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Scientometric Mapping as a Strategic Intelligence Tool for the Governance of Emerging Technologies

Author

Listed:
  • Daniele Rotolo

    (SPRU, University of Sussex, UK)

  • Ismael Rafols

    (SPRU, University of Sussex, UK
    Ingenio (CSIC-UPV), Universitat Politecnica de Valencia)

  • Michael Hopkins

    (SPRU, University of Sussex, UK)

  • Loet Leydesdorff

    (Amsterdam School of Communication Research (ASCoR), University of Amsterdam)

Abstract

How can scientometric mapping function as a tool of ’strategic intelligence’ to aid the governance of emerging technologies? The present paper aims to address this question by focusing on a set of recently developed scientometric techniques, namely overlay mapping. We examine the potential these techniques have to inform, in a timely manner, analysts and decision-makers about relevant dynamics of technical emergence. We investigate the capability of overlay mapping in generating informed perspectives about emergence across three spaces: geographical, social, and cognitive. Our analysis relies on three empirical studies of emerging technologies in the biomedical domain: RNA interference (RNAi), Human Papilloma Virus (HPV) testing technologies for cervical cancer, and Thiopurine Methyltransferase (TPMT) genetic testing. The case-studies are analysed and mapped longitudinally by using publication and patent data. Results show the variety of ’intelligence’ inputs overlay mapping can produce for the governance of emerging technologies. Overlay mapping also confers to the investigation of emergence flexibility and granularity in terms of adaptability to different sources of data and selection of the levels of the analysis, respectively. These features make possible the integration and comparison of results from different contexts and cases, thus providing possibilities for a potentially more ’distributed’ strategic intelligence. The generated perspectives allow triangulation of findings, which is important given the complexity featuring in technical emergence and the limitations associated with the use of single scientometric approaches

Suggested Citation

  • 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.
    • Handle: RePEc:sru:ssewps:2014-10
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    References listed on IDEAS

    as
    1. Loet Leydesdorff & Olle Persson, 2010. "Mapping the geography of science: Distribution patterns and networks of relations among cities and institutes," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(8), pages 1622-1634, August.
    2. Loet Leydesdorff & Lutz Bornmann, 2012. "Mapping (USPTO) patent data using overlays to Google Maps," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(7), pages 1442-1458, July.
    3. Zvi Griliches, 1998. "Productivity, R&D, and the Data Constraint," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 347-374, National Bureau of Economic Research, Inc.
    4. Lutz Bornmann & Loet Leydesdorff, 2011. "Which cities produce more excellent papers than can be expected? A new mapping approach, using Google Maps, based on statistical significance testing," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 1954-1962, October.
    5. Ludo Waltman & Nees Jan van Eck, 2012. "A new methodology for constructing a publication‐level classification system of science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    6. Kuhlmann, Stefan & Boekholt, Patries & Georghiou, Luke & Guy, Ken & Heraud, Jean-Alain & Laredo, Philippe & Lemola, Tarmo & Loveridge, Denis & Luukkonen, Terttu & Moniz, António & Polt, Wolfgang & Rip, 1999. "Improving Distributed Intelligence in Complex Innovation Systems," MPRA Paper 6426, University Library of Munich, Germany, revised May 1999.
    7. Andrew Fire & SiQun Xu & Mary K. Montgomery & Steven A. Kostas & Samuel E. Driver & Craig C. Mello, 1998. "Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans," Nature, Nature, vol. 391(6669), pages 806-811, February.
    8. Murray, Fiona, 2002. "Innovation as co-evolution of scientific and technological networks: exploring tissue engineering," Research Policy, Elsevier, vol. 31(8-9), pages 1389-1403, December.
    9. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    10. 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.
    11. Paul Nightingale & Tim Brady & Andrew Davies & Jeremy Hall, 2003. "Capacity utilization revisited: software, control and the growth of large technical systems," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 12(3), pages 477-517, June.
    12. Guangyuan Hu & Stephen Carley & Li Tang, 2012. "Visualizing nanotechnology research in Canada: evidence from publication activities, 1990–2009," The Journal of Technology Transfer, Springer, vol. 37(4), pages 550-562, August.
    13. Loet Leydesdorff & Ismael Rafols, 2011. "Local emergence and global diffusion of research technologies: An exploration of patterns of network formation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(5), pages 846-860, May.
    14. Ed Noyons, 2001. "Bibliometric mapping of science in a policy context," Scientometrics, Springer;Akadémiai Kiadó, vol. 50(1), pages 83-98, January.
    15. Andy Stirling, 2007. "A General Framework for Analysing Diversity in Science, Technology and Society," SPRU Working Paper Series 156, SPRU - Science Policy Research Unit, University of Sussex Business School.
    16. Ludo Waltman & Nees Jan Eck, 2012. "A new methodology for constructing a publication-level classification system of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    17. Loet Leydesdorff & Daniele Rotolo & Ismael Rafols, 2012. "Bibliometric perspectives on medical innovation using the medical subject Headings of PubMed," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(11), pages 2239-2253, November.
    18. David, Paul A, 1985. "Clio and the Economics of QWERTY," American Economic Review, American Economic Association, vol. 75(2), pages 332-337, May.
    19. Luciano Kay & Nils Newman & Jan Youtie & Alan L. Porter & Ismael Rafols, 2014. "Patent overlay mapping: Visualizing technological distance," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(12), pages 2432-2443, December.
    20. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    21. Loet Leydesdorff & Ismael Rafols & Chaomei Chen, 2013. "Interactive overlays of journals and the measurement of interdisciplinarity on the basis of aggregated journal–journal citations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(12), pages 2573-2586, December.
    22. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
    23. 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.
    24. Joachim Schummer, 2004. "Multidisciplinarity, interdisciplinarity, and patterns of research collaboration in nanoscience and nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(3), pages 425-465, March.
    25. Verbong, Geert & Geels, Frank, 2007. "The ongoing energy transition: Lessons from a socio-technical, multi-level analysis of the Dutch electricity system (1960-2004)," Energy Policy, Elsevier, vol. 35(2), pages 1025-1037, February.
    26. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    27. Geels, Frank W., 2002. "Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study," Research Policy, Elsevier, vol. 31(8-9), pages 1257-1274, December.
    28. Alan L. Porter & Ismael Rafols, 2009. "Is science becoming more interdisciplinary? Measuring and mapping six research fields over time," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 719-745, December.
    29. Corrocher Nicoletta & Malerba Franco & Montobbio Fabio, 2003. "The emergence of new technologies in the ICT field: main actors, geographical distribution and knowledge sources," Economics and Quantitative Methods qf0317, Department of Economics, University of Insubria.
    30. Ismael Rafols & Alan Porter & Loet Leydesdorff, 2009. "Overlay Maps of Science: a New Tool for Research Policy," SPRU Working Paper Series 179, SPRU - Science Policy Research Unit, University of Sussex Business School.
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    Cited by:

    1. Daniele Rotolo & Loet Leydesdorff, 2014. "Matching MEDLINE/PubMed Data with Web of Science (WOS): A Routine in R language," SPRU Working Paper Series 2014-14, SPRU - Science Policy Research Unit, University of Sussex Business School.
    2. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    3. Leonid Gokhberg & Ilya Kuzminov & Pavel Bakhtin & Elena Tochilina & Alexander Chulok & Anton Timofeev & Alina Lavrinenko, 2017. "Big-Data-Augmented Approach to Emerging Technologies Identification: Case of Agriculture and Food Sector," HSE Working papers WP BRP 76/STI/2017, National Research University Higher School of Economics.

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