漫长而曲折的道路:世卫组织数据共享的文化变革

Exposome Pub Date : 2024-04-13 DOI:10.1093/exposome/osae004
Robert O Wright, Konstantinos C Makris, P. Natsiavas, Timothy Fennel, Blake R Rushing, Ander Wilson
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引用次数: 0

摘要

数据共享需要数据生成者(如流行病学家、实验室研究人员)和数据使用者(如流行病学家、生物统计学家、计算机科学家)的合作。人类暴露组研究中的数据生成和数据使用需要大量不同的技能组合,而且在许多情况下时间上是分离的。要实现共享,就必须保留数据生成的历史记录,并建立一个系统来解决数据生成者对开展严谨工作所获得的荣誉(如作者身份)的担忧。共享还需要满足数据用户的需求,以促进数据的统一、可搜索性和质量保证/质量控制。我们从数据生成者和数据使用者的角度来阐述这些问题,并包括真实世界数据(如电子健康记录)的特殊情况。最后,我们就如何通过作者身份、成本回收和解决伦理问题更好地促进暴露组学中的数据共享提出了建议。
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A long and winding road: Culture change on data sharing in exposomics
Data sharing requires cooperation from data generators (e.g., epidemiologists, lab investigators) and data users (e.g., epidemiologists, biostatisticians, computer scientists). Data generation and data use in human exposome studies require significant but different skill sets and are separated temporally in many cases. Sharing will require maintaining a history of data generation and a system to address the concerns of data generators around credit for conducting rigorous work (e.g., authorship). Sharing also requires addressing the needs of data users to facilitate harmonization, searchability and QA/QC of data. We present these issues from the perspectives of data generators and data users and include the special case of real-world data (e.g., electronic health records). We conclude with recommendations to address how to better promote data sharing in exposomics through authorship, cost recovery and addressing ethical issues.
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Exposomics: perfection not required. A long and winding road: Culture change on data sharing in exposomics Interactive data sharing for multiple questionnaire-based exposome-wide association studies and exposome correlations in the Personalized Environment and Genes Study. Questionnaire-based exposome-wide association studies for common diseases in the Personalized Environment and Genes Study. Decoding the exposome: Data science methodologies and implications in Exposome-Wide association studies (ExWASs)
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