Lessons from Two Synthetic Data Use Cases at the UMCG
Year: 2026
Type: article
Abstract: This report describes the development and refinement of the IDEAL-SD framework for the responsible generation, evaluation, governance, and use of synthetic data at the University Medical Center Groningen (UMCG), drawing on lessons learned from two educational use cases. The report outlines the five stages of the IDEAL-SD framework: Intake, Data Preparation and Synthesis, Evaluation, Appraisal and Governance Approval, and Launch. It discusses how the framework evolved between the two applications, with particular attention to improving requirements gathering, aligning utility and privacy evaluations with intended uses and identified disclosure risks, and strengthening governance and decision-making procedures. The report also presents the practical outcomes of these experiences, including improvements to the Synthetic Data Intake Form, the evaluation methodology, and the documentation supporting governance decisions. Developed in the context of the UMCG's participation in the Dutch national Opschalingsticket Synthetische Data initiative, this report contributes to knowledge sharing among participating organisations and provides practical insights and examples that can support the development of responsible synthetic data processes in other institutional settings.
Author: De Pinho Uliana, Alexandre
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7225821570
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