冰山感知制造:一种用于关键数据分析的过程模型
IEEE transactions on visualization and computer graphics
|November 4, 2024
概括
这项研究引入了一种新的解释主义模型,用于数据感知,通过图表查看数据分析. 它提供了一个三阶段的过程,以更好地理解和完善数据洞察力.
科学领域:
- 数据科学数据科学数据科学
- 信息科学 信息科学 信息科学
- 人与计算机的交互
背景情况:
- 现有的数据感知模型通常依赖于积极主义假设.
- 对于更细致的数据分析理解,需要一个批判性的,人文的视角.
- 解释主义为重新构建数据提供了一个有价值的镜头.
研究的目的:
- 为数据感知过程提出一种新的解释主义模型.
- 将数据分析和可视化从一个批判性的,人文化的角度重新定义.
- 为了解分析师如何理解数据提供一个结构化,三阶段模型.
主要方法:
- 使用冰山类比,开发了一个三相过程模型 (添加,检查,精炼).
- 在整个意义制造过程中纳入了默契和明确方案的概念.
- 通过四种不同的数据分析场景验证了模型.
主要成果:
- 拟议的模型强调图表是数据解释的基础,将数据视为图表文物.
- 它强调了默认知识,权力动态和图形多样性在意义形成中的重要性.
- 该模型有效地解决了诸如识别缺失数据,数据纠纷和处理不方便数据等场景.
结论:
- 解释主义的方法培养了认识的谦卑,并促进了数据意义上的多元主义.
- 新模型为理解数据分析的复杂性提供了一个更全面的框架.
- 这种方法增强了感知模型的描述和规范能力.
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