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Selection of data sets for FAIRification in drug discovery and development: Which, why, and how?

Authors :
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center]
European Commission - EC [sponsor]
Alharbi, Ebtisam
Gadiya, Yojana
Henderson, David
Zaliani, Andrea
Delfin-Rossaro, Alejandra
Cambon-Thomsen, Anne
Kohler, Manfred
Witt, Gesa
Welter, Danielle
Juty, Nick
Jay, Caroline
Engkvist, Ola
Goble, Carole
Reilly, Dorothy S.
Satagopam, Venkata
Ioannidis, Vassilios
Gu, Wei
Gribbon, Philip
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center]
European Commission - EC [sponsor]
Alharbi, Ebtisam
Gadiya, Yojana
Henderson, David
Zaliani, Andrea
Delfin-Rossaro, Alejandra
Cambon-Thomsen, Anne
Kohler, Manfred
Witt, Gesa
Welter, Danielle
Juty, Nick
Jay, Caroline
Engkvist, Ola
Goble, Carole
Reilly, Dorothy S.
Satagopam, Venkata
Ioannidis, Vassilios
Gu, Wei
Gribbon, Philip
Publication Year :
2022

Abstract

Despite the intuitive value of adopting the Findable, Accessible, Interoperable, and Reusable (FAIR) principles in both academic and industrial sectors, challenges exist in resourcing, balancing long- versus short-term priorities, and achieving technical implementation. This situation is exacerbated by the unclear mechanisms by which costs and benefits can be assessed when decisions on FAIR are made. Scientific and research and development (R&D) leadership need reliable evidence of the potential benefits and information on effective implementation mechanisms and remediating strategies. In this article, we describe procedures for cost–benefit evaluation, and identify best-practice approaches to support the decision-making process involved in FAIR implementation.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1334949571
Document Type :
Electronic Resource