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.

中文翻译：

---

可视化决策任务的类型学

尽管决策是数据可视化的一个重要目标，但在我们领域内区分决策任务的工作却很少。虽然存在可视化任务分类法和类型学，但它们通常过于细化，无法描述复杂的决策目标和决策过程，从而限制了它们在设计决策支持工具中的潜在用途。在本文中，我们贡献了一种决策任务的类型，这些任务是从文献综述中提炼出的设计目标列表中迭代提炼出来的。我们的类型很简洁，仅包含三个任务：选择、激活和创建。最初由科学界提出，我们扩展并提供了适合可视化界的这些任务的定义。我们提出的类型有两个好处。首先，它促进了使用这三个任务的决策组合，允许跨不同复杂性和领域进行灵活和清晰的描述。其次，使用这种类型创建的图表通过抽象复杂的数据来鼓励可视化设计者和领域专家之间富有成效的对话，从而促进决策过程的清晰度和严格分析。我们通过四个案例研究来激发我们的类型学的使用，并通过与可视化社区的经验丰富的成员（包括学术和行业专家）进行半结构化访谈来展示我们的方法的好处，他们为开发或发布领域的决策支持系统做出了贡献专家。我们的受访者使用我们的类型学绘制了图表来描述驱动其决策支持工具的决策过程，展示其描述能力和有效性。