Professor Mark Elliot receives ESRC grant (March 2024)
(Social Statistics) has been awarded an ESRC grant for the project Enhancing Data Accessibility and Security through Innovative Data Synthesis (EDASIDA).
The EDASIDA project aims to transform both data accessibility and confidentiality through innovative data synthesis techniques. In essence, the project will develop a methodology for providing tailored teaching datasets and systematic disclosure risk assessment methods.
The new methodology involves leveraging cleared analytical outputs from data services as the basis for generating synthetic data using genetic algorithms. The goal is to provide trainees with data that not only closely resembles real-world data but also yields analytical output very similar to that of the real data, enhancing the training experience.
A pilot study conducted in collaboration with Administrative Data Research UK, demonstrated the feasibility of generating synthetic teaching datasets with both high utility and no marginal disclosure risk. The pilot dataset (a synthetic version of the linked ASHE-census dataset) was successfully used in a ADR-UK training course in April 2024.
The approach also offers a route to formalise assessment the disclosure risk associated with analytical outputs from safe settings. By embodying statistical outputs in synthetic data, it enables a systematic evaluation of disclosure risk, addressing the informality and potential inconsistencies present in current output checking procedures.
Finally, the project aims to bolster the federated services agenda by exploring the creation of synthetic linked data from using analytical outputs from data of multiple services. This approach expands the possibilities of data synthesis without the need for actual linkage and elaborate governance of infrastructure, such as trusted third parties.