图书情报工作 ›› 2021, Vol. 65 ›› Issue (16): 138-147.DOI: 10.13266/j.issn.0252-3116.2021.16.015

• 综述述评 • 上一篇    下一篇

FAIR数据评估模型与工具研究

叶兰   

  1. 深圳大学图书馆 深圳 518060
  • 收稿日期:2020-12-29 修回日期:2021-03-18 出版日期:2021-08-20 发布日期:2021-08-20
  • 作者简介:叶兰(ORCID:0000-0002-3079-5399),副研究馆员,硕士,E-mail:yel@szu.edu.cn。
  • 基金资助:
    本文系教育部人文社会科学研究青年基金项目"基于成熟度视角的高校图书馆科学数据管理服务能力评价研究"(项目编号:19YJC870028)研究成果之一。

Research on FAIR Data Assessment Models and Tools

Ye Lan   

  1. Shenzhen University Library, Shenzhen 518060
  • Received:2020-12-29 Revised:2021-03-18 Online:2021-08-20 Published:2021-08-20

摘要: [目的/意义] 对比分析FAIR数据评估模型与工具,为数据建设和数据管理过程中利益相关者评估FAIR数据的遵循度提供参考。[方法/过程] 通过文献综述及模型文本的研究,从评估指标和评估方法两方面介绍国际上7个评估FAIR数据遵循度的指标模型与工具,采用比较分析法从评估方法的类型、评估方法的自动化程度、评估方法的可操作性、指标数量与分布、元数据指标设置、指标清晰度等6个方面对比分析各模型与工具。[结果/结论] 基于对比与评析结果,为选择与应用FAIR数据评估模型与工具提出"FAIRsFAIR数据对象评估+FAIR数据成熟度模型"的方案。

关键词: FAIR评估, FAIR遵循度, FAIR成熟度, FAIR指标, 数据FAIR化, FAIR原则

Abstract: [Purpose/significance] This paper compares the main FAIR assessment models and tools in order to provide references for stakeholders in data management to assess data FAIRness.[Method/process] The metrics and the evaluation methods of each model or tool were introduced through a literature review and content analysis. The comparative analysis method was also used to evaluate FAIR assessment models and tools from 6 aspects, including types, automation, operability of FAIRness evaluation method, number and distribution of indicators, metadata indicator settings, and indicator clarity.[Result/conclusion] Based on the comparison of each model or tool, a solution of "FAIRsFAIR Data Object Assessment Metrics + RDA FAIR Data Maturity Model" is proposed for stakeholdersin data management in selecting and application of FAIR assessment models.

Key words: FAIR assessments, dataFAIRness, FAIR maturity, FAIR metrics, data FAIRification, FAIR principles

中图分类号: