Reilly, Dorothy, Alharbi, Ebtisam, Gadiya, Yojana , Henderson, David, Zaliani, Andrea , Delfin-Rossaro, Alejandra , Cambon-Thomsen, Anne , Witt, Gesa , Welter, Danielle , Juty, Nick, Jay, Caroline, Goble, Carol, Satagopam, Venkata , Ioannidis, Vassilios , Gu, Wei and Gribbon, Phil (2022) Selection of datasets for FAIRification in Drug Discovery and Development: Which, Why, and How? Drug discovery today. ISSN 1878-5832

Abstract

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.

Item Type:	Article
Keywords:	FAIRplus, FAIR, FAIR data stewardship, Innovative Medicines Initiative
Date Deposited:	05 Jun 2022 00:45
Last Modified:	14 Jun 2022 00:45
URI:	https://oak.novartis.com/id/eprint/46576