数据可视化如何支持跨学科研究? 卢克斯时代:在贝尔瓦尔 (Belval) 学习历史经济学
Dagny Aurich1, Aida Horaniet Ibañez2
1Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Frontiers in big data
|October 16, 2023
概括
卢森堡时间机器 (LuxTIME) 项目使用多种数据源和先进的数据可视化研究了Minnett地区的历史暴露. 这种方法为跨学科的历史暴露研究创造了一个灵活的工具箱.
科学领域:
- 环境健康科学 环境健康科学
- 历史研究 历史研究
- 数据科学数据科学数据科学
背景情况:
- 历史暴露组,包括环境和生活方式因素,显著影响人口健康.
- 卢森堡Minnett地区的工业化为研究历史暴露影响提供了一个独特的案例.
- 跨学科的方法对于理解复杂的历史健康决定因素至关重要.
研究的目的:
- 调查工业化时期在卢森堡的米内特地区的历史暴露.
- 开发和测试历史暴露组研究的多层次研究设计.
- 探索数据可视化的实用性,作为跨学科研究中的核心工具.
主要方法:
- 从国家和地方档案,图书馆和数字资源中收集了多样化的定量和定性数据.
- 采用数据可视化作为收集数据和元数据的主要导航和探索工具.
- 用一种投机式,以过程为导向的方法 ("沙堡") 来推进知识.
主要成果:
- 成功创建了一个多层次的历史暴露组研究设计的概念验证.
- 数据可视化促进了知识映射,范围定义和对研究过程的反思.
- 确定并记录了各种适合跨学科项目的数据可视化技术.
结论:
- 卢森堡时间机器项目展示了使用集成数据和可视化研究历史暴露物的可行性.
- 数据可视化是加强跨学科合作和知识发现的关键工具.
- 开发的"数据可视化工具箱"为未来的历史暴露组研究提供了可转移的框架.
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