The interrelation of sustainable development goals in publications and patents: A machine learning approach

The Sustainable Development Goals (SDGs) are the blueprint for achieving a better and more sustainable future for all by defining priorities and aspirations for 2030. In this paper, the attempt was to expand SDGs' definition by performing a comprehensive literature review. Furthermore, the descriptions of SDGs were utilized to compile a Machine Learning (ML) model so to automate the detection of SDG relevancy in other types of artefacts. The model was employed for identifying the SDG relevancy of patents as well-known proxies for innovation. The ML model was then used to classify a sample of patent families registered in the European Patent Office (EPO). The analysis revealed the extend to which SDGs were addressed in patents and the interrelations between SDG definitions. The findings guide how to align patenting strategies as well as measurement and management of their contribution to the realization of the SDGs when it comes to Intellectual Property (IP) strategies.