Are the FAIR Data Principles fair?
Are the FAIR Data Principles fair?
复制标题
FAIR 数据原则公平吗？
DOI：
--
复制
发表时间：
2017
影响因子：
--
通讯作者：
Jasmin Böhmer
中科院分区：
文献类型：
--
作者：
A. Dunning;Madeleine de Smaele;Jasmin Böhmer
这篇实践论文描述了一个正在进行的研究项目，以测试公平数据原则的有效性和相关性。同时，它将分析数据档案遵守这些原则的容易程度。该研究于2016年11月至2017年1月进行，并将以存储库的反馈为基础。FAIR数据原则有15个方面，对应于FAIR的四个字母-可查找，可扩展，可互操作，可重用。这些原则已经在研究界获得了广泛的关注。欧盟委员会最近扩大了对研究的需求，以产生开放数据。相关的指导原则1是在公平数据原则的背景下明确编写的。鉴于越来越多的研究人员将接触到这些准则，了解其可行性并提出修改和调整的空间至关重要。这篇实践论文与数据集（Dunning等人，2017），包含Excel电子表格中样本组统计数据和图表的原始概述。在两个月的时间里，对40多个数据储存库的网络界面、帮助页面和元数据记录进行了检查，以便根据公平信息检索原则和方面对各个数据储存库进行评分。交通灯评级系统可根据合规性和准确性进行颜色编码。统计分析提供了总体的、分类的、关于原则聚焦的和关于方面聚焦的结果。分析包括统计和描述性评价，其次是阐述公平数据原则的要素，特定于主题或存储库的差异，以及存储库可以做些什么来改进其信息架构。
This practice paper describes an ongoing research project to test the effectiveness and relevance of the FAIR Data Principles. Simultaneously, it will analyse how easy it is for data archives to adhere to the principles. The research took place from November 2016 to January 2017, and will be underpinned with feedback from the repositories. The FAIR Data Principles feature 15 facets corresponding to the four letters of FAIR - Findable, Accessible, Interoperable, Reusable. These principles have already gained traction within the research world. The European Commission has recently expanded its demand for research to produce open data. The relevant guidelines1are explicitly written in the context of the FAIR Data Principles. Given an increasing number of researchers will have exposure to the guidelines, understanding their viability and suggesting where there may be room for modification and adjustment is of vital importance. This practice paper is connected to a dataset(Dunning et al.,2017) containing the original overview of the sample group statistics and graphs, in an Excel spreadsheet. Over the course of two months, the web-interfaces, help-pages and metadata-records of over 40 data repositories have been examined, to score the individual data repository against the FAIR principles and facets. The traffic-light rating system enables colour-coding according to compliance and vagueness. The statistical analysis provides overall, categorised, on the principles focussing, and on the facet focussing results. The analysis includes the statistical and descriptive evaluation, followed by elaborations on Elements of the FAIR Data Principles, the subject specific or repository specific differences, and subsequently what repositories can do to improve their information architecture.