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Mapping the sustainable development goals (SDGs) in science, technology and innovation: application of machine learning in SDG-oriented artefact detection

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Listed:
  • Arash Hajikhani

    (VTT Technical Research Centre of Finland)

  • Arho Suominen

    (VTT Technical Research Centre of Finland
    Tampere University)

Abstract

The sustainable development goals (SDGs) are a blueprint for achieving a better and more sustainable future for all by defining priorities and aspirations for 2030. This paper attempts to expand on the United Nations SDGs definition by leveraging the interrelationship between science and technology. We utilize SDG classification of scientific publications to compile a machine learning (ML) model to classify the SDG relevancy in patent documents, used as a proxy of technology development. The ML model was used to classify a sample of patent families registered in the European Patent Office (EPO). The analysis revealed the extent to which SDGs were addressed in patents. We also performed a case study to identify the offered extension of ML model detection regarding the SDG orientation of patents. In response to global goals and sustainable development initiatives, the findings can advance the identification challenges of science and technology artefacts. Furthermore, we offer input towards the alignment of R&D efforts and patenting strategies as well as measurement and management of their contribution to the realization of SDGs.

Suggested Citation

  • Arash Hajikhani & Arho Suominen, 2022. "Mapping the sustainable development goals (SDGs) in science, technology and innovation: application of machine learning in SDG-oriented artefact detection," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6661-6693, November.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:11:d:10.1007_s11192-022-04358-x
    DOI: 10.1007/s11192-022-04358-x
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    3. Emanuela Bran & Răzvan Rughiniș & Dinu Țurcanu & Alexandru Radovici, 2024. "AI Leads, Cybersecurity Follows: Unveiling Research Priorities in Sustainable Development Goal-Relevant Technologies across Nations," Sustainability, MDPI, vol. 16(20), pages 1-31, October.
    4. Percia David, Dimitri & Maréchal, Loïc & Lacube, William & Gillard, Sébastien & Tsesmelis, Michael & Maillart, Thomas & Mermoud, Alain, 2023. "Measuring security development in information technologies: A scientometric framework using arXiv e-prints," Technological Forecasting and Social Change, Elsevier, vol. 188(C).

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