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Public funding accountability: a linked open data-based methodology for analysing the scientific productivity and influence of funded projects

Author

Listed:
  • Antonio Perianes-Rodríguez

    (Universidad Carlos III)

  • Carlos Olmeda-Gómez

    (Universidad Carlos III)

  • Natalia R. Delbianco

    (Universidade Estadual Paulista Júlio de Mesquita Filho)

  • Maria Cláudia Cabrini Grácio

    (Universidade Estadual Paulista Júlio de Mesquita Filho)

Abstract

Although funding acknowledgements (FAs) have been around for nearly three decades, there are not yet enough theoretical and practical studies of them to enable FAs to be considered a consolidated area of research. Fortunately, newly published findings and promising data sources presented in recent years have helped better our understanding of the process of scientific creation and communication and provide evidence of the importance of FAs. This paper seeks to help demonstrate the crucial role FAs play in evaluating research funding’s performance. A methodology based on the use of linked open metadata from diverse sources is presented for this purpose. The methodology highlights the important work analysts do to increase the accuracy, solidity, and diversity of the results of FA-based quantitative studies by gathering and analysing the data furnished by funding organisations. Lastly, the projects funded by the Spanish National Science and Research Agency from 2008 to 2020 are evaluated to verify the method’s usefulness, robustness, and reproducibility. Also, a new unit of analysis is introduced, funders, to create a new type of co-occurrence network: co-funding. In conclusion, funding agencies’ experts and analysts will find that this methodology gives them a valuable instrument for boosting the quality and efficacy of their activities, complying with transparency and accountability requirements, and quantifying the scope of funding results.

Suggested Citation

  • Antonio Perianes-Rodríguez & Carlos Olmeda-Gómez & Natalia R. Delbianco & Maria Cláudia Cabrini Grácio, 2024. "Public funding accountability: a linked open data-based methodology for analysing the scientific productivity and influence of funded projects," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(10), pages 5841-5868, October.
  • Handle: RePEc:spr:scient:v:129:y:2024:i:10:d:10.1007_s11192-024-04975-8
    DOI: 10.1007/s11192-024-04975-8
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    References listed on IDEAS

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    1. Nicola Grassano & Daniele Rotolo & Joshua Hutton & Frédérique Lang & Michael M. Hopkins, 2017. "Funding Data from Publication Acknowledgments: Coverage, Uses, and Limitations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 999-1017, April.
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    5. Adèle Paul-Hus & Nadine Desrochers & Rodrigo Costas, 2016. "Characterization, description, and considerations for the use of funding acknowledgement data in Web of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 167-182, July.
    6. Belén Álvarez-Bornstein & Fernanda Morillo & María Bordons, 2017. "Funding acknowledgments in the Web of Science: completeness and accuracy of collected data," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1793-1812, September.
    7. Linda Butler, 2001. "Revisiting bibliometric issues using new empirical data," Research Evaluation, Oxford University Press, vol. 10(1), pages 59-65, April.
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    9. Perianes-Rodriguez, Antonio & Waltman, Ludo & van Eck, Nees Jan, 2016. "Constructing bibliometric networks: A comparison between full and fractional counting," Journal of Informetrics, Elsevier, vol. 10(4), pages 1178-1195.
    10. Álvarez-Bornstein, Belén & Bordons, María, 2021. "Is funding related to higher research impact? Exploring its relationship and the mediating role of collaboration in several disciplines," Journal of Informetrics, Elsevier, vol. 15(1).
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