Projects of the Data Research, Access and Governance Network (DRAGoN)
An overview of our current and completed research projects since DRAGoN was formed in June 2020. In addition, we also provide regular training and consultancy.
Current projects
Brunel Centre
Project lead: Damian Whittard
Project team:
Partner organisations:
- University of Bath (Lead)
- Futures West
Funding: Research England
Project duration: April 2025-March 2030
Project summary: This is a five-year project to develop regional economic analytical capability in the South West, with a strong emphasis on applied policy-oriented analysis, novel uses of data, and working in a regional context.
Community Of Interest in Information Governance
Project lead: Professor Felix Ritchie
Partner organisations:
- University of Sheffield (Lead)
- eDRIS (Electronic Data Research and Innovation Service)
- The Francis Crick Institute
Funding: MRC
Project duration: February 2025-March 2026
Project summary: This is an Interest Group aiming to provide a forum for the discussion of best practice in information governance.
SDC-REBOOT: Automated output checking for TREs including evaluation of AI model outputs
Project lead: Professor Jim Smith
Project team:
Funding: MRC
Project duration:
- February 2025-March 2026
- January 2023-December 2024
Project summary:
The DRAGoN team were funded (with repeat funding) to run a network exploring the issues of output checking and the implementation of SACRO (Semi-Automated Checking of Research Outputs) and SACRO-ML.
Optimising data professional success: Identifying skills, career trajectories, and training requirements for enhanced data service delivery
Project lead: Elizabeth Green
Project team:
Partner organisations:
- University of Essex
- Research Data Scotland
Funding: Economic and Social Research Council (ESRC)
Project duration: June 2024-June 2025
Project summary: Staff in data services fall between the stools of academic or administrative staff. This pilot project from Future Data Services is developing career profiles, job description, development curricula and contextual material to help UK data services offer clear career opportunities to staff.
Researcher passports
Project team:
Partner organisation: Health Data Research UK (Lead)
Funding: MRC
Project duration: January 2024-March 2025
Project summary: This project aims to develop a working prototype of a researcher/organisation registry. The ambition of the registry is to provide a single point of validation for all users of secure research facilities in the UK.
Wage and Employment Dynamics (WED) - Phase 4
Project team:
Partner organisations:
- City University of London (Lead)
- University College London (UCL)
- University of Stirling
Funding: ESRC
Project duration: 2024-2025
Project summary: The fourth phase of the Wage and Employment Dynamics (WED) project links ASHE (Annual Survey of Hours and Earnings) to the Census 2021, integrated with the ASHE-Census 2011 link of WED1 enabling a doubly-longitudinal dataset to be created and analysed.
ADR UK Research Fellowship
Project lead: Damian Whittard
Funding: ESRC
Project duration: June 2023-June 2025
Project summary:
This is a two-year fellowship to analyse the distribution and impact of 'green jobs' in the UK.
Output:
- Whittard, D; Bradley, P; Phan, V; Ritchie, F (2024). Working towards a greener Britain: Who, where and for whose benefit? ESCoE Discussion Paper 2024-13.
Data governance for health research in low- and middle-income countries
Project lead: Professor Julie Mytton
Project team:
Partner organisations:
- Kathmandhu Medical College
- University of Bristol
- George Institute for Global Health UK
Funding: NIHR
Project duration: March 2022 to present
Project summary:
This project has three aims:
- explore how data governance models developed in the UK can be applied to a large public health project in Nepal
- explore how data governance can be usefully taught in LMIC health projects
- identify the state of data governance in LMICs
Output:
- Ferrer Breda, P; Green, E; Kendal, C; Ritchie, F (2023). Final conference report: Research data governance in low- and middle-income countries.
Qualidata Use and Confidential Knowledge (QUACK)
Project lead: Elizabeth Green
Project team: Professor Felix Ritchie
Partner organisations:
- ICPSR
- University of Michigan
- GESIS
- University of Mannheim
- Heidelberg University
- UK Data Archive
Funding: UWE Bristol internal funding
Completion date: December 2022
Project summary: When research data consists of personal identifiable information, there is a risk that publishing analyses will inadvertently release confidential information about data subjects. Quantitative data has well-established practices to manage this risk. As well as statistical theory, there are widely used practical guidelines and teaching materials. Research in statistical disclosure control (SDC) was mostly sponsored by national statistics institutes (NSIs), which provided both the motivation and the market for the research.
In contrast, there are almost no guidelines for qualitative data. Researchers working with qualitative data must trust to their own judgment and experience, often without any training or mentoring. As well as increasing the risk of confidentiality breach, this is inefficient, as each generation must learn the same lessons for itself.
One reason for this is the sheer range of qualitative data: ethnographic studies, social media analyses, interviews, videos, clinical case studies, court records. Guidelines in one field may be meaningless in another. A subsidiary reason is that there is no equivalent of the NSI network to sponsor qualitative data research. The Qualidata Use and Confidential Knowledge (QUACK) project seeks to scope and develop both principles and guidelines for working with disclosive qualitative data.
Completed projects
Future Data Services Strategic Fellowships
Project leads:
Funding: Economic and Social Research Council (ESRC)
Project duration: June 2022 to August 2024
Project summary: Felix and Lizzie were appointed Strategic Fellows by the ESRC support the two-year review into the current state of and future ambitions for data services in the UK.
St Paul's Carnival Economic Impact Assessment
Project lead: Damian Whittard
Funding: St Paul's Carnival
Completion date: 2024
Project summary: The DRAGoN team provided an Economic Impact Assessment to help shape Bristol Carnival's future plans.
Wage and Employment Dynamics (WED) - Phases 2 and 3
Project lead: Damian Whittard
Project team:
Partner organisations:
- University College London (UCL)
- Bayes Business School
- University of Reading
- NIESR
Funding: ESRC
Project duration: July 2023 (Phase 2) and March 2024 (Phase 3)
Project summary: The Wage and Employment Dynamics (WED) project’s primary aim is to develop a sustainable, documented ‘wage and employment spine’ with the potential to fundamentally transform UK research and policy analysis across a vast range of topics. Alongside the creation of data infrastructure, the project will also generate research findings of direct interest to policy makers. Public benefit will be maximised through the provision of high-quality metadata and training for users.
Key outputs:
- Derrick, B; Green, E; Ritchie, F; Smith, J; White, P. (2024) The inadvertently revealing statistic: A systemic gap in statistical training? Significance, volume 21, Issue 1, p24–27,
- Derrick, B; Green, E; Ritchie, F; White, P. (2023) Towards a comprehensive theory and practice of output SDC. Conference paper: UNECE/Eurostat Expert Group on Statistical Data Confidentiality
- Derrick, B; Green, E; Ritchie, F; White, P. (2022) Risk of disclosure when reporting commonly used univariate statistics. Conference paper: Privacy in Statistical Databases.
- Derrick, B; Green, E; Kember, K; Ritchie, F; White, P. (2022) Safety in numbers: Minimum thresholding, Maximum bounds and Little White Lies: The case of the mean and standard deviation. Conference Paper: Scottish Economic Society.
- Derrick, B; Green, E; Ritchie, F; White, P. (2022) Disclosure risks in odds ratios and logistic regression. Conference paper: Scottish Economic Society Annual Conference 2022: Special session 'Protecting confidentiality in social science research outputs'.
Guidelines and Resources for Artificial Intelligence Model Access from Trusted Research Environments (GRAIMatter)
Project leads:
- Emily Jefferson (University of Dundee)
- Professor Jim Smith
Project team:
- Professor Jim Smith
- Professor Felix Ritchie
- Dr Richard Preen
- Dr Francesco Tava
- Andrew McCarthy
Partner organisations:
- University of Dundee (lead)
- Swansea University
- University of Edinburgh
- University of Aberdeen
- Durham University
Funding: DARE/Health Date Research UK
Completion date: August 2022
Project summary: Researchers from the College of Arts, Technology and Environment at UWE Bristol are part of a consortium awarded £390K by the UKRI as funding for GRAIMatter (Guidelines and Resources for Artificial Intelligence Model Access from Trusted Research Environments) under a scheme run by DARE-UK which is developing a national research data infrastructure for the UK.
This project will investigate what technical, legal and ethical frameworks would enable Trusted Research Environments to safely manage the risk to individual’s privacy when allowing the release of AI-based models learned from the confidential data they host, such as medical records. Such models could have significant value for the public good - for example, diagnosing disease risk.
Professor Jim Smith (Computer Science Research Centre) is leading on technical AI-related aspects with Professor Felix Ritchie providing expertise on procedural/researcher-focused aspects and Dr Francesco Tava (College of Health, Science and Society) on ethical issues.
This project ties into the interdisciplinary DRAGoN which involves a number of College of Arts, Technology and Environment researchers, and which was awarded 100K investment from UWE Bristol's Expanding Research Excellence strategy.
Key outputs:
- Ritchie, F; Tilbrook, A; Cole, C; Jefferson, E; Krueger, S; Mansouri-Benssassi, E; Rogers, S; Smith, J. (2023). Machine learning models in trusted research environments - Understanding operational risks. International Journal of Population Data Science, vol 8, issue 1.
- Mansouri-Benssassi, E; Rogers, S; Reel, S; Malone, M; Smith, J; Ritchie, F; Jefferson, E. (2023). Disclosure control of machine learning models from trusted research environments (TRE): New challenges and opportunities. Heliyon, vol 9 issue 4.
Semi-Automated Checking of Researcher Outputs (SACRO)
Project lead: Professor Jim Smith
Project team:
Partner organisations:
- University of Oxford
- University of Edinburgh
- Swansea University
- Research Data Scotland
Funding: MRC
Project duration: February 2023-October 2023
Project summary: This project took the the proof-of-concept, ACRO, developed for Eurostat, and turned it into a generalised semi-automated output checking model, SACRO, designed to run across multiple environments. It is currently in operational testing across the UK and other countries.
As part of this, the DRAGoN team fundamentally redesigned the theoretical basis for output checking and developed the 'statbarns' concept. The team also led a group building on and extending the GRAIMATTER (Guidelines and Resources for Artificial Intelligence Model Access from Trusted Research Environments) research to provide guidance on producing safety checks for AI models.
Output:
- Green, Elizabeth; Ritchie, Felix; White, Paul (2024). The statbarn: A new model for output statistical disclosure control. Privacy in Statistical Databases: International Conference, PSD 2024, Antibes Juan-les-Pins, France, September 25–27, 2024, Proceedings.
Review of statistical disclosure control options for output tables
Project lead: Elizabeth Green
Project team: Professor Felix Ritchie
Funding: HESA
Project duration: July 2021-March 2022
Output:
- Green, E; Ritchie, F (2021). Statistical disclosure control for HESA: Part 1: Review of SDC theory.
Wage and Employment Dynamics (WED) - Phase 1
Project lead: Professor Felix Ritchie
Project team:
Partner organisations:
- University College London (UCL)
- Bayes Business School
- University of Reading
- NIESR
Funding: ESRC
Project duration: October 2019-July 2022 (Phase 1)
EREOSDC (Outputs Statistical Disclosure Control)
Project lead: Professor Felix Ritchie
Project team:
- Dr Ben Derrick
- Dr Laura Fogg-Rogers
- Elizabeth Green
- Dr Laura Hobbs
- Professor Jim Smith
- Professor Paul White
Funding: UWE Bristol internal funding
Completion date: December 2022
Project summary: Data is everywhere. Increasingly the data used for policy and analysis is confidential and needs to be protected. Analytical uses of data are moving to ‘trusted research environments’ (TREs), where users have great freedom to analyse data, but what they produce gets checked before release into the open to minimise confidentiality risks. UWE Bristol is a leader in telling people how to do this, but we are currently fragmented and running to stand still. This project is designed to allow us to
- strengthen the theoretical foundations of what we do, including public engagement
- develop re-usable resources for use by us (and others, with appropriate recognition
- cement UWE Bristol’s reputation as a world leader in data governance
- integrate and develop IT solutions UWE Bristol staff have built as pilots
There are four strands to output checking:
- Checking of statistical outputs: UWE Bristol has the field almost to itself and is the leader
- Checking of qualitative research outputs: an almost completely unresearched field
- Checking of Artificial Intelligence (AI) outputs and machine learning models: a completely unresearched field
- Statistical Disclosure Control (SDC) for national statistics; a well-established and very competitive field
Advanced ethical models of data governance
Project lead: Dr Francesco Tava
Project team: Elizabeth Green
Funding: UWE Bristol internal funding
Project duration: September 2020-August 2021
Externalities (wider costs and benefits) of data use (subcontractor)
Project lead: Damian Whittard
Project team: Professor Felix Ritchie
Partner organisation: Belmana Consulting (lead)
Funding: DCMS
Project duration: January 2021-March 2021
Output:
- Vaze, P; Ioramshvili, C; Whittard, D; Ritchie, F. (2022). Data use externatilies: Report to department for digital, culture, media and sport by Belmana with the University of the West of England.
Process evaluation and R&D and innovation in data access and governance
Project lead: Damian Whittard
Project team:
Funding: Open Data Institute
Project duration: October 2020-March 2021
Output:
- Alves, K; Tava, F; Whittard, D; Green, E; Beata Kreft, M; Ritchie, F. (2021). Process and economic evaluation of the ODI R&D programme: Final report.
Autumn school in data governance for low and middle-income countries
Project lead: Professor Julie Mytton
Project team: Elizabeth Green, Dr Francesco Tava
Funder: NIHR
Project duration: October 2020-December 2020
The value of data governance
Project lead: Damian Whittard
Project team: Professor Felix Ritchie
Funding: CABI
Project duration: July 2019-December 2020
Automated disclosure control for research outputs
Project lead: Professor Felix Ritchie
Project team:
Funding: Eurostat
Project duration: January 2020-December 2020
Project summary: This project analysed whether and how output checking could be automated, and developed a proof-of-concept, ACRO, a working prototype for Stata users.
Output:
- Green, E; Ritchie, F; Smith, J. (2021) Automatic Checking of Research Outputs (ACRO): A tool for dynamic disclosure checks. ESS Statistical Working Papers, vol 2021.
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