可视化决策任务的类型学。

IF 6.5
Camelia D Brumar, Sam Molnar, Gabriel Appleby, Kristi Potter, Remco Chang
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引用次数: 0

摘要

尽管决策是数据可视化的一个重要目标,但在该领域内区分决策任务的工作很少。虽然存在可视化任务分类法和类型学,但它们通常侧重于更细粒度的分析任务,这些任务级别太低,无法描述大型复杂决策,这可能会使推理和设计决策支持工具变得困难。在本文中,我们提供了一种决策任务的类型,这些任务是从文献综述中提取的设计目标列表中迭代改进而来的。我们的类型学很简洁,只有三个任务:选择、激活和创建。尽管存在源自其他学科的决策类型,但我们为这些任务提供了适合可视化社区的定义。我们提出的类型学有两个好处。首先,组合和分层组织任务的能力使具有不同复杂程度的决策的灵活和清晰的描述成为可能。其次,类型学通过抽象复杂的数据,鼓励可视化设计师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和严格分析。我们通过四个案例研究展示了我们的类型学的好处,并通过对可视化社区有经验的成员的半结构化访谈对类型学进行了评估,这些成员为领域专家开发或发布决策支持系统做出了贡献。我们的受访者使用我们的类型学来描述由他们的系统支持的决策过程,展示其描述能力和有效性。最后,我们提出了我们的类型学对可视化设计有用性的初步发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Typology of Decision-Making Tasks for Visualization.

Despite decision-making being a vital goal of data visualization, little work has been done to differentiate decision-making tasks within the field. While visualization task taxonomies and typologies exist, they often focus on more granular analytical tasks that are too low-level to describe large complex decisions, which can make it difficult to reason about and design 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. Although decision types originating in other disciplines exist, we provide definitions for these tasks that are suitable for the visualization community. Our proposed typology offers two benefits. First, the ability to compose and hierarchically organize the tasks enables flexible and clear descriptions of decisions with varying levels of complexities. Second, the typology encourages 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 demonstrate the benefits of our typology through four case studies, and present an evaluation of the typology from semi-structured interviews with experienced members of the visualization community who have contributed to developing or publishing decision support systems for domain experts. Our interviewees used our typology to delineate the decision-making processes supported by their systems, demonstrating its descriptive capacity and effectiveness. Finally, we present preliminary findings on the usefulness of our typology for visualization design.

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