Building a new national facility to connect the UK’s environmental data holdings with end-users across multiple sectors: a case study on linking air quality and health data

Data driven tools are emerging across all domains, largely held under the banner of AI. This includes developments at the interface between academic research and policy implementation. Data science, as a much broader discipline, also requires us to consider the supporting ecosystem of infrastructure and principles that underpin data access and sustainability. The research community is now constantly demonstrating more potential applications within air quality research, from molecular through to global scales. Likewise, the gap between air quality and health research is closing through demonstrable applications of data science approaches.

Alongside this, the UKs Natural Environment Research Council (NERC) Digital Solutions programme is funding a new national facility to connect environmental data with users in the public and private sector, covering health and climate use cases. Taking the unusual approach of asking what end-users may need, in this presentation we present outcomes from workshops held across the UK. We find remaining challenges centre around access and sustainable delivery and discuss the cultural dependencies on the research community. With a focus around the rapidly evolving pace of AI, we present several overarching developments including work on using Large Language Models (LLMs) to improve search and discovery of air quality data.