Mapping the sustainable development goals (SDGs) in science, technology and innovation: application of machine learning in SDG-oriented artefact detection
Year of publication
2022
Authors
Hajikhani, Arash; Suominen, Arho
Abstract
<p>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.</p>
Show moreOrganizations and authors
Tampere University
Suominen Arho
Publication type
Publication format
Article
Parent publication type
Journal
Article type
Original article
Audience
ScientificPeer-reviewed
Peer-ReviewedMINEDU's publication type classification code
A1 Journal article (refereed), original researchPublication channel information
Journal
Volume
127
Issue
11
Pages
6661–6693
ISSN
Publication forum
Publication forum level
2
Open access
Open access in the publisher’s service
Yes
Open access of publication channel
Partially open publication channel
Self-archived
Yes
Other information
Fields of science
Computer and information sciences; Business and management; Sociology
Keywords
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Internationality of the publisher
International
Language
English
International co-publication
No
Co-publication with a company
No
DOI
10.1007/s11192-022-04358-x
The publication is included in the Ministry of Education and Culture’s Publication data collection
Yes