Selection of data sets for FAIRification in drug discovery and development: Which, why, and how?
Selection of data sets for FAIRification in drug discovery and development: Which, why, and how?
复制标题
DOI：
10.1016/j.drudis.2022.05.010
复制
发表时间：
2022-08
影响因子：
7.4
通讯作者：
Gribbon, Philip
中科院分区：
文献类型：
--
作者：
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
研究机构的重点是量化实施公平竞争的成本和效益。用于选择公平评价数据的标准可能不透明和不一致。公平化工作取决于个人技能、能力、资源和可用时间。FAIRification应满足再利用的情景，并导致科学和经济的影响。组织的挑战包括为个人提供培训和发展公平的组织文化。尽管在学术和工业领域采用可查找、可扩展、可互操作和可重用（FAIR）原则具有直观的价值，但在资源配置、平衡长期与短期优先事项以及实现技术实施方面仍存在挑战。在就公平投资回报作出决定时，评估成本和效益的机制不明确，使这种情况更加严重。科学和研究与发展（研发）领导层需要关于潜在效益的可靠证据以及关于有效执行机制和补救战略的信息。在这篇文章中，我们描述了成本效益评估的程序，并确定最佳实践方法，以支持决策过程中涉及的公平实施。
Research organisations are focussed on quantifying the costs and benefits of implementing FAIR. Criteria used for the selection of data for FAIRification can be opaque and inconsistent. FAIRification effort depends on individual skills, competencies, resources, and time available. FAIRification should satisfy reuse scenarios, and lead to scientific and economic impacts. Organisational challenges include providing training to individuals and developing a FAIR organisation culture. 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.
登录
查看更多内容
DOI：
10.1016/j.patter.2021.100322
发表时间：
2021-09-10
期刊：
Patterns (New York, N.Y.)
影响因子：
--
作者：
Leipzig J;Nüst D;Hoyt CT;Ram K;Greenberg J
通讯作者：
Greenberg J
影响因子：
4.3
作者：
Corpas M;Kovalevskaya NV;McMurray A;Nielsen FGG
通讯作者：
Nielsen FGG
影响因子：
3.9
作者：
Arefolov, Alexander;Adam, Laura;McCreary, Mark
通讯作者：
McCreary, Mark
影响因子：
5.2
作者：
Staunton, Ciara;Slokenberga, Santa;Mascalzoni, Deborah
通讯作者：
Mascalzoni, Deborah
影响因子：
5.6
作者：
Briggs, Katharine;Bosc, Nicolas;Steger-Hartmann, Thomas
通讯作者：
Steger-Hartmann, Thomas