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A concept for inferring ‘frontier research’ in grant proposals

Author

Listed:
  • Marianne Hörlesberger

    (AIT Austrian Institute of Technology GmbH)

  • Ivana Roche

    (CNRS, Institut de l’Information Scientifique et Technique)

  • Dominique Besagni

    (CNRS, Institut de l’Information Scientifique et Technique)

  • Thomas Scherngell

    (AIT Austrian Institute of Technology GmbH)

  • Claire François

    (CNRS, Institut de l’Information Scientifique et Technique)

  • Pascal Cuxac

    (CNRS, Institut de l’Information Scientifique et Technique)

  • Edgar Schiebel

    (AIT Austrian Institute of Technology GmbH)

  • Michel Zitt

    (INRA
    Observatoire des Sciences et des Techniques (OST))

  • Dirk Holste

    (AIT Austrian Institute of Technology GmbH)

Abstract

This paper discusses a concept for inferring attributes of ‘frontier research’ in peer-reviewed research proposals under the popular scheme of the European Research Council (ERC). The concept serves two purposes: firstly to conceptualize, define and operationalize in scientometric terms attributes of frontier research; and secondly to build and compare outcomes of a statistical model with the review decision in order to obtain further insight and reflect upon the influence of frontier research in the peer-review process. To this end, indicators across scientific disciplines and in accord with the strategic definition of frontier research by the ERC are elaborated, exploiting textual proposal information and other scientometric data of grant applicants. Subsequently, a suitable model is formulated to measure ex-post the influence of attributes of frontier research on the decision probability of a proposal to be accepted. We present first empirical data as proof of concept for inferring frontier research in grant proposals. Ultimately the concept is aiming at advancing the methodology to deliver signals for monitoring the effectiveness of peer-review processes.

Suggested Citation

  • Marianne Hörlesberger & Ivana Roche & Dominique Besagni & Thomas Scherngell & Claire François & Pascal Cuxac & Edgar Schiebel & Michel Zitt & Dirk Holste, 2013. "A concept for inferring ‘frontier research’ in grant proposals," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 129-148, November.
    • Handle: RePEc:spr:scient:v:97:y:2013:i:2:d:10.1007_s11192-013-1008-6
    DOI: 10.1007/s11192-013-1008-6
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    References listed on IDEAS

    as
    1. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    2. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    3. 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.
    4. Peter van den Besselaar & Loet Leydesdorff, 2009. "Past performance, peer review and project selection: a case study in the social and behavioral sciences," Research Evaluation, Oxford University Press, vol. 18(4), pages 273-288, October.
    5. Richard Klavans & Kevin W. Boyack, 2006. "Quantitative evaluation of large maps of science," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(3), pages 475-499, September.
    6. David J. Hand & Heikki Mannila & Padhraic Smyth, 2001. "Principles of Data Mining," MIT Press Books, The MIT Press, edition 1, volume 1, number 026208290x, April.
    7. Primož Južnič & Stojan Pečlin & Matjaž Žaucer & Tilen Mandelj & Miro Pušnik & Franci Demšar, 2010. "Scientometric indicators: peer-review, bibliometric methods and conflict of interests," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(2), pages 429-441, November.
    8. David Adam, 2002. "The counting house," Nature, Nature, vol. 415(6873), pages 726-729, February.
    9. 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.
    10. Edgar Schiebel & Marianne Hörlesberger & Ivana Roche & Claire François & Dominique Besagni, 2010. "An advanced diffusion model to identify emergent research issues: the case of optoelectronic devices," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 765-781, June.
    11. Naoki Shibata & Yuya Kajikawa & Yoshiyuki Takeda & Katsumori Matsushima, 2009. "Comparative study on methods of detecting research fronts using different types of citation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(3), pages 571-580, March.
    12. 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.
    13. Smita Srinivas & Kimmo Viljamaa, 2008. "Emergence of Economic Institutions: Analysing the Third Role of Universities in Turku, Finland," Regional Studies, Taylor & Francis Journals, vol. 42(3), pages 323-341, April.
    14. Anton J. Nederhof, 2006. "Bibliometric monitoring of research performance in the Social Sciences and the Humanities: A Review," Scientometrics, Springer;Akadémiai Kiadó, vol. 66(1), pages 81-100, January.
    15. Byungun Yoon & Sungjoo Lee & Gwanghee Lee, 2010. "Development and application of a keyword-based knowledge map for effective R&D planning," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 803-820, December.
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    Cited by:

    1. Kevin W. Boyack & Caleb Smith & Richard Klavans, 2018. "Toward predicting research proposal success," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 449-461, February.
    2. Cristian Mejia & Yuya Kajikawa, 2018. "Using acknowledgement data to characterize funding organizations by the types of research sponsored: the case of robotics research," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 883-904, March.
    3. Balázs Győrffy & Andrea Magda Nagy & Péter Herman & Ádám Török, 2018. "Factors influencing the scientific performance of Momentum grant holders: an evaluation of the first 117 research groups," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 409-426, October.
    4. Li, Kai & Yan, Erjia, 2019. "Are NIH-funded publications fulfilling the proposed research? An examination of concept-matchedness between NIH research grants and their supported publications," Journal of Informetrics, Elsevier, vol. 13(1), pages 226-237.

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