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Outputs (11)

Using the five safes to structure economic evaluations of data governance (2024)
Journal Article
Ritchie, F., & Whittard, D. (2024). Using the five safes to structure economic evaluations of data governance. Data & Policy, 6, Article e16

As the world has become more digitally-dependent, questions of data governance such as ethics, institutional arrangements and statistical protection measures have increased in significance. Understanding the economic contribution of investments in da... Read More about Using the five safes to structure economic evaluations of data governance.

Working towards a greener Britain: Who, where and for whose benefit? (2024)
Conference Proceeding
Whittard, D., Bradley, P., Phan, V., & Ritchie, F. (in press). Working towards a greener Britain: Who, where and for whose benefit?.

Given the urgency of the transition to net-zero, there is a need for a robust evidence base to support green policy interventions. Intelligence in relation to green jobs, however, is partial and fragmented, partially due to the lack of an internation... Read More about Working towards a greener Britain: Who, where and for whose benefit?.

The inadvertently revealing statistic: A systemic gap in statistical training? (2024)
Journal Article
Derrick, B., Green, E., Ritchie, F., Smith, J., & White, P. (2024). The inadvertently revealing statistic: A systemic gap in statistical training?. Significance, 21(1), 24-27. https://doi.org/10.1093/jrssig/qmae009

While concerns around data privacy are well-known, there's a lack of awareness and training when it comes to the confidentiality risk of published statistics, argue Ben Derrick, Elizabeth Green, Felix Ritchie, Jim Smith, Paul White

Machine learning models in trusted research environments - Understanding operational risks (2023)
Journal Article
Ritchie, F., Tilbrook, A., Cole, C., Jefferson, E., Krueger, S., Mansouri-Benssassi, E., …Smith, J. (2023). Machine learning models in trusted research environments - Understanding operational risks. International Journal of Population Data Science, 8(1), Article 2165. https://doi.org/10.23889/ijpds.v8i1.2165

IntroductionTrusted research environments (TREs) provide secure access to very sensitive data for research. All TREs operate manual checks on outputs to ensure there is no residual disclosure risk. Machine learning (ML) models require very large amou... Read More about Machine learning models in trusted research environments - Understanding operational risks.

The present and future of the Five Safes framework (2023)
Journal Article
Green, E., & Ritchie, F. (2023). The present and future of the Five Safes framework. Journal of Privacy and Confidentiality, 13(2), https://doi.org/10.29012/jpc.831

The Five Safes has become the default framework for confidential data governance across multiple sectors and countries. Since its inception in 2003, the approach has influenced data management in many ways, particularly in the public sector. As it ha... Read More about The present and future of the Five Safes framework.

SACRO guide to statistical output checking (2023)
Other
Ritchie, F., Green, E., Smith, J., Tilbrook, A., & White, P. (2023). SACRO guide to statistical output checking. [web]

This guide for output SDC is the first report from the SACRO project. It covers, theory of output SDC, including the new statbarns model, practicalities, operational considerations, and FAQs for output checking teams.

Research data governance in low-and middle-income countries (2023)
Report
Ferrer Breda, P., Green, E., Kendal, C., & Ritchie, F. (2023). Research data governance in low-and middle-income countries. Bristol: UWE

Research and policy development on the governance of confidential research data is dominated by the work of academics and government agencies based in high-income countries (HICs). This leaves three quarters of the world’s population faced with a cor... Read More about Research data governance in low-and middle-income countries.

Disclosure control issues in complex medical data (2023)
Presentation / Conference
Green, E., Ritchie, F., Smith, J., Western, D., & White, P. (2023, September). Disclosure control issues in complex medical data. Paper presented at UNECE/Eurostat Expert Group on Statisticial Data Confidentiality, Wiesbaden

The covid19 pandemic assisted the acceleration of routine access to medical records for research. In the UK platforms including OpenSafely and NHSDigital, alongside emerging hospital trust based Trusted Research Environments (TREs), demonstrate the u... Read More about Disclosure control issues in complex medical data.

Towards a comprehensive theory and practice of output SDC (2023)
Presentation / Conference
Derrick, B., Green, E., Ritchie, F., & White, P. (2023, September). Towards a comprehensive theory and practice of output SDC. Paper presented at UNECE/Eurostat Expert Group on Statisticial Data Confidentiality, Wiesbaden

In 2000, the statistical disclosure control of outputs (OSDC) was largely limited to models of table protection developed by and intended for national statistical institutes (NSIs), as a particular branch of general SDC theory. However, in this centu... Read More about Towards a comprehensive theory and practice of output SDC.

Research data governance in low- and middle-income countries (2023)
Presentation / Conference
Ferrer Breda, P., Green, E., & Ritchie, F. (2023, September). Research data governance in low- and middle-income countries. Paper presented at UNECE/Eurostat Expert Group on Statisticial Data Confidentiality, Wiesbaden

Research and policy development on the governance of confidential research data is dominated by the work of academics and government agencies based in high-income countries (HICs). This leaves three quarters of the world’s population faced with a cor... Read More about Research data governance in low- and middle-income countries.