论文标题
元数据在可复制计算研究中的作用
The role of metadata in reproducible computational research
论文作者
论文摘要
可再现的计算研究（RCR）是用于计算机分析的科学方法的基石，将原始数据转换为已发表的结果。除了其在研究完整性中的作用外，RCR还具有显着加速评估和重用的能力。公平原则的这种潜在和广泛的支持激发了对支持RCR的元数据标准的兴趣。元数据为原始数据和方法提供了上下文和出处，对于发现和验证都是必不可少的。尽管与科学数据有着共同的联系，但很少有研究明确描述了元数据和RCR之间的关系。本文采用功能内容分析来识别支持RCR功能的元数据标准，该标准由输入数据，工具，笔记本，管道和出版物组成。我们的文章提供了背景上下文，探索差距，并发现了嵌入性和方法论的组成趋势，我们从中为将来的工作提出了建议。
Reproducible computational research (RCR) is the keystone of the scientific method for in silico analyses, packaging the transformation of raw data to published results. In addition to its role in research integrity, RCR has the capacity to significantly accelerate evaluation and reuse. This potential and wide-support for the FAIR principles have motivated interest in metadata standards supporting RCR. Metadata provides context and provenance to raw data and methods and is essential to both discovery and validation. Despite this shared connection with scientific data, few studies have explicitly described the relationship between metadata and RCR. This article employs a functional content analysis to identify metadata standards that support RCR functions across an analytic stack consisting of input data, tools, notebooks, pipelines, and publications. Our article provides background context, explores gaps, and discovers component trends of embeddedness and methodology weight from which we derive recommendations for future work.
