00000cam 2200000zi 4500 9.965832 CaOODSP 20260914133516 m o d f cr cn||||||||| 260914e20250908oncad obs f000 0 eng d CaOODSP eng rda CaOODSP n-cn--- CS11-522/2024-1-1E-PDF Pilgram, Lisa 1991- author. Practical applications of synthetic data generation / by Lisa Pilgram and Khaled El Emam. At head of title: Proceedings of Statistics Canada Symposium 2024 : the future of official statistics [Ottawa] : Statistics Canada = Statistique Canada, September 8, 2025. 1 online resource (11 unnumbered pages) : illustrations, graphs. text txt rdacontent computer c rdamedia online resource cr rdacarrier [Statistics Canada international symposium series : proceedings], 1709-8211 Title from cover. Issued also in French under title: Applications pratiques de la génération de données synthétiques. Includes bibliographical references. "Synthetic data generation (SDG) is increasingly applied across sectors for privacy-preserving data sharing, de-biasing and augmentation. Each use case requires a distinct set of evaluation metrics that must account for the stochasticity of the SDG process: membership and attribute disclosure vulnerability are critical for privacy; fidelity and downstream task utility apply even more broadly; and fairness and diversity are relevant for de-biasing and augmentation, respectively. Presenting accumulated evidence and through exemplar case studies, it is shown that SDG can perform well across many of these use cases and key learnings from our experiences with synthetic health data are shared"--Abstract, page [2]. Data privacy Canada. Data mining Statistical methods Canada. Canada Statistics, Medical. Statistics Canada, issuing body. Applications pratiques de la génération de données synthétiques / (CaOODSP)9.965839 Statistics Canada international symposium series - proceedings, 1709-8211 (CaOODSP)9.505681 PDF 395 KB https://publications.gc.ca/collections/collection_2026/statcan/11-522-x/CS11-522-2024-1-1-eng.pdf 11-522-X