利用大数据进行实验报告:高驱动协作研究项目案例
Alessio Capello1, Matteo Fresta1, Francesco Bellotti1
1Department of Electrical, Electronic and Telecommunication Engineering (DITEN), University of Genoa, Via Opera Pia 11A, 16145 Genoa, Italy.
Sensors (Basel, Switzerland)
|September 28, 2023
概括
我们开发了一个数据工具链,通过简化报告工具的设置来实现项目进展监控的自动化. 该系统有效地从实验数据中提取关键绩效指标,提高项目管理效率.
科学领域:
- 数据科学数据科学数据科学
- 软件工程 软件工程 软件工程
- 项目管理 项目管理
背景情况:
- 及时的项目状态信息对于有效的管理至关重要.
- 现有的框架可能需要进行广泛的定制以监测进展.
- 自动数据提取对于处理大量项目数据至关重要.
研究的目的:
- 开发一个数据工具链,用于自动化项目进展监测.
- 通过配置文件简化报告工具的设置.
- 确保从实验数据中自动提取项目绩效指标.
主要方法:
- 扩展了Measurify框架,用于在MongoDB上构建丰富的测量应用程序.
- 使用JSON配置文件来定义项目进展/绩效指标.
- 专注于从项目实验数据文件中自动提取数据.
主要成果:
- 成功开发了一个数据工具链,支持自动化项目进度监测.
- 工具链通过可编辑的JSON配置文件简化了报告工具的设置.
- 在一个协作研究项目中证明了有效性,确定了330多个数值指标.
结论:
- 开发的数据工具链对于使用实际项目数据编制定期进展报告是有效的.
- 设计选择,包括API资源定义,确保在汽车行业之外的广泛应用.
- 该工具链通过提供及时和数据丰富的项目状态洞察力来增强项目管理.
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