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Considerations for the provision of synthetic forms of secure data: An ADR UK Synthetic Data Working Group Guidance paper

Year: 2025

Type: article

Abstract: This guidance document, developed by the ADR UK Synthetic Data Working Group, outlines key considerations for data owners and providers who are planning to generate and share synthetic forms of secure tabular data. It is intended to support the responsible and effective use of synthetic data for purposes such as research planning, tool development, training and collaboration, particularly within Trusted Research Environments (TREs).The guidance provided in this paper intentionally relates to the provision of synthetic data with low disclosure risk. This is typically ‘lower fidelity’ synthetic data in tabular form that replicates the structure of real datasets but does not preserve statistical relationships between variables yet still has the potential for high utility for a set of defined use cases.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17980236

Authors: Oliver, Emily, McCall, Sophie, Bremner, Ryan, Boyd, Andy, Magder, Cristina, Myles, Puja, Frayling, Lora, Pearson, Jonathan

Institutions: Research Councils UK, University of Bristol, University of Essex, Clinical Practice Research Datalink, NHS England

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7116148564

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