赋予社区权力:为各种任务和用户量身定制的流行病数据可视化
IEEE computer graphics and applications
|April 14, 2025
概括
在COVID-19大流行期间,数据可视化至关重要. 本综述详细介绍了设计经验,挑战和跨学科项目的教训,以告知未来的流行病反应.
科学领域:
- 公共卫生信息学 公共卫生信息学
- 数据科学数据科学数据科学
- 人与计算机的交互
背景情况:
- 由于COVID-19的流行,需要快速的数据分析和沟通.
- 有效的数据可视化成为了解和应对疫情的关键工具.
研究的目的:
- 审查跨学科COVID-19数据可视化项目的设计经验和挑战.
- 描述用户社区,任务和遇到的数据类型.
- 为未来的流行病准备提取经验教训.
主要方法:
- 从多个跨学科COVID-19项目的设计经验的审查.
- 用户社区,目标,任务,数据类型和视觉媒体的表征.
- 案例研究的介绍,以说明发现.
- 分析视觉分析所学到的经验教训.
主要成果:
- 识别了流行病数据可视化中的各种用户需求和挑战.
- 记录了各种数据类型和使用的视觉媒体.
- 详细的具体项目案例研究及其结果.
- 综合了通过数据可视化改善未来的流行病应对措施的关键经验教训.
结论:
- 有效的数据可视化设计需要了解用户社区和特定任务.
- 跨学科的合作对于成功的流行病数据可视化至关重要.
- 学到的经验教训可以指导开发更强大的和响应的可视化工具,以应对未来的健康危机.
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