Abstract
In the current era of global challenges, the United Nations’ Sustainable Development Goals (SDGs) serve as a universal call to action, addressing critical issues such as poverty, inequality, climate change, environmental degradation, and peace and justice. The alignment of scientific research with these goals is pivotal for measuring and enhancing the impact of academia on these global objectives.
The Swisstext 2024 Shared Task proposed by members of the Departments of Computational Linguistics and Informatics at the University of Zurich targets an innovative and significant undertaking: the automatic classification of scientific abstracts (in English) with respect to SDGs and their specific targets. This task not only aligns with the increasing importance of interdisciplinary research towards sustainable development but also represents a crucial step in integrating advanced Natural Language Processing (NLP) within the realm of sustainability research. By automating the classification process, this Shared Task aims to facilitate the identification and analysis of research towards the SDGs, thereby fostering a targeted and efficient approach in addressing the world’s most pressing challenges.
This Shared Task evolved in the context of the UZH Digital Society Initiative project “SDG Research Scout” financed by the Digitalization Initiative of the Zurich Higher Education Institutions (DIZH).
Clematide, Simon