A UK Specification for Trusted Research Environments

ObjectivesThe need for Trusted Research Environments (TREs) is clear. Several influential reports have highlighted that personal or sensitive data which have been collected for operational, commercial or governmental reasons need to be managed securely in an environment that encourages best practices. TREs are designed to enable only authorised projects and researchers access to sensitive data whilst minimising risk of data exposure. Yet the TRE landscape has grown organically over at least the last decade resulting in heterogeneous environments, making it harder for data to be discovered, shared and used for public benefit. A baseline specification for TREs is required. ApproachWe engaged with around 60 organisations covering government, industry, health and academia through regular, online, shared spaces or “Collaboration Cafés”. We also embedded the public voice within the project by having members of the public within the research team and developed a series of workshops to include and reflect their input to the architecture. The whole project was developed in the open to instil trustworthiness. ResultsThe SATRE project has produced a reference TRE architecture and implementation through significant engagement with the UK TRE community. This baseline specification for UK TREs includes a set of four pillars, 28 capabilities and 160 statements. Conclusions and ImplicationsAn open and transparent TRE specification and architecture for a wide range of stakeholders has been developed. TREs can now use the SATRE specification to evaluate their environments against a common baseline.

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Publication Details

Journal
International Journal for Population Data Science
Published
2024-09-10
DOI
https://doi.org/10.23889/ijpds.v9i5.2609
Citations
1
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
0.78
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article

A UK Specification for Trusted Research Environments

Jillian Beggs, Dermot Kerr, Ed Chalstrey, Antony Chuter et al.
1 citations
International Journal for Population Data Science
Research Data Management Practices
0.78
article

A UK Specification for Trusted Research Environments

Jillian Beggs, Dermot Kerr, Ed Chalstrey, Antony Chuter, James P. W. Robinson, Martin T. O'Reilly, Sonya Coleman, Christian Cole, Simon Li, Hari Sood, Matthew Craddock, Jim Madge, David Sarmiento-Perez, Tim Machin, Katie Oldfield, C. O’Donovan
article en
1 citations

Abstract

ObjectivesThe need for Trusted Research Environments (TREs) is clear. Several influential reports have highlighted that personal or sensitive data which have been collected for operational, commercial or governmental reasons need to be managed securely in an environment that encourages best practices. TREs are designed to enable only authorised projects and researchers access to sensitive data whilst minimising risk of data exposure. Yet the TRE landscape has grown organically over at least the last decade resulting in heterogeneous environments, making it harder for data to be discovered, shared and used for public benefit. A baseline specification for TREs is required. ApproachWe engaged with around 60 organisations covering government, industry, health and academia through regular, online, shared spaces or “Collaboration Cafés”. We also embedded the public voice within the project by having members of the public within the research team and developed a series of workshops to include and reflect their input to the architecture. The whole project was developed in the open to instil trustworthiness. ResultsThe SATRE project has produced a reference TRE architecture and implementation through significant engagement with the UK TRE community. This baseline specification for UK TREs includes a set of four pillars, 28 capabilities and 160 statements. Conclusions and ImplicationsAn open and transparent TRE specification and architecture for a wide range of stakeholders has been developed. TREs can now use the SATRE specification to evaluate their environments against a common baseline.

International Journal for Population Data ScienceVol. 9(5)
University of Ulster (GB), University of Dundee (GB), Economie Publique (FR), The Alan Turing Institute (GB), Health Data Research UK (GB), University College London (GB)
Openalex Percentile: Top 21%
Research Data Management Practices
0.78
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