激励研究数据共享:一项范围综述
Incentivising research data sharing: a scoping review.
作者信息
Woods Helen Buckley, Pinfield Stephen
机构信息
Research on Research Institute, Information School, University of Sheffield, Sheffield, South Yorkshire, S10 2TN, UK.
出版信息
Wellcome Open Res. 2022 Apr 6;6:355. doi: 10.12688/wellcomeopenres.17286.2. eCollection 2021.
Numerous mechanisms exist to incentivise researchers to share their data. This scoping review aims to identify and summarise evidence of the efficacy of different interventions to promote open data practices and provide an overview of current research. This scoping review is based on data identified from Web of Science and LISTA, limited from 2016 to 2021. A total of 1128 papers were screened, with 38 items being included. Items were selected if they focused on designing or evaluating an intervention or presenting an initiative to incentivise sharing. Items comprised a mixture of research papers, opinion pieces and descriptive articles. Seven major themes in the literature were identified: publisher/journal data sharing policies, metrics, software solutions, research data sharing agreements in general, open science 'badges', funder mandates, and initiatives. A number of key messages for data sharing include: the need to build on existing cultures and practices, meeting people where they are and tailoring interventions to support them; the importance of publicising and explaining the policy/service widely; the need to have disciplinary data champions to model good practice and drive cultural change; the requirement to resource interventions properly; and the imperative to provide robust technical infrastructure and protocols, such as labelling of data sets, use of DOIs, data standards and use of data repositories.
存在多种激励研究人员共享数据的机制。本综述旨在识别和总结不同干预措施促进开放数据实践的有效性证据,并概述当前的研究情况。本综述基于从科学网和图书馆、信息科学与技术文摘数据库(LISTA)中检索到的数据,时间范围限制在2016年至2021年。共筛选了1128篇论文,纳入了38篇文章。如果文章专注于设计或评估一项干预措施,或提出一项激励共享的倡议,则会被选中。文章包括研究论文、观点文章和描述性文章的混合。文献中确定了七个主要主题:出版商/期刊数据共享政策、指标、软件解决方案、一般研究数据共享协议、开放科学“徽章”、资助者要求和倡议。关于数据共享的一些关键信息包括:需要在现有文化和实践的基础上进行建设,在人们所处的位置与他们接触,并量身定制干预措施以支持他们;广泛宣传和解释政策/服务的重要性;需要有学科数据倡导者来树立良好实践榜样并推动文化变革;为干预措施提供适当资源的必要性;以及提供强大技术基础设施和协议的紧迫性,例如数据集的标注、数字对象标识符(DOI)的使用、数据标准和数据存储库的使用。
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