ArticleInternational journal of population data science2025
Four checks for low-fidelity synthetic data: recommendations for disclosure control and quality evaluation.
Article in International journal of population data science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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3 authors.
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Abstract
Confidential administrative data is usually only available to researchers within a Trusted Research Environment (TRE). Recently, some UK groups have proposed that low-fidelity synthetic data (LFSD) be made available to researchers outside the TRE, to allow code-testing and data discovery. There is a need for transparency so that those who access LFSD know how it has been created and what to expect from it. Relationships between variables are not maintained in LFSD, but a real or apparent data breach can occur from its release. To be useful to researchers for preliminary analyses LFSD needs to meet some minimum quality standards. Researchers who will use the LFSD need to have details of how it compares with the data they will access in the TRE clearly explained and documented. We propose that these checks should be run by data controllers before releasing LFSD to ensure it is well documented, useful and non-disclosive.
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