First phase of the programme
The first phase of the Future Data Services programme reviewed ESRC’s data service infrastructure investments to ensure they meet the challenges of the rapidly evolving technological landscape.
Following extensive consultation with researchers, data professionals, data custodians and technologists, the report sets out a series of actionable recommendations that will deliver a vision for a seamless, connected, research-centred data service landscape that harnessed new technologies to maximise data usage for public good.
The report sets out the actions needed to deliver improved data services for the research community, while enabling the most cutting-edge social science and economic research to thrive.
Read ESRC’s ‘Fixing the Data Pipeline’ report.
ESRC was supported by Professor Felix Ritchie and Dr Elizabeth Green from University of West of England. See ESRC Future Data Services technical papers.
Future data services: pilots to enhance data services for the future
ESRC invested £3 million (2024-2025 and 2025-2026) to fund 9 exciting pilot projects for 12 months to support ESRC’s Future Data Services strategic review of data services infrastructure.
These pilots were tasked to develop and trial new infrastructures to help ESRC deliver:
- data discovery using machine learning or other AI technologies
- increased skills capacity for data service professionals
The projects also received funding through the UKRI Digital Research Infrastructure programme, to demonstrate the potential to substantially enhance and transform the data service landscape.
The funded projects were:
Connect 4: The project looked to align policies across the UK’s Trusted Research Environments to streamline projects that require data from different jurisdictions.
See the Connect 4 project website
CORDIAL-AI: The project focussed on developing a natural language model to improve the discovery of census data.
See the Cordial-AI UKDS Blog
Data Discovery Made Easy: The project applied machine learning to help researchers retrieve statistics, by allowing them to ask in plain English.
Find further details on the funded project here
EDASIDA: The project delivered bespoke synthetic datasets to support teaching and enhance the discoverability of datasets.
See the EDASIDA website
Enhancing Data Services: The project developed a Comprehensive Training Program for Trusted Research Environment Staff in Social Science Data.
Find further details on the funded project here
Harmony: The project used AI to provide faster and easier ways for researchers to discover and use existing data.
See the Harmony website
Metacurate-ML: The project fine‑tuned pre‑trained language models to automate the extraction, comparison, and classification of survey metadata, reducing reliance on unsustainable manual processes.
See the Metacurate-ML website
ODYSSEY: The project developed a data services curriculum to help optimise Data Professional Success by addressing recruitment and skills.
See the ODYSSEY website
Talk data to me!: The project developed ‘chat box’ search to help researchers find the data they need.
Find further details on the funded project here