Managing data in cross-institutional projects

IASSIST quarterly Pub Date : 2019-09-25 DOI:10.29173/iq950
Z. Hansen, F. Kruse, J. Thestrup
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引用次数: 1

Abstract

This paper provides guidelines for data management professionals and researchers on how FAIR data usage can help improve the planning, execution and overall success of a cross-institutional project. Cases from Danish cross-institutional projects are detailed to illustrate this point – as well as the lessons learnt with implementing FAIR data principles in such projects. Key learnings from this paper are: Using FAIR data principles in cross-institutional projects can help manage the data used in the project in terms of knowledge sharing, access rights, use of templates, metadata and further sharing the data after the project has ended. To benefit the most from using FAIR data in a cross-institutional project it should be considered and planned for early in the project process. If FAIR is not considered early in the project process problems can arise such as a lot of time spent on converting formats, obtaining permissions and assigning metadata. It is necessary for researchers and research projects to have infrastructure and other services in place which support FAIR data usage.
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管理跨机构项目中的数据
本文为数据管理专业人员和研究人员提供了关于公平数据使用如何帮助改善跨机构项目的规划、执行和总体成功的指导方针。丹麦跨机构项目的案例详细说明了这一点,以及在这些项目中实施公平数据原则的经验教训。本文的主要经验是:在跨机构项目中使用FAIR数据原则有助于管理项目中使用的数据,包括知识共享、访问权、模板使用、元数据以及项目结束后进一步共享数据。为了从跨机构项目中使用公平数据中获益最大,应该在项目过程的早期就考虑和规划公平数据。如果在项目过程的早期没有考虑到FAIR,可能会出现问题,例如在转换格式、获得权限和分配元数据上花费了大量时间。研究人员和研究项目有必要拥有支持公平数据使用的基础设施和其他服务。
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