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，但鲜有研究对本领域的决策任务进行区分。现有可视化任务分类法与类型学虽已存在，但在描述复杂决策目标与决策过程时往往过于细粒度，从而限制了其在设计决策支持工具中的潜在应用。本文提出一种决策任务类型学，该类型学通过文献综述归纳的设计目标列表反复提炼而成。该类型学简洁凝练，仅包含选择（choose）、激活（activate）与创建（create）三类任务。我们借鉴科学界的原始概念，对其进行扩展并给出适用于可视化领域的定义。本类型学具有两大优势：其一，通过这三类任务组合决策过程，可灵活清晰地描述不同复杂程度与领域的决策需求；其二，基于该类型学绘制的示意图通过抽象数据复杂性，促进可视化设计者与领域专家之间的高效对话，从而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验证该类型学的实用性，并对具有决策支持系统开发或发表经验的资深可视化领域从业者（包括学术界与工业界专家）开展半结构化访谈，证明其优势。受访者使用本类型学绘制示意图，清晰勾勒出其决策支持工具所驱动的决策过程，充分展示了该类型学的描述能力与有效性。