=Paper=
{{Paper
|id=Vol-3603/Poster1
|storemode=property
|title=A Method to Facilitate the Identification of FAIRification Objectives
|pdfUrl=https://ceur-ws.org/Vol-3603/Poster1.pdf
|volume=Vol-3603
|authors=César Bernabé,Annika Jacobsen,Luiz O. Bonino da S.S.,Marco Roos
|dblpUrl=https://dblp.org/rec/conf/icbo/BernabeJSR23
}}
==A Method to Facilitate the Identification of FAIRification Objectives==
https://ceur-ws.org/Vol-3603/Poster1.pdf
A method to facilitate the identification of FAIRification
objectives
César Bernabé 1, Annika Jacobsen 1, Luiz O. Bonino da S.S.1,2 and Marco Roos1
1
Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands
2
University of Twente, Address, Drienerlolaan 5, 7522 NB, Enschede, The Netherlands1
1. Introduction
The FAIR principles guide making resources accessible, interoperable, and reusable for humans and
machines. The process of making data FAIR (FAIRification) is multi-faceted and can be realised by
different means. Consequently, to achieve successful FAIRification, it is essential to define clear
objectives that will support establishing a cohesive and effective FAIRification process.
2. Results
We present GO-Plan [1], a method for identifying FAIRification objectives, drawing from
experience with recent FAIRification projects (e.g., FAIRification of rare disease data) and feedback
from FAIR experts. The method consists of six phases: (i) FAIRification preparation, (ii) assessment
of FAIR supporting infrastructure and target resources, (iii) preparation of project collaborators, (iv)
identification of domain scope and groups of reuse stakeholders, (v) FAIRification goals refinement
and alignment to target FAIR principles, and (vi) decision-making. In the first phase, FAIRification
preparation tasks are performed. In phase two, the organisation's infrastructure is assessed for its ability
to support initial objectives. In the third phase, stakeholders are categorised into domain and FAIR
experts, and knowledge gaps between them are addressed to facilitate communication. In the fourth
phase, the domain scope, competency questions for modelling (meta)data, and objectives based on
potential reusers of the FAIR resource are defined. In the fifth phase, the objectives initially identified
are further refined. Finally, implementation decisions are made to achieve the FAIRification objectives
in phase six. These phases are accompanied by validation sessions with domain and FAIR experts. The
FAIRification objectives identified with GO-Plan are used to guide and constrain the subsequent
FAIRification (meta)data modelling steps and to support the selection of ontologies to be reused.
3. Discussion
We anticipate that GO-Plan will help stakeholders better define implementation strategies. By
establishing clear objectives through the method, people conducting FAIRification can effectively
guide and justify implementation choices and determine the (meta)data elements that must be collected
and published to facilitate FAIR data reuse.
4. References
[1] Bernabé et al. A goal-oriented method for FAIRification planning, 23 June 2023, PREPRINT
Available at: https://doi.org/10.21203/rs.3.rs-3092538/v1
Proceedings of the International Conference on Biomedical Ontologies 2023, August 28th-September 1st, 2023, Brasilia, Brazil
EMAIL: c.h.bernabe@lumc.nl (C. Bernabé); a.jacobsen@lumc.nl (A. Jacobsen); l.o.boninodasilvasantos@utwente.nl (L. O. Bonino da S. S.),
m.roos@lumc.nl (M. Roos)
ORCID: 0000-0003-1795-5930 (C. Bernabé); 0000-0003-4818-2360 (A. Jacobsen); 0000-0002-1164-1351 (L. O. Bonino da S. S.), 0000-
0002-8691-772X (M. Roos)
© 2023 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
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