A Generic Workflow for the Data FAIRification Process
A Generic Workflow for the Data FAIRification Process
Mons, Barend Roos, Marco Jacobsen, Annika Schultes, Erik Kaliyaperumal, Rajaram Thompson, Mark Santos, Luiz Olavo Bonino da Silva
作者信息
摘要
The FAIR guiding principles aim to enhance the Findability, Accessibility, Interoperability and Reusability of digital resources such as data, for both humans and machines. The process of making data FAIR (“FAIRification”) can be described in multiple steps. In this paper, we describe a generic step-by-step FAIRification workflow to be performed in a multidisciplinary team guided by FAIR data stewards. The FAIRification workflow should be applicable to any type of data and has been developed and used for “Bring Your Own Data” (BYOD) workshops, as well as for the FAIRification of e.g., rare diseases resources. The steps are: 1) identify the FAIRification objective, 2) analyze data, 3) analyze metadata, 4) define semantic model for data (4a) and metadata (4b), 5) make data (5a) and metadata (5b) linkable, 6) host FAIR data, and 7) assess FAIR data. For each step we describe how the data are processed, what expertise is required, which procedures and tools can be used, and which FAIR principles they relate to.Abstract
The FAIR guiding principles aim to enhance the Findability, Accessibility, Interoperability and Reusability of digital resources such as data, for both humans and machines. The process of making data FAIR (“FAIRification”) can be described in multiple steps. In this paper, we describe a generic step-by-step FAIRification workflow to be performed in a multidisciplinary team guided by FAIR data stewards. The FAIRification workflow should be applicable to any type of data and has been developed and used for “Bring Your Own Data” (BYOD) workshops, as well as for the FAIRification of e.g., rare diseases resources. The steps are: 1) identify the FAIRification objective, 2) analyze data, 3) analyze metadata, 4) define semantic model for data (4a) and metadata (4b), 5) make data (5a) and metadata (5b) linkable, 6) host FAIR data, and 7) assess FAIR data. For each step we describe how the data are processed, what expertise is required, which procedures and tools can be used, and which FAIR principles they relate to. 关键词
FAIR data/FAIRification workflow/FAIR data stewardship/Hands-on FAIRification/FAIR dissemination引用本文复制引用
Mons, Barend,Roos, Marco,Jacobsen, Annika,Schultes, Erik,Kaliyaperumal, Rajaram,Thompson, Mark,Santos, Luiz Olavo Bonino da Silva.A Generic Workflow for the Data FAIRification Process[EB/OL].(2022-11-16)[2025-12-13].https://chinaxiv.org/abs/202211.00191.学科分类
信息科学、信息技术/自然科学研究方法
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