Despite decision-making being a vital goal of data visualization, little work has been done to differentiate the decision-making tasks within our field. While visualization task taxonomies and typologies exist, they are often too granular for describing complex decision goals and decision-making processes, thus limiting their potential use in designing decision-support tools. In this paper, we contribute a typology of decision-making tasks that were iteratively refined from a list of design goals distilled from a literature review. Our typology is concise and consists of only three tasks: choose, activate, and create. Originally proposed by the scientific community, we extend and provide definitions for these tasks that are suitable for the visualization community. Our proposed typology offers two benefits. First, it facilitates the composition of decisions using these three tasks, allowing for flexible and clear descriptions across varying complexities and domains. Second, diagrams created using this typology encourage productive discourse between visualization designers and domain experts by abstracting the intricacies of data, thereby promoting clarity and rigorous analysis of decision-making processes. We motivate the use of our typology through four case studies and demonstrate the benefits of our approach through semi-structured interviews conducted with experienced members of the visualization community, comprising academic and industry experts, who have contributed to developing or publishing decision support systems for domain experts. Our interviewees composed diagrams using our typology to delineate the decision-making processes that drive their decision-support tools, demonstrating its descriptive capacity and effectiveness.

翻译：尽管决策是数据可视化的重要目标，但针对该领域内决策任务的差异化研究仍较为匮乏。现有可视化任务分类体系虽已存在，但其粒度往往过于细化，难以描述复杂的决策目标与决策过程，从而限制了它们在设计决策支持工具中的潜在应用。本文提出了一种决策任务类型学，该分类体系基于文献综述中凝练的设计目标清单，经过迭代完善而成。该类型学简洁精炼，仅包含选择、激活与创建三项任务。我们借鉴科学界的原始定义，对其进行扩展并赋予适用于可视化领域的阐释。本文提出的类型学具有双重优势：首先，它通过三项任务的组合描述决策构成，既能灵活适配不同复杂程度与应用领域，又能保证描述的清晰性；其次，利用该类型学构建的示意图能抽象数据复杂性，通过促进可视化设计者与领域专家之间的高效沟通，提升决策过程分析的清晰度与严谨性。我们通过四个案例研究论证该类型学的应用价值，并对可视化领域资深人士（包括参与开发或发布面向领域专家决策支持系统的学术界与工业界专家）进行半结构化访谈，验证其方法优势。受访者运用该类型学绘制示意图，清晰勾勒出驱动其决策支持工具的决策流程，充分彰显了该方法的描述能力与有效性。