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The detection of “hot regions” in the geography of science—A visualization approach by using density maps

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  • Bornmann, Lutz
  • Waltman, Ludo

Abstract

Spatial scientometrics has attracted a lot of attention in the very recent past. The visualization methods (density maps) presented in this paper allow for an analysis revealing regions of excellence around the world using computer programs that are freely available. Based on Scopus and Web of Science data, field-specific and field-overlapping scientific excellence can be identified in broader regions (worldwide or for a specific continent) where high quality papers (highly cited papers or papers published in Nature or Science) were published. We used a geographic information system to produce our density maps. We also briefly discuss the use of Google Earth.

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  • Bornmann, Lutz & Waltman, Ludo, 2011. "The detection of “hot regions” in the geography of science—A visualization approach by using density maps," Journal of Informetrics, Elsevier, vol. 5(4), pages 547-553.
    • Handle: RePEc:eee:infome:v:5:y:2011:i:4:p:547-553
    DOI: 10.1016/j.joi.2011.04.006
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    Cited by:

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    2. Copiello, Sergio, 2019. "Peer and neighborhood effects: Citation analysis using a spatial autoregressive model and pseudo-spatial data," Journal of Informetrics, Elsevier, vol. 13(1), pages 238-254.
    3. Bornmann, Lutz & Leydesdorff, Loet, 2012. "Which are the best performing regions in information science in terms of highly cited papers? Some improvements of our previous mapping approaches," Journal of Informetrics, Elsevier, vol. 6(2), pages 336-345.
    4. Djuro Kutlača & Dragan Babić & Lazar Živković & Dijana Štrbac, 2015. "Analysis of quantitative and qualitative indicators of SEE countries scientific output," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 247-265, January.
    5. Csomós, György, 2018. "Reprint of “A spatial scientometric analysis of the publication output of cities worldwide”," Journal of Informetrics, Elsevier, vol. 12(2), pages 547-566.
    6. Bornmann, Lutz & Ozimek, Adam, 2012. "Stata commands for importing bibliometric data and processing author address information," Journal of Informetrics, Elsevier, vol. 6(4), pages 505-512.
    7. Bornmann, Lutz & Stefaner, Moritz & de Moya Anegón, Felix & Mutz, Rüdiger, 2014. "What is the effect of country-specific characteristics on the research performance of scientific institutions? Using multi-level statistical models to rank and map universities and research-focused in," Journal of Informetrics, Elsevier, vol. 8(3), pages 581-593.
    8. János József Tóth & Gergő Háló & Manuel Goyanes, 2023. "Beyond views, productivity, and citations: measuring geopolitical differences of scientific impact in communication research," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5705-5729, October.
    9. Abramo, Giovanni & D’Angelo, Ciriaco Andrea, 2015. "A methodology to compute the territorial productivity of scientists: The case of Italy," Journal of Informetrics, Elsevier, vol. 9(4), pages 675-685.
    10. Michael Gowanlock & Rich Gazan, 2013. "Assessing researcher interdisciplinarity: a case study of the University of Hawaii NASA Astrobiology Institute," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 133-161, January.
    11. Daniele Rotolo & Ismael Rafols & Michael Hopkins & Loet Leydesdorff, 2014. "Scientometric Mapping as a Strategic Intelligence Tool for the Governance of Emerging Technologies," SPRU Working Paper Series 2014-10, SPRU - Science Policy Research Unit, University of Sussex Business School.

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