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How (not) to design and implement a large-scale, interdisciplinary research infrastructure
Science and Public Policy ( IF 2.6 ) Pub Date : 2020-12-22 , DOI: 10.1093/scipol/scaa042
David Kaufmann 1 , Johanna Kuenzler 2 , Fritz Sager 2
Affiliation  

Research is increasingly carried out in large-scale, interdisciplinary research programs that aim to tackle complex, multidimensional, and future-oriented challenges. We explore the case of the Swiss Initiative in Systems Biology (SystemsX.ch), the largest ever Swiss research program, and more specifically the partial failure of the program’s IT-project SyBIT. Apart from providing IT and data science support, SyBIT aimed to establish a common data repository. The establishment of this common data repository failed. Based on an interdisciplinary analytical framework, we propose that five explanatory factors account for this failure: a lack of demand from researchers, technological complexity of heterogeneous data formats, absence of governance decisions in favor of the data repository, interpersonal problems, and political difficulties. We conclude that for large-scale research infrastructure, the policy design is crucial for success, given that it can result in positive or negative after effects, such as user resistance versus acceptance and technological complexity versus coherence.

中文翻译:

如何(不)设计和实施大规模的跨学科研究基础设施

越来越多的大型跨学科研究计划进行了研究,旨在应对复杂,多维和面向未来的挑战。我们将探讨瑞士系统生物学倡议(SystemsX.ch)的案例,这是瑞士规模最大的研究计划,尤其是该计划的IT项目SyBIT的部分失败。除了提供IT和数据科学支持外,SyBIT的目标是建立一个通用的数据存储库。该公共数据存储库的建立失败。基于跨学科的分析框架,我们提出了造成这种失败的五个解释性因素:研究人员的需求不足,异构数据格式的技术复杂性,缺乏有利于数据存储库的治理决策,人际问题以及政治困难。
更新日期:2020-12-22
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