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

Antonio Perianes-Rodríguez (), Carlos Olmeda-Gómez (), Natalia R. Delbianco () and Maria Cláudia Cabrini Grácio ()
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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

Scientometrics, 2024, vol. 129, issue 10, No 3, 5868 pages

Abstract: 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.

Keywords: Public funding; Linked open data; Co-funding networks (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11192-024-04975-8

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