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UNECE Expert Meeting on Statistical Data Editing 2024

UNECE Expert Meeting on Statistical Data Editing 2024

07 - 09 October 2024
Vienna Austria

The focus of the meeting will be on cutting edge ideas, approaches, and tools in the area of statistical data editing. In addition to the traditional presentations, the agenda of the meeting anticipates interactive discussions related to particular topics within this field.

The target audience of the expert meeting includes senior and middle-level methodologists, statisticians and researchers, working on editing and imputation of statistical data derived from surveys, censuses, administrative and external sources.

Document Title Documents Presentations
Information Notice 1  PDF  
Information Notice 2 (logistical information) PDF  
Preliminary timetable  PDF  

Session 1: E&I quality

     
Keynote Presentation: Current work on automatic multisource editing at Statistics Netherlands. Sander Scholtus (Statistics Netherlands) Abstract   Paper Presentation
Leveraging AI for statistical editing: the case of the BIS AI Metadata Editor - Olivier Sirello (Bank for International Settlements) Abstract Paper Presentation
Lightning Talk: Using hidden Markov and macro integration models for combining data from different sources - Sander Scholtus (Statistics Netherlands) Abstract - Presentation

Session 2: E&I process

     
National guidelines on data editing; the foundation for building a solution for the future - Aslaug Hurlen Foss (Statistics Norway) Abstract Paper Presentation
Moving towards the standardized process of automatic statistical data editing using machine learning techniques - Ieva Burakauskaitė (State Data Agency, Statistics Lithuania) Abstract Paper Presentation
The editing and imputation process of the 2021 household and nuclei types reconstruction in Italy - Rosa Maria Lipsi (Istat, Italy) Abstract Paper Presentation
Keynote Presentation: Building the new Banff: an open-source data editing system based on GSDEM concepts - Darren Gray (Statistics Canada) Abstract   Presentation

Session 3: Imputation

     
Full conditional distributions for handling restrictions in the context of automated statistical data editing - Christian Aßmann (Leibniz Institute for Educational Trajectories) Abstract Paper Presentation
Application of the MissForest algorithm for imputing income variables in the Survey on Income and Living Conditions - Blandine Bianchi (Swiss Federal Statistical Office) Abstract Paper Presentation
Assessment of Manual vs Automated Survey Editing and Imputation - Sean Rhodes (U.S. Department of Agriculture National Agricultural Statistics Service) Abstract Paper Presentation
Enhancing Official Statistics through Artificial Intelligence: A Comparative Study of Imputation Techniques - Simona Cafieri (Istat, Italy) Abstract Paper Presentation
Lightning Talk: Random forest imputation of nutritional information for statistics on food consumption in Norway - Magne Furuholmen Myhren (Statistics Norway) Abstract - Presentation

Session 4: Selective editing and outlier detection

     
Detecting Extreme Numerical Outliers in Trade Data: A Novel Method for Highly Asymmetric Distributions - Andrea Cerasa (European Commission, Joint Research Centre) Abstract Paper Presentation
Selective editing for the production of new Services Producer Price Indices (SPPIs) from indirect data sources - Simona Rosati (Istat, Italy) Abstract Paper Presentation
Outlier Identification and Adjustment for Time Series - Markus Fröhlich (Statistics Austria) Abstract Paper Presentation

Session 5: International community building

     
Organisational Aspects of Implementing ML Based Data Editing in Statistical Production - Steffen Moritz (Destatis) Abstract Paper Presentation
Presentation on the various themes of AIML4OS: project overview - Alexander Kowarik (Statistics Austria) - - Presentation
The European One-Stop-Shop for Artificial Intelligence and Machine Learning for Official Statistics (AIML4OS): WP8 Use Case focused on data editing - Steffen Moritz (Destatis, Germany) Abstract Paper Presentation
The European One-Stop-Shop for Artificial Intelligence and Machine Learning for Official Statistics (AIML4OS): WP9 Use Case focused on imputation - David Salgado (Statistics Spain) Abstract Paper Presentation