AI 中文总结
该研究针对图表类型边界定义难题，以甘特图等为例区分图表类型的核心与可变特征，提出推理边界的词汇工具，明确此类研究的范围选择需公开。
AI 中文摘要
什么构成了甘特图？当我们着手构建甘特图的设计空间时，这个问题被证明出乎意料地难以回答。现有定义各自受其研究目标的影响，做出了我们无法直接调和的不同范围选择。我们对什么应该算作甘特图、什么不应该进行了推理，在此过程中开发了相关概念和工具。我们区分了图表类型身份所必需的特征与可变化的特征，并利用这些区分来绘制图表类型如何通过它们的共性和差异产生关联。将这些思路应用于甘特图、雷达图和表格 cartograms（表格 cartogram 是一种数据可视化技术，此处保留原名），我们得出了关于边界工作揭示内容的关键见解：定义因功能原因而产生分歧，划定边界会暴露描述性词汇中的隐藏结构，如特征纠缠，而范围选择决定了研究结果的可推广程度。我们认识到不存在确定的答案，但通过探究这个问题得出了一个功能性定义，该定义指导了我们最初着手构建的设计空间。此外，我们还提供了用于推理图表类型边界、揭示这些边界决策的词汇和工具，以及一个已记录的甘特图设计空间。我们更广泛的反思是，以图表类型为中心的研究中的范围选择——这些选择决定了设计空间包含什么、语法生成什么以及感知研究测量什么——是值得被明确呈现的研究决策。
英文摘要
What makes a Gantt chart? This question proved unexpectedly difficult to answer when we set out to build a design space for Gantt charts. Existing definitions, each shaped by their respective research goals, made different scope choices that we could not directly reconcile. We reasoned about what should and should not count as a Gantt chart, developing concepts and tools along the way. We distinguish features that are essential to a chart type's identity from those that can vary, and use these distinctions to map how chart types relate through what they share and lack. Applying these ideas to Gantt charts, radar charts, and table cartograms, we produce key insights on what boundary work reveals: definitions diverge for functional reasons, drawing boundaries exposes hidden structure in descriptive vocabulary such as feature entanglements, and scope choices shape how far findings can generalize. We came to understand that there is not a definitive answer, but that working through the question produced a functional definition that guided the design space we originally set out to build. Additionally, we present vocabulary and tools for reasoning about chart type boundaries and surfacing these boundary decisions, alongside a documented Gantt chart design space. Our broader reflection is that scope choices in chart-type-centered research---which determine what design spaces include, what grammars generate, and what perceptual studies measure---are research decisions worth making visible.
Comments11 pages, 7 figs. IEEE VIS 2026
