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UNECE Expert Meeting on Statistical Data Confidentiality 2023

UNECE Expert Meeting on Statistical Data Confidentiality 2023

26 - 28 September 2023
Wiesbaden Germany

If you wish to register to attend this meeting, you may do so via the following website: https://indico.un.org/e/SDC2023

 

Practical information for participants

Please refer to the details contained within Information Notice 2, below.

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

Innovative approaches in granting access to microdata

Remote Access for Scientific Use Files – a New Pathway for German Official Statistics Microdata Access, DESTATIS Germany

Paper

PPT

Remote access to European microdata, Eurostat

Paper

PPT

Producing useful microdata files

An overview of data protection strategies for individual-level geocoded data, Institute for Employment Research (IAB)

Paper

PPT

Smoothing the way for secure data access using synthetic data, Administrative Data Research UK

Paper

PPT

Overview of the AnigeD Project and Potentials of Dataset Synthetization for Official Statistics and Research, DESTATIS, Germany

Paper

PPT

Study and analysis for the elaboration and dissemination of microdata of sociodemographic information, Basque Statistics Office, Spain

Paper

PPT

Challenges in publishing safe tables and maps

Protecting High-Resolution Poverty Statistics against Disclosure using Differential Privacy, Swiss Federal Statistical Office

Paper

PPT

An overview of used methods to protect the European Census 2021 tables, Statistics Netherlands

Paper

PPT

A Disclosure-Based Framework for Comparing Frequency Table Protection, Statistics Norway

Paper

PPT

Spatial SDC experiments and evaluations – multiple countries comparison, Statistics Austria

Paper

PPT

What is Reconstruction and Reidentification?  Illustrations from the 2010 US Census Tabular Data Release, University of Oklahoma USA

Paper

PPT

The Potential of Differential Privacy Applied to Detailed Statistical Tables Created Using Microdata from the Japanese Population Census, Chuo University Japan

Paper

PPT

Risk assessment: Privacy, confidentiality, and disclosure vs utility

Assessing the utility of synthetic data: A density ratio perspective, Utrecht University, Statistics Netherlands

Paper

PPT

Intruder testing for Census 2021 England and Wales– checking risk and utility in Build Your Own system, Office for National Statistics, UK

Paper

PPT

Making Attribute Information of Synthetic Data Interpretable With the Aggregation Equivalence Level, Ministry of Education, Culture and Science, Netherlands

Paper

PPT

Generating Synthetic Microdata and Assessing Statistical Disclosure Risk Measures, World Bank

Paper

PPT

Do samples of synthetic microdata population replicate the relationship between samples taken from an original population and that population? University of Manchester, UK

Paper

PPT

Confidence-ranked reconstruction of census records does not reflect privacy risks or reidentifiability, Universitat Rovira i Virgili

Paper

PPT

Differential privacy for microdata, World Bank

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PPT

The case of bounds in noisy protection methods: Selected risk and utility perspectives from official population statistics, Eurostat

Paper

PPT

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

Paper

PPT

Output checking in research data centres

A Case Study of Output Checking in Japan, National Statistics Center

Paper

PPT

Towards a comprehensive theory and practice of output SDC, University of the West of England, UK

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PPT

COACH: COmputer-Assisted output CHecking with Human-in-the-Loop, Statistics Netherlands

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PPT

SACRO: semi-automated output checking, University of the West of England, UK

Paper

PPT

Checking Data Outputs from Research Works: a Mixed Method with AI and Human Control, CASD Secure data hub

Paper

PPT

Other emerging issues

SDC in statistical education - the Polish experience, Statistical Office in Poznań, Poland

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PPT

Experiments on Federated Data Synthesis, University of Manchester, UK

Paper

PPT

Insights into privacy-preserving federated machine learning from the perspective of a national statistical office, ISTAT, Italy

Paper

PPT

The risk of identity disclosure through network structure: anecdotal evidence from a hackathon, Statistics Netherlands

Paper

PPT

Disclosure control issues in complex medical data, University of the West of England, UK

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PPT