Data Curation in Interdisciplinary and Highly Collaborative Research

Inna Kouper
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Abstract

This paper provides a systematic analysis of publications that discuss data curation in interdisciplinary and highly collaborative research (IHCR). Using content analysis methodology, it examined 159 publications and identified patterns in definitions of interdisciplinarity, projects’ participants and methodologies, and approaches to data curation. The findings suggest that data is a prominent component in interdisciplinarity. In addition to crossing disciplinary and other boundaries, IHCR is defined as curating and integrating heterogeneous data and creating new forms of knowledge from it. Using personal experiences and descriptive approaches, the publications discussed challenges that data curation in IHCR faces, including an increased overhead in coordination and management, lack of consistent metadata practices, and custom infrastructure that makes interoperability across projects, domains, and repositories difficult. The paper concludes with suggestions for future research.
跨学科和高度协作研究中的数据管理
本文对跨学科和高度合作研究(IHCR)中讨论数据管理的出版物进行了系统分析。使用内容分析方法,它检查了159份出版物,并确定了跨学科定义、项目参与者和方法以及数据管理方法的模式。研究结果表明,数据是跨学科的重要组成部分。除了跨越学科和其他界限外,国际人道主义责任还被定义为管理和整合异构数据,并从中创造新形式的知识。这些出版物利用个人经验和描述性方法,讨论了IHCR数据管理面临的挑战,包括协调和管理方面的开销增加,缺乏一致的元数据实践,以及使项目、领域和存储库之间的互操作性变得困难的定制基础设施。最后,对今后的研究提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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