Enhancing Reproducibility in Research Through FAIR Digital Objects

Zeyd Boukhers, Leyla Jael Castro
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Abstract

The FAIR principles were introduced to enhance data reuse by providing guidelines for effective data management practices. In the broader context of research, assets encompass not only data but also artifacts such as code, software, and publications. FAIRifying these artifacts is as essential as FAIRifying data, given the increasing complexity of current AI approaches that make reproducibility extremely challenging. Therefore, the reuse of these artifacts is growing in importance. The concept of FAIR Digital Objects (FDOs) presents a solution to FAIRify these artifacts, treating them as FDOs. NFDI4DataScience is embracing FDOs and proposing an architecture to efficiently manage them.
通过FAIR数字对象提高研究的可重复性
引入FAIR原则是为了通过为有效的数据管理实践提供指导方针来增强数据重用。在更广泛的研究背景下,资产不仅包括数据,还包括代码、软件和出版物等工件。鉴于当前人工智能方法日益复杂,使得可重复性极具挑战性,对这些工件进行公平化与对数据进行公平化一样重要。因此,这些工件的重用变得越来越重要。公平数字对象(FAIR Digital Objects, fdo)的概念提出了一种公平处理这些工件的解决方案,将它们视为fdo。NFDI4DataScience正在拥抱fdo,并提出了一种架构来有效地管理它们。
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