饮食摄入数据再利用质量评估框架的开发和评估:FNS-Cloud研究
Laura A Bardon1,2,3, Grace Bennett1,2,3, Michelle Weech4,5
1Food and Nutrition National Bioscience Research Infrastructure, Quadram Institute Bioscience, Norwich, United Kingdom.
Frontiers in nutrition
|June 23, 2025
概括
在FNS-Cloud项目中,开发了一个数据质量评估工具,以帮助研究人员评估饮食摄入数据集,以便重复使用. 该工具支持对数据适用于新研究目的的知情决策.
科学领域:
- 食品和营养科学 食品和营养科学
- 数据科学数据科学数据科学
- 医疗信息学 医疗信息学
背景情况:
- 食物,营养和健康数据的碎片化阻碍了有效的研究.
- 越来越多的数据重复使用需要保持科学严谨性和质量.
- 研究人员需要帮助确定现有数据集是否适合用于新分析.
研究的目的:
- 开发和评估FNS-Cloud数据质量评估工具,用于饮食摄入数据集.
- 为研究人员提供一个框架,以便在重复使用之前评估数据质量.
- 通过改进数据选择,提高科学分析的可靠性.
主要方法:
- 从文献中确定了数据收集,来源,管理和分析的质量标记.
- 开发了一个质量评估框架,包括决策树和反信息.
- 将框架转化为在线工具,并与13名参与者进行了用户评估研究.
主要成果:
- FNS-Cloud工具为研究人员提供了一份报告,以帮助他们做出再利用决策.
- 用户评估显示,对评估格式和反的评价是积极的.
- 参与者发现该工具对培训学生和缺乏经验的研究人员有用.
结论:
- FNS-Cloud数据质量评估工具是公开可访问的,以支持研究人员识别合适的数据集.
- 该工具有助于决定以前收集的数据集是否适合用于新的研究目的.
- 进一步完善该工具将提高其适用于更广泛的用户基础的可用性.
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