Skip to main content
Royal Town Planning Institute home

Project: Beyond Data Portals: AI, Environmental Data, and the NERC Digital Solutions Hub

View other projects under this theme

Research published 2026

Lead researchers and institutions:

Prof Richard Kingston, University of Manchester *

* RTPI-accredited planning school

 

Funders

Natural Environment Research Council (NERC)

 

NOTE:  Findings and recommendations reflect the views of the researchers at the time of writing and are not necessarily the views of the RTPI

 

Key takeaways:

  • The Natural Environment Research Council (NERC) Digital Solutions Hub (DSH) rethinks how environmental data are accessed, integrated, and applied to real world problems in diverse use cases across disciplines.
  • The DSH enables fast, evidence-based analysis of environmental risks and opportunities that are relevant to housing delivery and planning.
  • By enabling easier access to environmental data the DSH supports more transparent, timely, and policy-relevant decision-making.
  • Constraining your search to your own data is key: “quality in, quality out”. The DSH was designed to work only with trusted NERC data and peer-reviewed scientific papers linked to it.

 

Summary

The Natural Environment Research Council (NERC) Digital Solutions Hub (DSH) was developed to address the persistent gap between NERC datasets and their use in decision-making, policy, and innovation. NERC’s Environmental Data Service and related infrastructures give access to vast, world-leading, high-quality environmental data assets, yet these resources are hard to discover, interpret, and combine for non-specialist users - even experienced researchers find them time-consuming to use.

NERC wanted their data to be more accessible to non-academics (though academics will find it very useful too). The key target groups were people working at all levels in government who are not GIS experts, such as:

  • environmental health officers wanting to locate all properties at risk of flooding;
  • planners assessing sites for environmental and climate risk.

The data on its own can’t solve societal challenges or deliver government missions – and people often don’t know what to do with it. So the researchers developed use cases to show what is possible. The researchers began by running workshops across UK nations and regions to find out what people needed, to ensure that what they built would be useful. A self-selecting group of 100 people from 40 organisations (e.g. the NHS) took part.

Data analysts and other researchers were spending 80% of their time wrangling with data - it might take them all day to produce a map from spatial data layers - and just 20% on doing something useful with the results. This project enables a huge reduction in the time spent wrangling. You can put in a query and the map you need is generated for you.

The researchers used AI to lower barriers to data discovery and use. Central to the approach is an AI-driven large language model catalogue that enables natural language searches across heterogeneous environmental datasets, metadata, and documentation.

Rather than replacing existing data infrastructures, the system sits alongside them, acting as an intelligent interface that supports exploration, explanation, and synthesis while remaining grounded in authoritative sources.

The team used advanced AI techniques to help people search and understand NERC’s vast environmental data collections. It uses Retrieval Augmented Generation (RAG), where AI first finds the most relevant information directly from NERC’s own databases and publications, and then generates an answer. This ensures more accuracy, transparency and resistance to “hallucinations” or invented information that can occur with general-purpose AI systems.

Until recently NERC’s data has been primarily used by climate scientists, but there are many other potential users, e.g. those who decide where new towns will be built. Currently the new town locations are being chosen based mainly on economic criteria, but NERC hold data that can be used to bring in environmental considerations around future climate change, heat and flood risk. The researchers’ housing use case helps understand the problems that arise when environmental data are not considered.

Funding options are being sought to enable the hub to continue to run beyond the initial 5 year period. Some use cases, such as housing and the UPRN service, will continue beyond 2026.

The researchers suggest making the DSH tool and the data it allows access to available as open access for government departments and other public sector organisations, while charging private companies to use it to sustain its running costs.

Published outputs 

This research project is highly inter-disciplinary. Outputs have not been published in planning journals to date but in journals of other disciplines e.g. medicine, computing.

 

Discover more
View all our research themes
View other digital planning projects