Simulated Microdata: Expanding Safe Access to Public Sector Information

The Australian Bureau of Statistics (ABS) is exploring the use of simulated microdata to expand safe access to public sector datasets. These synthetic datasets replicate the properties of real data while safeguarding confidentiality, giving researchers, students, and policymakers a practical way to test ideas, build models, and train with realistic information. By serving as a secure stepping stone before accessing sensitive data, simulated microdata has the potential to accelerate research, strengthen data literacy, and broaden participation in evidence‑based analysis.

In this presentation, Dr Chien will:

• Describe the simulated microdata techniques the ABS has explored to create safe datasets for research and training.
• Discuss how these datasets serve as a bridge to secure environments, enabling innovation while safeguarding confidentiality.
• Highlight the benefits they offer to researchers, along with the challenges encountered in their development.

Chien-Hung (Joseph) Chien is the Director of Data Access and Confidential Methodology Unit at the Australian Bureau of Statistics (ABS), a role he has held since 2019. With over two decades of experience in statistical leadership, including a tenure at the OECD in Paris, he brings deep expertise in data confidentiality and accessibility. As the ABS’s first Sir Roland Wilson Scholar, he earned a PhD focused on using administrative data to uncover microdrivers of productivity. He currently leads efforts to advance synthetic data, output protection for the ABS DataLab, and the application of differential privacy to strengthen confidentiality frameworks.

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