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A bibliometric analysis of NOAA’s Office of Ocean Exploration and Research

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  • Chris W. Belter

    (NOAA Central Library)

Abstract

Bibliometric analysis techniques are increasingly being used to analyze and evaluate scientific research produced by institutions and grant funding agencies. This article uses bibliometric methods to analyze journal articles funded by NOAA’s Office of Ocean Exploration and Research (OER), an extramural grant-funding agency focused on the scientific exploration of the world’s oceans. OER-supported articles in this analysis were identified through grant reports, personal communication, and acknowledgement of OER support or grant numbers. The articles identified were analyzed to determine the number of publications and citations received per year, subject, and institution. The productivity and citation impact of institutions in the US receiving OER grant funding were mapped geographically. Word co-occurrence and bibliographic coupling networks were created and visualized to identify the research topics of OER-supported articles. Finally, article citation counts were evaluated by means of percentile ranks. This article demonstrates that bibliometric analysis can be useful for summarizing and evaluating the research performance of a grant funding agency.

Suggested Citation

  • Chris W. Belter, 2013. "A bibliometric analysis of NOAA’s Office of Ocean Exploration and Research," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 629-644, May.
    • Handle: RePEc:spr:scient:v:95:y:2013:i:2:d:10.1007_s11192-012-0836-0
    DOI: 10.1007/s11192-012-0836-0
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    References listed on IDEAS

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    1. Angela M. Zoss & Katy Börner, 2012. "Mapping interactions within the evolving science of science and innovation policy community," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 631-644, May.
    2. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    3. Loet Leydesdorff & Lutz Bornmann & Rüdiger Mutz & Tobias Opthof, 2011. "Turning the tables on citation analysis one more time: Principles for comparing sets of documents," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(7), pages 1370-1381, July.
    4. Ismael Rafols & Alan L. Porter & Loet Leydesdorff, 2010. "Science overlay maps: A new tool for research policy and library management," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(9), pages 1871-1887, September.
    5. Salter, Ammon J. & Martin, Ben R., 2001. "The economic benefits of publicly funded basic research: a critical review," Research Policy, Elsevier, vol. 30(3), pages 509-532, March.
    6. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    7. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    8. Ed Noyons, 2001. "Bibliometric mapping of science in a policy context," Scientometrics, Springer;Akadémiai Kiadó, vol. 50(1), pages 83-98, January.
    9. Radmila Lyubarova & Brandon K Itagaki & Michael W Itagaki, 2009. "The Impact of National Institutes of Health Funding on U.S. Cardiovascular Disease Research," PLOS ONE, Public Library of Science, vol. 4(7), pages 1-8, July.
    10. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    11. Kevin W. Boyack & Katy Börner, 2003. "Indicator‐assisted evaluation and funding of research: Visualizing the influence of grants on the number and citation counts of research papers," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(5), pages 447-461, March.
    12. Bourke, Paul & Butler, Linda, 1999. "The efficacy of different modes of funding research: perspectives from Australian data on the biological sciences," Research Policy, Elsevier, vol. 28(5), pages 489-499, June.
    13. Dangzhi Zhao, 2010. "Characteristics and impact of grant-funded research: a case study of the library and information science field," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 293-306, August.
    14. Narin, Francis & Hamilton, Kimberly S. & Olivastro, Dominic, 1997. "The increasing linkage between U.S. technology and public science," Research Policy, Elsevier, vol. 26(3), pages 317-330, October.
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    Cited by:

    1. Elaine Aparecida Regiani Campos & Regina Negri Pagani & Luis Mauricio Resende & Joseane Pontes, 2018. "Construction and qualitative assessment of a bibliographic portfolio using the methodology Methodi Ordinatio," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 815-842, August.
    2. Jayshree Mamtora & Jacqueline K. Wolstenholme & Gaby Haddow, 2014. "Environmental sciences research in northern Australia, 2000–2011: a bibliometric analysis within the context of a national research assessment exercise," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 265-281, January.
    3. Torger Möller & Marion Schmidt & Stefan Hornbostel, 2016. "Assessing the effects of the German Excellence Initiative with bibliometric methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2217-2239, December.
    4. Elio Atenógenes Villaseñor & Ricardo Arencibia-Jorge & Humberto Carrillo-Calvet, 2017. "Multiparametric characterization of scientometric performance profiles assisted by neural networks: a study of Mexican higher education institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 77-104, January.

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