Mapping the Nexus of Biodiversity, Climate Change, Human Society and Health Using Large Language Models

Background

The loss of biodiversity and the threats to human health and societies due to pollution, habitat damage, and climate change require urgent solutions. However, the large amount of fragmented information across millions of scientific publications determines a lack of understanding of the complex interconnections between these issues that hinders progress.

Aim

The project aims at creating a large knowledge graph that links between climate change, biodiversity, human health and social sustainability and that can be used to pinpoint potential mitigation strategies.

Methods

The project is based on the implementation of a text mining pipeline based on large language models that can process all accessible scientific literature on biodiversity, climate change, medicine, and social sustainability. Further computational analysis will allow to identify strategies to mitigate effect of major drivers on the system.

Significance

WASP-HS perspective: the knowledge graph will help in clarifying sustainability-related challenges.

DDLS perspective: The project will develop a method to make text mining technologies accessible to a much larger audience of life science, social science and humanities researchers and even non-academics and will establish new knowledge about the link between biodiversity, social science and humanities research.