代基于约束的工具，而是提供它们所缺乏的东西：一种情境化的指导。生成式系统可以检索这种指导来为其推理提供依据，用户可以对照引用的来源进行验证，专家也可以在知识演进过程中进行编写。