Revolutions in science: The proposal of an approach for the identification of most important researchers, institutions and countries based on co-citation reference publication year spectroscopy exemplified at research on physical modelling of Earth’s climate

IF 1.7 4区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
L. Bornmann, R. Haunschild, W. Marx
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引用次数: 0

Abstract

Reference Publication Year Spectroscopy (RPYS) is a bibliometric method originally introduced to reveal the historical roots of research topics or fields. RPYS does not identify the most highly cited papers of the publication set being studied (as is usually done by bibliometric analyses in research evaluation), but instead it indicates most frequently referenced publications – each within a specific reference publication year. In this study, we propose to use the method to identify important researchers, institutions, and countries in the context of breakthrough research. To do so, we focus on research on physical modeling of Earth’s climate and the prediction of global warming as an example. Klaus Hasselmann (KH) and Syukuro Manabe (SM) were both honoured with the Nobel Prize in 2021 for their fundamental contributions to research on physical modeling of Earth’s climate and the prediction of global warming. Our results reveal that RPYS is able to identify most important researchers, institutions, and countries. In our example, all the relevant authors’ institutions are located in the United States. These institutions are either research centers of two US National Research Administrations (NASA and NOAA) or universities: the University of Arizona, Princeton University, the Massachusetts Institute of Technology (MIT), and the University of Stony Brook. The limitations of our approach to identify important researchers, institutions, and countries in the context of breakthrough research are discussed.
科学革命:提出一种基于共引参考出版年份光谱学来识别最重要的研究人员、机构和国家的方法,以地球气候物理模型研究为例
文献出版年光谱(RPYS)是一种文献计量学方法,最初是为了揭示研究课题或领域的历史根源而引入的。RPYS不确定被研究的出版物中被引用次数最多的论文(这通常是研究评估中的文献计量分析所做的),而是指出被引用次数最多的出版物——每一篇都在一个特定的参考出版年内。在本研究中,我们建议使用该方法来识别突破性研究背景下的重要研究者、机构和国家。为此,我们以地球气候的物理模拟和全球变暖的预测为例进行了研究。Klaus Hasselmann (KH)和Syukuro Manabe (SM)因其在地球气候物理模型研究和全球变暖预测方面的基础贡献,于2021年获得诺贝尔奖。我们的研究结果表明,RPYS能够识别最重要的研究人员、机构和国家。在我们的例子中,所有相关作者的机构都位于美国。这些机构要么是两个美国国家研究管理局(NASA和NOAA)的研究中心,要么是大学:亚利桑那大学、普林斯顿大学、麻省理工学院(MIT)和石溪大学。讨论了在突破性研究背景下识别重要研究人员、机构和国家的方法的局限性。
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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来源期刊
Journal of Information Science
Journal of Information Science 工程技术-计算机:信息系统
CiteScore
6.80
自引率
8.30%
发文量
121
审稿时长
4 months
期刊介绍: The Journal of Information Science is a peer-reviewed international journal of high repute covering topics of interest to all those researching and working in the sciences of information and knowledge management. The Editors welcome material on any aspect of information science theory, policy, application or practice that will advance thinking in the field.
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