利益与挑战:两个协作项目中的数据管理计划

Q2 Computer Science
Denise Jäckel, Anna Lehmann
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引用次数: 1

摘要

科学研究的数据驱动转变导致了更广泛的研究数据。为了以可持续和充分的方式管理这些数据,建立了数据管理计划(dmp)作为一种方法。然而,由于缺乏时间、资源和对需求的理解,一些研究人员仍然没有创建dmp。此外,大多数现有的模板和工具在很大程度上是未知的。在本文中,我们在几个学术机构的两个联合研究项目中调查了dmp的好处和挑战。为此,我们描述了创建DMP的过程、潜在的挑战和所经历的好处。我们表明,由于个体和主体的差异(例如,存储和政策),在合作机构之间完全统一内容的DMP是不可能的。相反,在某些情况下,必须拟订个别案文,以克服多样性。现有的工具无法处理这种复杂性。因此,这两个项目都创建了一个带有一些通用内容的自适应模板。现有的指导方针和内部项目政策在生成过程中有所帮助。我们的经验是,很少有人比许多人更有效地在DMP上工作,项目中的所有研究人员都可以从每个DMP中获利。虽然我们没有被要求生产一个,但我们认识到在联合项目的研究过程中,相关的好处可以作为指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Benefits and Challenges: Data Management Plans in Two Collaborative Projects
The data-driven shift in the science research leads to a wider range of research data. To manage this data in a sustainable and adequate way, data management plans (DMPs) were established as a method. However, some researchers still do not create DMPs due to lack of time, resources and understanding of the needs. Furthermore, most of the existing templates and tools are largely unknown. In this article, we investigated the benefits and challenges of DMPs in two joint research projects of several academic institutions. For this, we described the process during the DMP creation, potential challenges and benefits experienced. We showed that a DMP with completely uniform content among the partner institutions was not possible due to individual and subject differences (e.g., in storage and policies). Instead, individual texts had to be formulated in some cases to overcome the diversity. This complexity could not be handled with the existing tools. Therefore, both projects created an own adapted template with some generic contents. Existing guidelines and internal project policies helped during the generation. We experienced that fewer people work more efficiently on a DMP than many and that all researchers within the project can profit from every individual DMP. Although we were not required to produce one, we recognised the associated benefits as a guide during the research process in joint projects.
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来源期刊
Data Science Journal
Data Science Journal Computer Science-Computer Science (miscellaneous)
CiteScore
5.40
自引率
0.00%
发文量
17
审稿时长
10 weeks
期刊介绍: The Data Science Journal is a peer-reviewed electronic journal publishing papers on the management of data and databases in Science and Technology. Details can be found in the prospectus. The scope of the journal includes descriptions of data systems, their publication on the internet, applications and legal issues. All of the Sciences are covered, including the Physical Sciences, Engineering, the Geosciences and the Biosciences, along with Agriculture and the Medical Science. The journal publishes papers about data and data systems; it does not publish data or data compilations. However it may publish papers about methods of data compilation or analysis.
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