Synthetic data: A primer by Dr Dan Quintana

About the speaker

Daniel S. Quintana is a researcher in biological psychiatry at the University of Oslo. His research interests include social behaviour, the oxytocin system, heart rate variability, and meta-analysis. He currently leads a project investigating the role of the oxytocin system in the development of severe mental illness and metabolic disorder, which is supported by an Excellence Project for Young Researchers grant from the Novo Nordisk Foundation. Dan is also known for the Everything Hertz podcast, which he co-hosts with James Heathers. Widely praised for his training materials to support the adoption of open research practices, Dan is a strong advocate for disseminating scholarly outputs with the aid of social media, which was the subject of his talk for the Rotterdam RIOTS Club in May.

About the talk

Open research data provide considerable scientific, societal, and economic benefits. However, disclosure risks can sometimes limit the sharing of open data, especially in datasets that include sensitive details or information from individuals with rare disorders. This talk introduces the concept of synthetic datasets, which is an emerging method originally developed to permit the sharing of confidential census data. Synthetic datasets mimic real datasets by preserving their statistical properties and the relationships between variables. Importantly, this method also reduces disclosure risk to essentially nil as no record in the synthetic dataset represents a real individual. This practical guide with accompanying R script enables biobehavioural researchers to create synthetic datasets and assess their utility via the synthpop R package. By sharing synthetic datasets that mimic original datasets that could not otherwise be made open, researchers can ensure the reproducibility of their results and facilitate data exploration while maintaining participant privacy.