从仪表板动物园到人口普查:使用图表公众的案例研究
IEEE transactions on visualization and computer graphics
|November 6, 2024
概括
本研究介绍了一种基于图形的方法,用于系统地分析仪表板设计,揭示普遍的模式. 这种方法有助于开发更好的创作工具,并利用人工智能 (AI) 和机器学习 (ML) 来进行数据可视化.
科学领域:
- 数据可视化 数据可视化
- 人与计算机的交互
- 软件工程 软件工程 软件工程
背景情况:
- 仪表板对于数据分析和传播至关重要,但缺乏对其设计模式的系统理解.
- 分析仪表板设计的现有方法在范围和量化方面是有限的.
- 机器学习 (ML) 启发的方法通常集中在单个可视化或狭窄的设计特征上.
研究的目的:
- 开发一种可量化的系统方法来建模仪表板的内容和构成.
- 提供流行仪表板设计模式的描述性概述.
- 支持开发先进的仪表板创作工具和AI/ML应用程序.
主要方法:
- 开发了一个图形表示来建模仪表板设计,将其分解为内容块 (节点) 和关系 (边缘).
- 这种图形表示被应用到Tableau Public.25620个仪表板的普查中.
- 该方法超出了先前的工作范围,通过捕捉内容和构成.
主要成果:
- 获得了25620个仪表板的全面普查,详细介绍了核心构建块和普遍的设计模式.
- 该研究提供了"在野外"仪表板设计的描述性概述.
- 这些发现突出了常见和不太常见的仪表板设计模式.
结论:
- 拟议的图形表示为系统分析仪表板设计提供了一个强大的方法.
- 由此产生的普查和方法可以指导开发直观的仪表板创作工具.
- 这项工作有助于使仪表板更容易访问,并使先进的AI/ML技术用于数据可视化.
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