结合数据集成和视觉数据分析的初步指南
IEEE transactions on visualization and computer graphics
|November 20, 2023
概括
在视觉分析过程中整合数据,无论是手动 (ex-situ) 还是自动 (in-situ),都显示了类似的任务完成时间. 然而,现场集成允许更多的时间用于实际分析和假设跟踪.
科学领域:
- 信息可视化 信息可视化
- 人与计算机的交互
- 数据科学数据科学数据科学
背景情况:
- 在视觉数据分析中,数据整合对于整合不同的数据源至关重要.
- 当前的实践往往将数据集成与核心视觉分析操作 (例如编码,过) 分开.
- 这种分离可能会阻碍分析工作流和洞察力生成.
研究的目的:
- 调查将数据集成直接集成到视觉分析过程中的影响.
- 为了比较手动,现场集成和自动,现场集成之间的用户性能和行为.
- 为未来的视觉分析接口推导设计准则.
主要方法:
- 一项初步的用户研究比较了两个接口替代方案:手动基于文件的现场集成和基于UI的自动现场集成.
- 参与者完成了特定和自由形式的任务,包括模式发现,洞察力生成和跨多个文件的关系总结.
- 分析交互数据和用户反,以评估任务完成,花费时间和整合策略.
主要成果:
- 在ex-situ和in-situ整合接口中,任务完成时间和总交互是可比的.
- 与现场集成相比,现场集成允许用户在分析任务上花费更多时间.
- 不同的整合策略和分析行为出现,受界面的影响,影响假设生成和跟踪.
结论:
- 虽然总体任务效率可能相似,但现场数据集成支持更深入地参与分析.
- 接口设计显著影响用户对假设管理和洞察力开发的策略.
- 初步指南建议在增强的视觉分析系统的积极分析过程中无地整合属性集成.
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