GO-Plan: A goal-oriented method for FAIRification planning

The FAIR principles provide guidance on improving the Findability, Accessibility, Interoperability, and Reusability of digital resources. Since the publication of the principles, several workflows have been proposed to support the process of making data FAIR (FAIRification). However, to respect the uniqueness of different communities, both the principles and the available workflows have been deliberately designed to remain agnostic in terms of standards, tools, and implementation choices. Consequently, FAIRification needs to be properly planned, and implementation details must be discussed with stakeholders and aligned with FAIRification objectives. To support this need, this paper describes GO-Plan, a method for identifying and refining FAIRification objectives. Leveraging on best practices from requirements and ontology engineering, the method aims at incrementally elaborating the most obvious aspects of the domain (e.g. the initial set of elements to be collected) into complex and comprehensive objectives. The definition of clear objectives enables stakeholders to communicate effectively and make informed implementation decisions, such as defining achievement criteria for distinct principles and identifying relevant metadata to be collected. GO-Plan has been validated in multiple discussion sessions with experts on FAIR, in an application to a real use case and in two hands-on tutorials with end-users.

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Publication Details

Journal
Information Services & Use
Published
2025-03-14
DOI
https://doi.org/10.1177/18758789251324008
Citations
2
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
6.49

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article

GO-Plan: A goal-oriented method for FAIRification planning

Marco Roos, Tiago Prince Sales, Niek van Ulzen, Ikerne del Valle et al.
2 citations
Information Services & Use
Research Data Management Practices
6.49
article

GO-Plan: A goal-oriented method for FAIRification planning

Marco Roos, Tiago Prince Sales, Niek van Ulzen, Ikerne del Valle, Erik Schultes, Annika Jacobsen, Vítor E. Silva Souza, Luiz Olavo Bonino da Silva Santos, Barend Mons, César H. Bernabé
article en
2 citations

Abstract

The FAIR principles provide guidance on improving the Findability, Accessibility, Interoperability, and Reusability of digital resources. Since the publication of the principles, several workflows have been proposed to support the process of making data FAIR (FAIRification). However, to respect the uniqueness of different communities, both the principles and the available workflows have been deliberately designed to remain agnostic in terms of standards, tools, and implementation choices. Consequently, FAIRification needs to be properly planned, and implementation details must be discussed with stakeholders and aligned with FAIRification objectives. To support this need, this paper describes GO-Plan, a method for identifying and refining FAIRification objectives. Leveraging on best practices from requirements and ontology engineering, the method aims at incrementally elaborating the most obvious aspects of the domain (e.g. the initial set of elements to be collected) into complex and comprehensive objectives. The definition of clear objectives enables stakeholders to communicate effectively and make informed implementation decisions, such as defining achievement criteria for distinct principles and identifying relevant metadata to be collected. GO-Plan has been validated in multiple discussion sessions with experts on FAIR, in an application to a real use case and in two hands-on tutorials with end-users.

Information Services & UseVol. 45(1-2)
Rhode Island Department of Health (US), Leiden University Medical Center (NL), Centre for Human Drug Research (NL), GO FAIR Foundation, Universidade Federal do Espírito Santo (BR), University of Twente (NL)
Innovative Health Initiative, Fundação de Amparo à Pesquisa e Inovação do Espírito Santo, Horizon 2020 Framework Programme
Openalex Percentile: Top 5%
Research Data Management Practices
6.49
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