Implementation of the FAIR Data Principles for Exploratory Biomarker Data from Clinical Trials
Implementation of the FAIR Data Principles for Exploratory Biomarker Data from Clinical Trials
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DOI：
10.1162/dint_a_00106
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发表时间：
2021-10-25
影响因子：
3.9
通讯作者：
McCreary, Mark
中科院分区：
文献类型：
--
作者：
Arefolov, Alexander;Adam, Laura;McCreary, Mark
FAIR数据指导原则最近被开发并被广泛采用，以提高数字资产的可查找性、可访问性、互操作性和重用性，以应对数据量和复杂性的指数增长。FAIR数据原则是在一般层面上制定的，这些原则的技术实施仍然取决于致力于最大化其数据价值的行业和组织。在这里，我们描述了数据管理和管理方法和最佳实践开发的临床探索性生物标志物数据标准化从250多个临床研究收集。我们将讨论所涉及的数据管理工作、结果输出以及我们工作的商业和科学影响。最后，我们提出了FAIR数据的前瞻性规划，以优化数据管理工作并最大化数据价值。
The FAIR data guiding principles have been recently developed and widely adopted to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets in the face of an exponential increase of data volume and complexity. The FAIR data principles have been formulated on a general level and the technological implementation of these principles remains up to the industries and organizations working on maximizing the value of their data. Here, we describe the data management and curation methodologies and best practices developed for FAIRification of clinical exploratory biomarker data collected from over 250 clinical studies. We discuss the data curation effort involved, the resulting output, and the business and scientific impact of our work. Finally, we propose prospective planning for FAIR data to optimize data management efforts and maximize data value.