Evaluating the Benefits, Costs, and Utility of Synthetic Data for Data Owners and Trusted Research Environments

Objectives This study evaluates low-fidelity synthetic data's benefits, costs, and utility for data owners and Trusted Research Environments (TREs). It examines financial implications, operational efficiencies, and governance challenges, informing best practices for scalable and ethical synthetic data production. The findings will provide actionable insights for the entire research ecosystem. Methods A mixed-methods approach evaluated synthetic data adoption among data owners and TREs. A literature review synthesized best practices, ethical considerations, and technical challenges. A survey assessed data owners' perceptions, readiness, and financial concerns. Using semi-structured interviews, policy analysis, and standard operating procedures (SOPs), case studies were conducted with existing synthetic data producers to examine frameworks, governance, and cost structures. Focus groups with TRE representatives explored operational challenges, security risks, and policy gaps. This research was a jointly funded initiative by the Economic and Social Research Council (ESRC) Data & Infrastructure Programme and ADR UK, conducted by UK Data Service. Results When submitting this propos