We found 225 results
Climate and hydrology data shines a light on the impacts of environmental change on UK ecosystems
Reuse of data made available by the EDS has enabled researchers to build tools to better understand the impacts of climate change on a national scale.
Data Citation
Gain credit for the data you generate. Find out how you can make your data citable and increase the impact of your research.
Accessible marine data supports the sustainable management of the marine environment
Marine data is increasingly used to support the development of tools and policies which generate societal and economic benefits for the marine sector. The EDS provides users with a rich source of accessible marine data.
Geological data supports the management of environmental risks from pollution in England’s water environments
Open access to geological data enables Environment Agency staff to develop an understanding of how water flows in the subsurface environment, helping to support their statutory function to protect England’s waters and associated environments from pollution risk.
Your current and future needs for AI - Review of UK Digital Research Infrastructure for AI
You are invited to contribute to a short online survey about your current and future needs in relation to compute, data access and skills for AI research and innovation in the UK.
Successful webinar series draws to a close
The NERC Environmental Data Service (EDS) has recently completed a successful webinar series, run in collaboration with the NERC Constructing a Digital Environment program.
An insight to the Antarctic: improving data access via the Polar Airborne Geophysics Data Portal
As the coldest, driest, windiest and fastest changing environment on Earth, Antarctica is a fascinating continent that still hides its secrets. For the last 60 years, scientists have explored and strived to better understand the past, present and future of the Antarctic Ice Sheet but also its geological structure.
Machine learning algorithm enables automatic characterisation of rock properties
International researchers use digital photographs of geological core from the NGDC to demonstrate the potential of a machine learning algorithm to automatically label core material and obtain geological insights, potentially creating a cost-effective alternative to in-person observations for some applications.