Conference "Data science for better decisions"

On Tuesday 17 December 2019, Statistics Flanders and CBS, Statistics Netherlands jointly organise this one-day international conference on how data science can contribute to better official statistics for decision making. In a fast-moving digital environment, how can new data sources and techniques help in supporting better decisions? What are the opportunities from the boom in the availability of data to inform policy decisions, and what are the risks in using new tools and techniques to handle big data sources?

Go to Practical information - Route - Registration


The programme will be completed in September and October.

In the morning a number of keynote speakers will comment on the position of big data, data science and associated techniques (such as machine learning and artificial intelligence) in the broader data landscape, and discuss how digital developments affect policy making and the data sources required to support policy decisions.

09:00 Welcome with coffee
Auditorium, Brussels Department for the Environment, Tour & Taxis
10:00 Introduction
Tjark Tjin-A-Tsoi, director-general CBS, Statistics Netherlands
Roeland Beerten, chief statistician Statistics Flanders
10:20 Keynote speaker - Diane Coyle
Diane Coyle is Bennett Professor of Public Policy at the University of Cambridge. Her research interests focus on economic measurement in the context of new technologies, digitalisation, sustainability and globalisation. She was the recipient of the Indigo Prize for innovation in economics. She is currently a Fellow at the UK Office for National Statistics where she advises on measuring the economy.
11:10 Keynote speaker - Kenneth Cukier
Kenneth Cukier is an American journalist and author of a number of books on the data revolution and new technologies and their impact on society. He is a Senior Editor at The Economist, and host of its weekly podcast on technology. As associate fellow at Said Business School at Oxford, he researches artificial intelligence. His book 'Big Data: A Revolution that Will Transform How We Work, Live and Think' was one of the first books on the topic of big data and was translated into more than 20 languages.
In the afternoon four parallel sessions will look more closely at different data science techniques and their application, as well as the conditions that support the efficient use of these techniques. The day will close with a panel discussion.
13:00-14:45 Parallel sessions

Session 1. Machine learning

Machine learning algorithms detect patterns in data and use these to predict missing data. Data can be missing because it was not collected or observed, or simply because the prediction is about the future. Machine learning algorithms do not aim to model underlying real-world systems explicitly, rather they employ computational techniques to achieve optimal predictive accuracy. Consequently, they are often described as black-box systems, lacking transparency. This session addresses issues related to decision making when machine learning is involved.

Session 2. Natural Language Processing

Natural language processing investigates how large amounts of data consisting of natural language can be processed and analyzed via computers. Some examples: data from social media are used to test the number of messages and the sentiment with regard to certain subjects. The usefulness of this sentiment analysis has, for example, been demonstrated in the context of consumer confidence. Web scraping, where data is extracted from websites, is used in several research areas, including in the context of job vacancy statistics.

Session 3. Images and visualisation

This session involves two aspects of the use of images: the use of images as a data source, and visualisation of data to a wide audience. The basic data for data science can consist of images such as satellite images or images from Google street view, which poses new challenges. Furthermore there is the rapidly growing field of data visualisation where abstract information is being made available more efficiently than ever before. This session will give an overview of some projects where images are used as data, as well in data visualisation and dashboard displays to translate abstract data into user-friendly information.

Session 4. Preconditions for effective data science deployment

The usefulness of data science for supporting decisions doesn't just depend on statistical and technical standards. Several ethical and organisational issues determine important preconditions for delivering good data science. First of all, there are significant debates around the ethics and privacy dimensions of the growing data science field, to be taken into account when techniques are applied to real-life data. Secondly, developing data science methods for official statistics requires active collaboration between NSI's and international institutions such as the UN and Eurostat, given the global nature of many of the new data sources and policy decisions. Thirdly, providers of Big Data are often private companies. How to organise a sustainable relationship with them? Finally, partnerships are set up with universities and companies to optimise the use of these promising techniques for the development, production and quality improvement of official statistics. This is also a challenge.


Panel Discussion

Working with new and uncharted data sources requires different ways of working in statistical offices compared to the traditional way of producing statistics based on surveys or administrative data. The experts in the panel will discuss some of the new topics in this context, including the challenges and opportunities of these new data types and their associated methodologies, the different approaches needed to acquire data from external data producers rather than collecting the data in-house, communicating the strengths and limitations of new data science approaches to non-technical experts, and some of the ethical challenges surrounding a data-driven society.


  • Diego Kuonen, CEO Statoo Consulting, Professor of Data Science University of Geneva, Principal Scientific and Strategic Big Data and Data Science Advisor for the Directorate and the Board of Management of the Swiss Federal Statistical Office (FS0), Co-Author of FSO's Data Innovation  Strategy, Switzerland
  • Martina Hahn, Head of Methodology and Innovation in Official Statistics, Eurostat
  • Sofie De Broe, Scientific Director of the Center for Big Data Statistics, CBS, Statistics Netherlands
  • Roeland Beerten, Chief statistician Statistics Flanders, Belgium
16:15 Drinks reception

Practical information

When Tuesday 17 December 2019, from 10:00 a.m. to 16:15 p.m.
Where Brussels (Belgium), on the Tour & Taxis site (Havenlaan 86C, 1000 Brussel)
Language English
Who Everyone who has an interest in data, statistics and data science and how they can support decision-making.

Registration is free.

Coffee, tea and water are available all day. We provide a simple lunch and conclude with a drinks reception. These are free, but we ask you to register for lunch and the reception


Free shuttle service There is a shuttle service between the railway station Brussels North station and the site. Large buses are used during peak hours and small shuttle buses during off-peak hours. The shuttle service works according to the 'first come, first served' principle. During peak hours there may not be enough room for all those waiting at the bus.
Bus stop at Brussels North. If you leave the railway station via the main entrance, buses (with a "Tour & Taxis" sign) stop to the left of the stairs. This is at Bolivarplein at the side entrance of the Proximus building.
Bus stop on the site Tour&Taxis. There is a bus stop with a bus shelter at the entrance of the site between the Herman Teirlinck building and ‘het pakhuis’.
On foot On foot from the railway station Brussels North
On foot: 20 minutes
The recommended walking route from the railway station Brussels North runs via the ‘Willebroekkaai’. People who use blind guidance tiles can also follow this route.
Route on Google maps
By car You can plan your route in Google Maps

Parking nearby
Parking up-site (at 500 meters from Thurn & Taxis) – Willebroekkaai 35 – 1000 Brussels
WTC-parking (close to the railway station Brussels North) - Simon Bolivarlaan – 1000 Brussel


Register now online




Jointly organised with

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