UNECE Expert Meeting on Statistical Data Confidentiality 2023
26 - 28 September 2023
Wiesbaden, Germany
Documents
39497 _ Information Notice 1 _ 375829 _ English _ 773 _ 374591 _ pdf
39497 _ Information Notice 2 _ 380915 _ English _ 773 _ 386916 _ pdf
39497 _ Tentative Timetable _ 382347 _ English _ 773 _ 391182 _ pdf
39497 _ Meeting report _ 384924 _ English _ 773 _ 397810 _ pdf
Innovative approaches in granting access to microdata
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Remote Access for Scientific Use Files – a New Pathway for German Official Statistics Microdata Access, DESTATIS Germany |
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Remote access to European microdata, Eurostat |
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Governance of confidential research data in low- and middle-income countries, University of West England |
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Producing useful microdata files
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An overview of data protection strategies for individual-level geocoded data, Institute for Employment Research (IAB) |
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Smoothing the way for secure data access using synthetic data, Administrative Data Research UK |
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Overview of the AnigeD Project and Potentials of Dataset Synthetization for Official Statistics and Research, DESTATIS, Germany |
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Study and analysis for the elaboration and dissemination of microdata of sociodemographic information, Basque Statistics Office, Spain |
Challenges in publishing safe tables and maps
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Protecting High-Resolution Poverty Statistics against Disclosure using Differential Privacy, Swiss Federal Statistical Office |
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An overview of used methods to protect the European Census 2021 tables, Statistics Netherlands |
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A Disclosure-Based Framework for Comparing Frequency Table Protection, Statistics Norway |
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Spatial SDC experiments and evaluations – multiple countries comparison, Statistics Austria |
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What is Reconstruction and Reidentification? Illustrations from the 2010 US Census Tabular Data Release, University of Oklahoma USA |
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The Potential of Differential Privacy Applied to Detailed Statistical Tables Created Using Microdata from the Japanese Population Census, Chuo University Japan |
Risk assessment: Privacy, confidentiality, and disclosure vs utility
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Assessing the utility of synthetic data: A density ratio perspective, Utrecht University, Statistics Netherlands |
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Intruder testing for Census 2021 England and Wales– checking risk and utility in Build Your Own system, Office for National Statistics, UK |
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Making Attribute Information of Synthetic Data Interpretable With the Aggregation Equivalence Level, Ministry of Education, Culture and Science, Netherlands |
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Generating Synthetic Microdata and Assessing Statistical Disclosure Risk Measures, World Bank |
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Do samples of synthetic microdata population replicate the relationship between samples taken from an original population and that population? University of Manchester, UK |
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Confidence-ranked reconstruction of census records does not reflect privacy risks or reidentifiability, Universitat Rovira i Virgili |
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Differential privacy for microdata, World Bank |
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The case of bounds in noisy protection methods: Selected risk and utility perspectives from official population statistics, Eurostat |
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Dissemination of agricultural geo-referenced data within the context of the 50x30 initiative: an overview of the tradeoff between disclosure risk and data utility, United Nations Food and Agriculture Organization |
Output checking in research data centres
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A Case Study of Output Checking in Japan, National Statistics Center |
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Towards a comprehensive theory and practice of output SDC, University of the West of England, UK |
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COACH: COmputer-Assisted output CHecking with Human-in-the-Loop, Statistics Netherlands |
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SACRO: semi-automated output checking, University of the West of England, UK |
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Checking Data Outputs from Research Works: a Mixed Method with AI and Human Control, CASD Secure data hub |
Other emerging issues
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SDC in statistical education - the Polish experience, Statistical Office in Poznań, Poland |
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Experiments on Federated Data Synthesis, University of Manchester, UK |
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Insights into privacy-preserving federated machine learning from the perspective of a national statistical office, ISTAT, Italy |
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The risk of identity disclosure through network structure: anecdotal evidence from a hackathon, Statistics Netherlands |
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Disclosure control issues in complex medical data, University of the West of England, UK |