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Session 1: Machine Learning Applications

Session Organizers: Michael Reusens (Statistics Flanders, Belgium) and Joni Karanka (Office for National Statistics, UK)

Classifying companies in France using machine learning - Thomas Faria and Tom Seimandi (Insee, France)	Abstract	Paper	Presentation
Using Webdata to derive the Economic Activity of Enterprises - Manveer Mangat (Statistics Austria)	Abstract	Paper	Presentation
Clothing Price Index using Web-Scraped Data - Laura Christen and Ahmet Aydin (Office for National Statistics, UK)	Abstract	Paper	Presentation
Imputation of occupation in the Occupational Register - Jens Malmros (Statistics Sweden)	Abstract	Paper	Presentation
Too good to be true? A case of machine learning in the validation process of the R&D statistics - Eva Charlotte Berner and Solveig Bjørkholt (Statistics Norway)	Abstract	Paper	Presentation
Geospatial Bayesian Methods for Hazard-Impact Modelling - Hamish Patten (University of Oxford)	Abstract	Paper	Presentation
Progression patterns in the Swiss social security system based on Machine Learning: methods for evaluating quality and model drift - Athanassia Chalimourda (Swiss Federal Statistics Office)	Abstract	Paper	Presentation
ML Poverty: Using Machine Learning to estimate poverty rates in Switzerland at the canton level - Yara Abu Awad (Swiss Federal Statistics Office)	Abstract	Paper	Presentation
Creating a modern business index: Machine learning record linkage at scale - Isabela Breton and Joanne Sheppard (Office for National Statistics, UK)	Abstract	Paper	Presentation
Time Series Outlier Detection using Metadata and Data Machine Learning in Statistical Production - Olivier Sirello (BIS)	Abstract	Paper	Presentation
Timeliness and Accuracy with Machine Learning Algorithms: Early Estimates of the Industrial Turnover Index - David Salgado (Statistics Spain)	Abstract	Paper	Presentation
Nowcasting TiVA indicators: improving timeliness of trade data - Polina Knutsson (OECD)	Abstract	Paper	Presentation

Session 2: Quality Aspects of Machine Learning in Official Statistics

Session Organizers: Florian Dumpert (Federal Statistical Office of Germany) and Ralf Becker (UN Statistical Division)

Quality Framework for Statistical Algorithms - InKyung Choi (UNECE)	-	Paper	Presentation
A Quality Concept for the Use of Machine Learning in Official Statistics - Florian Dumpert (Federal Statistical Office of Germany)	Abstract	Paper	Presentation
Exploring quality dimensions in trustworthy Machine Learning in the context of official statistics: model explainability, accuracy and uncertainty - Saeid Molladavoudi (Statistics Canada)	Abstract	-	Presentation
Understanding model quality in the context of trustworthiness and value - Emily Barrington (Office for Statistics Regulation, UK)	Abstract	Paper	Presentation
Lessons learned when applying Machine Learning in Official Statistics: Why it helps to be a survey statistician and a data scientist! - Piet Daas (Statistics Netherlands)	Abstract	Paper	Presentation
Changing Data Sources in the Age of Data Science for Official Statistics - Cedric De Boom (Statistics Flanders, Belgium)	Abstract	Paper	Presentation

Session 3: Toward system-wide transformation of statistical production

Session Organizers: Riitta Piela (Statistics Finland) and Dominika Nowak (Statisitcs Poland)

Keynote presentation: How to Manage Machine Learning as a Process of Continuous Improvement in the Context of Official Statistics - Prof. Diego Kuonen (Statoo Consulting & GSEM, University of Geneva, Switzerland)	-	-	Presentation
Facilitators and Blockers of ML Adoption in Official Statistics - Joni Karanka (ONS, UK)	Abstract	Paper	Presentation
A Machine Learning Capability Uplift Strategy - Claire Clarke (Australian Bureau of Statistics)	Abstract	-	Presentation
ML training : Who? What? How? and… What for? - Christophe Bontemps (UN Statistical Institute for Asia and the Pacific, ESCAP)	Abstract	-	Presentation
Balsam: A Collaborative Platform to Support ML and ML-Ops initiatives - Jakob Engdahl (Statistics Sweden)	Abstract	Paper	Presentation
An open source data science platform to foster innovative and production-ready machine learning systems - Romain Avouac (Insee, France)	Abstract	Paper	Presentation
Hands-on Lab: An introduction to MLOps with Mlflow - Tom Seimandi, Romain Avouac and Thomas Faria (Insee, France)	Abstract	-	Presentation

UNECE Machine Learning for Official Statistics Workshop 2023

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