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 | |||
| Information Notice 2 (logistical information) | |||
| Preliminary timetable | |||
Session 1: E&I quality |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |