In the face of complex decisions, people often engage in a three-stage process that spans from (1) exploring and analyzing pertinent information (intelligence); (2) generating and exploring alternative options (design); and ultimately culminating in (3) selecting the optimal decision by evaluating discerning criteria (choice). We can fairly assume that all good visualizations aid in the intelligence stage by enabling data exploration and analysis. Yet, to what degree and how do visualization systems currently support the other decision making stages, namely design and choice? To explore this question, we conducted a comprehensive review of decision-focused visualization tools by examining publications in major visualization journals and conferences, including VIS, EuroVis, and CHI, spanning all available years. We employed a deductive coding method and in-depth analysis to assess if and how visualization tools support design and choice. Specifically, we examined each visualization tool by (i) its degree of visibility for displaying decision alternatives, criteria, and preferences, and (ii) its degree of flexibility for offering means to manipulate the decision alternatives, criteria, and preferences with interactions such as adding, modifying, changing mapping, and filtering. Our review highlights the opportunities and challenges and reveals a surprising scarcity of tools that support all stages, and while most tools excel in offering visibility for decision criteria and alternatives, the degree of flexibility to manipulate these elements is often limited, and the lack of tools that accommodate decision preferences and their elicitation is notable. Future research could explore enhancing flexibility levels and variety, exploring novel visualization paradigms, increasing algorithmic support, and ensuring that this automation is user-controlled via the enhanced flexibility levels.

翻译：面对复杂决策，人们通常经历三个阶段：（1）探索与分析相关信息（情报）；（2）生成并探索备选方案（设计）；（3）通过评估判别标准选择最优决策（选择）。我们可以合理假设，所有优秀的数据可视化都能通过支持数据探索与分析来辅助情报阶段。然而，可视化系统在何种程度上以及如何支持其他决策阶段（即设计和选择）？为探讨此问题，我们对主要可视化期刊与会议（包括VIS、EuroVis和CHI）历年发表的以决策为核心的可视化工具进行了系统性综述。采用演绎编码法与深度分析，评估可视化工具是否以及如何支持设计与选择。具体而言，我们从以下两个维度对每个工具进行分析：（1）显示决策备选方案、标准与偏好的可见性程度；（2）通过交互操作（如添加、修改、映射变更与过滤）操控决策备选方案、标准与偏好的灵活性程度。综述揭示了机遇与挑战：支持全阶段的可视化工具异常稀缺；尽管多数工具在展示决策标准与备选方案方面表现优异，但操控这些元素的灵活性普遍有限；而能够适应决策偏好及其引导的工具有显著缺失。未来研究可探索提升灵活性水平与多样性、开发新型可视化范式、增强算法支持，并通过增强的灵活性确保用户对自动化过程的控制。