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Theme Groups

The ML Group 2022 is focussing its activities on a number of key themes which are important to advancing our understanding of the added value of ML for official statistics and how it can best be integrated into statistical systems. Members have formed small groups to work together on knowledge exchange and research activities aimed at delivering common outputs.

The groups are organised and run by members themselves, who contribute in different ways depending on their interests and the objectives of the group:

  • Knowledge exchange: Joining a group to share knowledge and experience on a topic of common interest on a regular basis. (e.g. a study group or discussion group)
  • Research support. Providing feedback and advice to other ML Group members working on their own research projects, or receiving input on your own project.
  • Research collaboration. Working on a common topic or data set with other group members with a primary aim of delivering the output together
ThemeDescriptionProject information
ImageryThis group will focus on the use of machine learning for earth observation data. Its objectives are expected to concentrate on capability building and the research projects proposed by members (see right)
IT InfrastructureThis group aims to share experiences of statistical organisations in developing open base platforms for ML data processing and analysis that will enable collaboration with external research partners.
ModellingThis group explores the application of machine learning techniques to modelling research projects proposed by group members. Members will work together, collaborating on research activities, providing feedback on outputs and sharing relevant input and advice.
Model RetrainingThis Theme Group will explore ways to monitor and re-train ML models. Members will share experiences from their own projects and discuss best practice, building on the work done in ML Group 2021.
Quality of Training DataThis group will explore issues related to human annotation process and sampling methods to obtain representative training sets. 
Text ClassificationThis group will host a series of presentations on statistical offices projects and discussions on best practice.
Web scraping DataThis group will work together on a research project to create new indicators for companies using text scraped from company web pages. In particular, organisations wishing to run a similar project in parallel with others are invited to get in touch as soon as possible.

If you would like to take part in any of these activities or join the ML Group programme for 2022 please contact

Key Documents

Terms of reference:  This document provides information on the purpose of the group, how it is run and what membership involves.

Invitation to join international collaboration on Machine Learning in Official Statistics

We are inviting colleagues working in official statistics and government data science roles around the world to participate in our 2022 programme.

We are an international platform for research collaboration, knowledge exchange and capability building on ML for official statistics. We bring together 250+ members from 33 different countries to explore how ML can improve statistical output and be integrated successfully into production. Last year we ran 18 different research projects and held regular expert presentations on ML innovations at statistical organisations around the world.

We’re a dynamic and growing community, and welcome all levels of ML experience from expert to novice. It’s a great place to connect with and learn from others working on ML. We’re especially keen to recruit more experienced data scientists to our membership this year.

This year our programme focuses on the following themes:

For an overview of the group's work and our 2022 programme, please read the presentation from our programme launch meeting on 9 February. 

As a member you will be invited to our monthly meetings for expert presentations and discussions. You will also receive access to members websites and library, our members discussion forum, and will receive regular updates from our Theme Groups. All members are encouraged to contribute input, eg by sharing experience from their work through discussions and presentations.

Members are also invited to join one of our Theme Groups, small groups running knowledge exchange and research collaboration activities on key areas of our ML 2022 programme. (see right-hand column).

If you’d like to join us as a member or be added to our public mailing list, please get in touch with Alison Baily, International Programme Manager, on .  We also welcome enquiries about collaboration from the ML academic community.

We look forward to hearing from you!

ML Group 2022 Monthly Meeting Presentations 

June 15 

Piet Daas, CBS Netherlands

Using web site texts to identify different types of companies (presentation slides)

David Corney, Full Fact, UK

How to stop people misusing statistics: Automatic verification of statistical claims (presentation slides)

May 4

Florian Dumpert (Federal Statistical Office of Germany)

Quality Framework for Statistical Algorithms (presentation slides)
April 6

Abel Dasylva (Statistics Canada)

Estimating linkage errors without training data and without assumptions about the interactions among the linkage variables (presentation slides)

Joep Burger (CBS Netherlands)

Convolutional neural networks for learning target variables and extracting image features from Earth Observation (presentation slides)
March 2Ingmar Weber (Qatar Computing Research Institute)Using Advertising Data to Model Digital Gender Gaps and Poverty (presentation slides)
Ralf Becker (UN Statistics Division)Introduction to the new UN Big Data Training Catalogue (presentation slides)

Coffee and Coding Session

27 April

Tom Wise (UK ONS)

Machine Learning foundations and focused on the theory behind these techniques.

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