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High-impact papers presented in the subject category of water resources in the essential science indicators database of the institute for scientific information

Author

Listed:
  • Kun-Yang Chuang

    (Taipei Medical University)

  • Ming-Huang Wang

    (Peking University)

  • Yuh-Shan Ho

    (Peking University
    Asia University)

Abstract

The Essential Science Indicators (ESI) database is widely used to evaluate institutions and researchers. The objective of this study was to analyze trends and characteristics of papers in the subject category of water resources in the ESI database of the Institute for Scientific Information (ISI). Distributions of document type, language of publication, scientific output, and publication of journals are reported in this article. Five indicators (the number and ranking of total papers, first-author papers, corresponding-author papers, independent papers, and collaborative papers) were applied to evaluate country, institute, and author performances. In addition, the numbers of authors cited, numbers of institutes cited, numbers of countries cited, and numbers of subject areas cited were also used to evaluate ESI papers. Results showed that 265 papers, all written in English, were listed in 27 journals in the field of water resources. A review paper was more likely to be included in the ESI than a research paper. Journal of Hydrology published the most papers. The USA and UK were the two leading nations. ESI papers published in the US were more likely to involve inter-institutional collaboration than papers published in the UK. The University of Arizona was the most productive institute. Some papers that were almost excluded from the ESI database appear to have consistently received annual high frequencies of citation. Perhaps the 10 year criterion for inclusion in the ESI should be reassessed.

Suggested Citation

  • Kun-Yang Chuang & Ming-Huang Wang & Yuh-Shan Ho, 2011. "High-impact papers presented in the subject category of water resources in the essential science indicators database of the institute for scientific information," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 551-562, June.
    • Handle: RePEc:spr:scient:v:87:y:2011:i:3:d:10.1007_s11192-011-0365-2
    DOI: 10.1007/s11192-011-0365-2
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    10. Liao, Huchang & Tang, Ming & Li, Zongmin & Lev, Benjamin, 2019. "Bibliometric analysis for highly cited papers in operations research and management science from 2008 to 2017 based on Essential Science Indicators," Omega, Elsevier, vol. 88(C), pages 223-236.
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    14. Barbosa, Fabiana G. & Schneck, Fabiana, 2015. "Characteristics of the top-cited papers in species distribution predictive models," Ecological Modelling, Elsevier, vol. 313(C), pages 77-83.
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