The New Techniques and Technologies for Statistics (NTTS) is an international biennial scientific conference series, organised by Eurostat, on new techniques and methods for official statistics and the impact of new technologies on statistical collection, production and dissemination systems. 

The NTTS 2023, the 12th edition, will be a hybrid conference and will take place in March 2023.

The purpose of the conference is both to allow the presentation of results from currently ongoing research and innovation projects in official statistics, and to stimulate and facilitate the preparation of new innovative projects (by encouraging the exchange of views and co-operation between researchers - including the possible building of research consortia) with the aim of enhancing the quality and usefulness of official statistics. The conference brings together academics, statisticians and users of data to discuss, network and exchange ideas.

Previous editions can be found as following: NTTS2021NTTS2019,  NTTS2017NTTS2015,  NTTS2013NTTS2011NTTS2009.


Registrations will be opened on 23rd of January 2023.

Stay tuned!

Call for Abstracts

The NTTS2023 Call for Abstracts is closed


Guidelines and template



Submission website:


Contact us if you need help with your submission!


Key dates

Call for abstracts: 1st July 2022

Deadline for submission of abstracts: 16th October 2022

Notification of acceptance: 28th November 2022

Registrations: From 23rd of January 2023 to 28th of February 2023

Please note that accepted speakers are expected to participate in the event physically in Brussels.

List of topics

Data collection and integration
Innovation in Statistics
Data analytics revolution
Estimation and analysis
Data reuse and sharing
Users outreach, communication and dissemination
Data ecosystem
Frameworks, software and tools
Mixed-mode and web data collection 
New data sources 
Data science and (big) data analytics 
Nowcasting and flash estimates
Data platforms and data-as-a-service 
Communicating uncertainty of official statistics 
Data stewardship models 
Open frameworks for replicability and reproducibility 
Collection and use of paradata to improve surveys
Web Intelligence 
Experimental statistics 
Time series analysis and revisions 
Statistical disclosure control, confidentiality and privacy 
Digital economy, digitalisation (data from financial sector, health, environment, etc.) 
Use of R in official statistics 
Adaptive and responsive survey designs  
Designed data collection by (mobile) devices 
Blockchain, distributed ledgers and smart contracts applied to official statistics 
Outlier detection
Data access for researchers
Data Storytelling
Sustainable Development Goals – opportunities for collaboration between statistical and social sciences research communities  
New Statistical tools and software (Python, Julia, Shiny, etc.) 
Non-response, response propensity, respondent behavior and response burden 
Smart Surveys and
Trusted Smart Surveys
Artificial intelligence in statistics
Seasonal Adjustment 
Technical and legal aspects around the use of confidential data of official statistics, GDPR 
Collaborative and participative analytics  
Sustainable use of natural resources 
Open source and sharing codes (git, Github, etc.) 
Behavioral applied to surveys 
Privacy preserving technologies applied to official statistics 
Semantic web and Natural Language Processing  
Econometric Modelling 
Data validation 
Methods for capturing user input, assessing user needs and user satisfaction 
Ethics, digital skills, cybersecurity 
Reusing tools and services 
Measurement of longitudinal phenomena 
Novel methodological approaches for non-traditional data sources  
Machine learning  
Variance estimation 
(Linked) Open Data 
(Statistical) literacy in the data age 
Statistical systems in developing countries – opportunities and risk from alternative methods  
Enterprise architecture and standards 
Data linking and statistical matching with different sources 
Quality aspects of non-traditional data sources  
Skills for tomorrow’s official statisticians
Small area estimation 
Data minimization and enhancing techniques  
Producing Official Statistics in Emergency Situations: Reflections and challenges posed by the Covid-19 pandemic 
Data architecture 
Multinational repositories and exchange/share/use of microdata 
Data Innovation 
Geospatial statistics 
Data policies and governance  
Collaborating with private sector and academic researchers
Integrated data collection systems 
GIS, regional and spatial statistics 
Crowdsourcing and Citizen statistics 
New challenges in the measurement of vulnerabilities (economic insecurity, inequality, poverty) 
Use of privately held data for public purposes 
Social data mining 
Mission and governance of statistical office in the future 


Satellite Events

European Big Data Hackathon 2023

Monday, 6th March 2023

Eurostat is organising the forth round of the European Big Data Hackathon in 2023. 

The European Big Data Hackathon  gathers teams from all over Europe to compete for a statistical challenge. The teams develop innovative approaches, applications and data products combining official statistics and big data that can inform policy makers in pressing policy questions facing Europe.


Introduction to MOTUS: a data collection platform for HBS and TUS

Monday, 6th March 2023, 13:00-18:00

EUROSTAT has a long history in providing countries the opportunity to innovate their data collection processes. Innovation is in particular important for studies that face a high response burden, a decline in response rates, and a rise of collection costs. Amongst the most demanding studies are the HBS (Household Budget Survey) and the TUS (Time Use Survey).

In consortium with STATBEL and DESTATIS (respectively the statistical offices of Belgium and Germany), the MOTUS data collection platform was introduced to the Official Statistics. MOTUS is a data collection platform developed by the Research Group TOR of the Vrije Universiteit Brussel, and further developed by its spin-off “hbits”. In a recent ESTAT.F.4 funded grant project (CRŒSS), the consortium scaled up MOTUS from a TUS-related platform to include HBS as well. The goal of the CRŒSS project was to realise a CROSS-domain platform (HBS and TUS) that is also shareable within the ESS. The CRŒSS project and its main outcomes will be presented in a parallel session organised by ESTAT.F.4.

The goal of this satellite event is to introduce the participants to the MOTUS data collection platform. Starting from the angle of the GSBPM, MOTUS handles the (3) build, (4) collect and (5) process phases, and covers in part the (2) design and (6) analyse phases.

The first part of the workshop will explain to the audience how studies (TUS and HBS) can be created via the back-office of MOTUS, and how data can be collected via the front-office of MOTUS (both via mobile and web application).

After this introduction the participants are divided into groups, who will create their own study and their own data collection app via the MOTUS Discovery setup. The groups will be supported by a MOTUS expert.

The maximum number for this workshop is set on 40 participants. Participants will bring their own computer and need to be able to connect to the internet.

Documentation and guidelines on MOTUS will be provided.


Web Intelligence in Practice.  How to use content from the web for enterprise statistics?

Workshop – Friday, 10 March 2023 – 09:00 – 13:00

The ESSnet Web Intelligence Network (WIN) project is creating an environment where an array of non-traditional data sources can be accessed by members of the European Statistics System (ESS) and beyond.

The WIN is investigating new data sources to generate a significant added value for the official statistics, complementing or substituting parts of traditional outputs. These new data sources come with significant challenges for national statistical institutes (NSIs) as they do not follow the quality standards of the official statistics, which will require new methodology techniques. 

The use of innovative data sources in official statistics is a fact and has been well formulated in the foundations of Trusted Smart Statistics. One of the examples is to get information based on the content of the websites. Extracting data from enterprise websites to get characteristics is a part of a project currently undertaken by the Web Intelligence Network.

The course will cover a general overview of Web Intelligence Network and Web Intelligence Hub, demonstrating how the Web Intelligence Platform and Datalab can be used to acquire and process data from the web. Methodological issues of conducting surveys based on web data will be explained in dedicated sessions on data collection and data processing.

The course will also lead participants step by step on how to start the data acquisition with the Web Intelligence Platform and how to process them with the Datalab.

After completing this training course, participants should have basic knowledge of how to use Web Intelligence tools to conduct surveys on enterprise characteristics with respect to the methodological principles of the web-based survey.

To find out more about this event please visit our website.


Earth Observation and Machine Learning

Friday, 10th March 2023 | 9.00 - 13.00

In recent years, National Statistic Institutes have increasingly searched for new data sources in order to produce statistics more efficient, faster and more frequently. For instance, in 2015, the United Nations launched a plan to achieve 17 sustainable development goals. And in 2020, the European Green Deal was approved to be climate neutral in the EU by 2050. The challenge is not only to achieve these goals, but also to measure and monitor their status and progress.

Earth Observation (EO) is rapidly becoming a valuable source for producing statistics, as has been acknowledged by the National Statistic Institutes in the Warsaw Memorandum in 2021.

EO data, like satellite and aerial images, is usually freely available. In addition, the resolution of these images and type of observations, such as air pollutants, keeps increasing. 

However, EO data is usually not collected with official statistics in mind and requires state-of-the-art techniques to be processed and refined into official statistics. One of the techniques to process image data is supervised machine learning and one particular type of algorithms to deal with images is (convolutional) deep learning.

During this event, an open-source tool will be launched to support and execute machine learning types for the statistical production process. Additionally, several use cases will be presented where EO data is used to produce statistics.




Innovation Day 

Seeking effective ways for peer-to-peer knowledge sharing, responsive collaboration and training supporting innovation

Friday, 10th March 2023 | 9.00 to 13.00

Innovation in official statistics cannot be carried out in isolation. Moreover, upskilling the workforce, strengthening competences in data science, data engineering and data analytics is a prerequisite for innovation in official statistics aiming at improving efficiency in delivering new services and creating value for users.

In this framework, we seek mechanisms that will create, support and improve the innovation environment, in particular facilitating processes of innovation, creating conditions for spreading innovative ideas, through launching and executing innovation to integrating it into systematic statistical production across the European Statistical System.

Part of these mechanisms concern the capacity building, enhancement of collaboration and a learning environment with non-traditional delivery methods through peer-to-peer knowledge sharing. The latter is a key factor for innovation, for acquiring and developing new capabilities enabled by new data technologies and advanced methodological developments.

Indicatively, peer-to-peer knowledge sharing could take the form of activities bringing people together online or physically to exchange experiences, collaborate, develop and learn together, job shadowing, knowledge sharing and discussion platforms, sprints, etc. It can also be realised by providing support for developing and ‘softwarising’ specific methodologies and production pipelines, designing processes and framework, and support for reusing existing solutions and best practices.

Join this satellite event and help us identify together the needs (demand) to support and enhance innovation across the European Statistical System and effective methods (supply) for peer-to-peer knowledge sharing.



The draft outline of the NTTS 2023 conference is ready!

The draft detailed scientific programme is available below.

Scientific Committee

Monica Scannapieco

Istat Statistics Italy [...]

Alexander Kowarik

Statistics Austria AT - [...]

Remco Paulussen

CBS Statistics Netherlands [...]

Mojca Bavdaž

Emanuele Baldacci

Roeland Beerten

Bank of Belgium [...]

Diego Kuonen

Statoo Consulting amp [...]

Stefano Bertolo

Scientific Programme Officer at [...]

Markus Zwick

Lewis Dijkstra

Head of the Economic [...]

Monica Pratesi

ISTAT [...]

Practical information

There are no fees to be paid to attend the conference

Registration will be open from 23rd of January 2023 to 28th of February 2023

For your inquiries, please contact the organising committee at:


Organising Committee:

Albrecht Wirthmann (Chair)

Dario Buono 

Carola Carstens

Francine Kessler 

Maria Isabel Lazaro

Cristiano Tessitore