AI 中文总结
本文借助设计理论绘制数据可视化的设计知识图景，指出该领域在部分知识领域优势显著、部分阐释不足，提出可视化设计依赖知识制品与在用知识，主张计算系统可支持部分设计认知，而非将设计视为完全可形式化或抗拒计算支持的对象。
AI 中文摘要
数据可视化研究已发展出诸多有影响力的设计知识形式，包括感知原则、设计指南、过程模型以及设计约束的形式化表示。这些成果能有效阐明显性、可迁移且可编码的知识形式。然而，可视化设计所依赖的更广阔图景仍未得到清晰阐释，尤其在中级知识、先例、隐性知识库以及情境化认知形式方面。本文借助设计理论绘制数据可视化中设计知识的更广阔图景。通过这一视角，我们展示了可视化研究在部分领域已构建显著优势，而其他领域则相对阐释不足。我们进一步提出，可视化设计不仅依赖理论、指南、模式等知识制品，还依赖“在用知识”——即具体设计情境中对多种认知形式的情境化解读、适配与协调。这一更宽泛的阐释对该领域如何概念化设计专长、评估与开发学术贡献，以及处理AI辅助设计具有重要意义。我们主张采用差异化视角，而非将可视化设计视为完全可形式化或完全抗拒计算支持的对象，即计算系统可支持部分设计认知形式，而其他形式则与人类判断、情境解读及实践中设计工作的持续重组不可分割。
英文摘要
Data visualization research has developed many influential forms of design knowledge, including perceptual principles, design guidelines, process models, and formalized representations of design constraints. These contributions have been effective at articulating explicit, portable, and codified forms of knowledge. Yet the broader landscape on which visualization design depends remains less clearly articulated, especially with respect to intermediate-level knowledge, precedents, tacit repertoires, and situated forms of knowing. In this paper, we draw on design theory to map this broader landscape of design knowledge in data visualization. Through this lens, we show how visualization research has built substantial strengths in some regions while leaving others comparatively underarticulated. We further argue that visualization design depends not only on knowledge artifacts such as theories, guidelines, and patterns, but also on knowledge-in-use---the situated interpretation, adaptation, and coordination of multiple forms of knowing in concrete design situations. This broader account has implications for how the field conceptualizes design expertise, evaluates and develops scholarly contributions, and approaches AI-assisted design. Rather than treating visualization design as either fully formalizable or wholly resistant to computational support, we argue for a differentiated view in which computational systems can support some forms of design knowing, while others remain inseparable from human judgment, contextual interpretation, and the ongoing reorganization of design work in practice.
CommentsTo be presented at IEEE VIS 2026 and published in IEEE TVCG in 2027
