Each training course is limited to 50 participants.
All training courses will run in parallel.
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A job in official Statistics is like working for Google and CNN at the same time!
The impact of statistics in the society and innovation
Marcel van der Steen – Chief Innovation and Strategic Partnership Officer, NL
Vision on the future of official statistics
How to increase the impact of statistics for the society?
Correct data does not mean complete information
Innovation towards the future
Innovation 101
What is innovation?
Necessity to innovate?
Types of innovation (incremental vs radical, sustainable vs disruptive, closed vs open)
Government institutes and innovation
Bring theory to practice. Some examples.
Advanced Data Collection
Big Data
- Sensor data in various applications
- Satellite data
- The added value and challenges of the integration of private data
Communication and Dissemination
- Information Dialogue
Dissemination of Statistics and the role of the Media
Thomas Ruigrok – Director CBS Communication and News (CCN), NL
CBS and the Media
How to collaborate with the media so that statistics are visible to a wide audience.
How to make statistics ready for media – making data attractive
Communication Channels
How to use social media in dissemination (LinkedIn, Twitter, Instagram, Youtube and Facebook)
Why Facebook is not the right place to put your message as a Bureau for Statistics and why Linkedin and Twitter are perfect and Youtube is underestimated.
Innovations
Create media spokespersons of your experts.
Creating a Newsroom for all or your news messages
The success of spreading news messages under embargo
Target audience:
Strategists responsible for vision, mission and prioritization (resource planning)
Directors / Managers who are responsible for innovation strategy and management
Directors / Managers who are responsible for communication and dissemination
Statisticians working in research, development and innovation
Everybody who wants to know more about creating and increasing added value
Suggested reading:
To be provided.
Facilitators/ Instructors (short biographical note):
Thomas Ruigrok
Editor-in-chief (deputy) at the Central Bureau of Statistics (CBS). He is responsible for the entire media strategy of Statistics Netherlands. In addition, he is leading the Creation and Media team.
Ruigrok worked for over 25 years as a journalist for various media organisations, including a number of TV current affairs programs on Channel One of the public broadcasting organization. There he worked as a political reporter and editor-in-chief. He also directed documentaries about politics and sports for Dutch television. As a writer he published ‘Van Rem-eiland tot RTL4’, 40 years of commercial television in the Netherlands.
Marcel van der Steen
Chief Innovation and Strategic Partnerships Officer at the Central Bureau of Statistics (CBS)
Marcel van der Steen obtained a Bachelor's Degree in Automotive Engineering at the University of Applied Sciences in Apeldoorn in 1984. In 1990 he graduated from the Technical University Eindhoven in the Netherlands, and received his Master's Degree in Mechanical Engineering. Furthermore, he graduated from the Rotterdam Business School in 2013 with a thesis on Radical and Disruptive Innovation Management and received his Master’s Degree in Business Administration (MBA).
Previously he has been working for 13 years in the automotive industry and was member of the Board of Directors of ENGVA (European Natural Gas Vehicle Association).
In 2005 he joined the Netherlands Forensic Institute (NFI) as Manager of Research and Development. On 1 February 2009 he became the Advisor to the Board of NFI.
In September 2015 he started working for CBS to become the Manager of Innovation and Business Development responsible for the development of a vision based open innovation strategy. From 2019 he is the Chief Innovation and Strategic Partnerships Officer (CISPO).
Training material:
Quality Management in Official Statistics & Lean Transformation
Remi Prual, EE
Selected participants will be asked to take lead in group works.
Course description (incl. course objectives, course level (basic or advanced):
The course provides useful, both practical and theoretical advice on how to successfully manage the quality and implement well-known quality management approaches in public data valuation organisations such as coordinators of the national statistical systems and other national authorities involved in the production of the official statistics.
The objective is to demonstrate and explain how quality management and lean management approaches can be used to guarantee the quality and efficiency by rational design of the official statistics production systems and related capabilities. Common Quality Framework of the European Statistical System (ESS), related quality concepts and quality criteria, European Statistics Code of Practice and other commonly accepted and widely used quality methods and tools will be covered during the course. Lean management approaches will be presented for process analysis and group works during the course. Lean transformation is a term used to describe the strategic, tactical, and operational improvements that organisations undergo in order to create more value for their customers.
Participants will be expected to actively engage, and there will be opportunity for interactions both with the facilitators and other participants. For example, group works will be used to to ignite lively discussions and energise innovative thinking.
The course will enhance participants' knowledge about quality management in official statistics, related quality concepts, ESS quality criteria, the ESS Common Quality Framework, quality management models and methods used to monitor, assess, communicate and improve quality of official statistics.
Target audience:
The course is addressed to employees of organisations involved in the production of the official statistics.
Knowledge and experiences in quality management and production of statistics would be very useful for active participation in group works and discussions.
To maximise interaction, the number of participants for the training will be limited.
Suggested reading:
European Statistics Code of Practice https://ec.europa.eu/eurostat/web/quality
ESS Quality Assurance Framework https://ec.europa.eu/eurostat/web/quality
Generic Statistical Business Process Model (GSBPM) https://statswiki.unece.org/display/GSBPM
Facilitators/ Instructors (short biographical note):
Remi Prual has been involved in the enhancement of the quality of official statistics for close to 20 years via numerous projects and activities. He was the Quality Manager and Head of General Department in Statistics Estonia (in between 2004-2017). He is a Board Member of the Estonian Association for Quality (since 2016) and management consultant, advisor, trainer and expert with dedicated focus on valuation of data, metadata, statistics, information and knowledge. Remi is certified as an auditor for ISO9001, EFQM, CAF, ITIL, LEAN and several other quality management related standards and approaches.
Statistics in the era of Big Data
Prof. Audronė Jakaitienė, PhD, LT
Course description (incl. course objectives, course level (basic or advanced)):
The course focuses on opportunities and challenges of Big Data in Statistics. It aims to provide an overview of challenges by adopting Big Data technologies, as well as rethinking methods to enable sound statistical analyses on Big Data. The course will cover a variety of areas, all of which will be presented from the perspective of the user, who is a researcher.
Target audience:
The participant should be interested in expanding the knowledge of statistics regarding benefits and challenges of Big Data - this may be suitable for an analyst, subject matter expert or researcher. The participant needs no prior technical experience.
Suggested reading:
Radermacher, Walter J. "Official statistics in the era of big data opportunities and threats". International Journal of Data Science and Analytics 6.3 (2018): 225-231.
https://doi.org/10.1007/s41060-018-0124-z
Ricciato, Fabio, Albrecht Wirthmann, and Martina Hahn. "Trusted Smart Statistics: How new data will change official statistics". Data & Policy 2 (2020).
https://doi.org/10.1017/dap.2020.7
Friedrich, Sarah, et al. "Is there a role for statistics in artificial intelligence?". Advances in Data Analysis and Classification (2021): 1-24.
https://doi.org/10.1007/s11634-021-00455-6
Facilitators/ Instructors (short biographical note):
Audronė Jakaitienė is a Professor and Chief Researcher at Vilnius University. Prior to this, she held a position as Senior Economist at the Bank of Lithuania. She has also worked as Senior Expert (Economist) for the European Central Bank. Dr Jakaitienė is a Board member of the Lithuanian Statistical Society; Lithuania’s representative at the International Biometric Society. From 2011 she is head of Bioinformatics and Biostatistics centre at Human and Medical Genetics Department. From 2019 she is member of European Statistical Advisory Committee (ESAC). She conducts research analysing economic, medicine (with special interest to genetics), and education data.
Storytelling with statistics: learning from data journalism and data visualisation
Theo Jolliffe, Data Journalist
Frank Donnarumma, Data Visualisation Standards Lead
Office for National Statistics (ONS), UK
Course description (incl. course objectives, course level (basic or advanced)):
Since 2015 at the UK’s Office for National Statistics (ONS), we have used specialist data journalism and data visualisation teams to present our statistics to the widest possible audience. In this session, we will introduce our work and share techniques for writing about statistics for non-expert users and visualising your data for the greatest understanding.
We will discuss the differences between publishing and storytelling with statistics, choosing the right stories for the right audience, and how to engage and involve the reader using different storytelling techniques.
We’ll present a back-to-basics workshop on getting the best from your charts and appealing to a wide audience, with principles and techniques we apply at the ONS, including how we design our charts to be understandable by non-experts. We’ll also cover best practice and accessibility around charts and equip you with tools to pick better chart types.
We will also provide insight on creating content for different platforms including social media, and how to write clearly and concisely about statistics without ‘dumbing down’.
Objectives:
- Understand the difference between publishing statistics and storytelling
- Understand the audiences for statistical content, and their differing user needs
- Learn techniques for applying the principles of journalism to writing about statistics
- Learn how to write engagingly about statistics on different platforms, without sensationalising or dumbing-down
- Think about and understand your graphs through the eyes of you reader
- Improve your ability to make the most informative charts with your data
- Improve your ability to critique and improve existing charts.
Target audience:
Anyone responsible for communicating and disseminating statistics, especially to a non-expert audience. Could include statisticians, analysts and communications professionals.
Suggested reading:
Office for National Statistics: Project Cairo (portfolio of data journalism and data visualisation collaborations)
Financial Times: Visual Vocabulary (useful resource for choosing charts)
Nathan Yau (Flowing Data): Ask the Question, Visualize the Answer
Paul Bradshaw (Online Journalism Blog): Here are the angles journalists use most often to tell the stories in data part one / part two
Michael Blastland and Andrew Dilnot: The Tiger That Isn’t
Facilitators/ Instructors (short biographical note):
Theo Jolliffe, Data Journalist, Office for National Statistics, UK
Theo is a data journalist focussing on computational approaches to finding and telling stories about national statistics. Since joining the ONS just over a year ago he has been developing systems for semi-automated journalism in order to reach a wider audience with the information that is important to them.
Frank Donnarumma - Data Visualisation Standards Lead, ONS, UK
Frank has a passion for sharing best practice in data visualisation and works with other statisticians to communicate data using charts and interactive content. Frank joined ONS seven years ago as an entry level statistician working on house price statistics, later joining the specialist data visualisation team, learning the skills on the job.
Training material:
- Data Visualisation Introduction
- Data Journalism Introduction
- Visual Vocabulary chart choice aid Interactive and Poster
- ColorBrewer – help choosing accessible colours
- Ask the Question, Visualise the Answer – Great inspirational blog
- More about colour-blindness and colour-blindness simulator
Participants can also communicate with the lecturer on Twitter @frankman1000.
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Training Courses - Tuesday, 7 June, 2022
| ETA | GAMMA | OMEGA | EPSILON | |
| 08:30-09:30 | Training Courses Registration | |||
| Training Course 1 Statistics in the era of Big Data Trainer: Prof. Audronė Jakaitienė |
Training Course 2 Quality Management in Official Statistics and Lean Transformation Trainer: Remi Prual |
Training Course 3 A job in official Statistics is like working for Google and CNN at the same time! Trainers: Marcel van der Steen, Thomas Ruigrok |
Training Course 4 Storytelling with statistics: learning from data journalism and data visualization Trainers: Theo Jolliffe, Frank Donnarumma |
|
| Morning session | ||||
| 09:30-09:45 | Welcome. Course objectives and structure | Welcoming and introduction Course objectives and structure Participants and expectations |
Introduction of the lecturers and explanation and description of today’s course | Introducing Theo and Frank, discuss the objectives for the day |
| 09:45-11:00 | Big Data. What is it? Why does it matter for statistics? | Definition of quality and quality in statistics -Concepts and definitions -Evolution of quality management and quality in statistical production Quality in the European Statistical System (ESS) -ESS legal framework and quality criteria -ESS Common Quality Framework -European Statistics Code of Practice -ESS Quality Assurance Framework -Compliance assessment Quality frameworks and standards -Quality frameworks for statistical production -General quality frameworks -Standards for statistical production |
Vision on the future – How to increase the impact of statistics for the society (30) Getting your statistics in the news every day by using a Newsroom. How to use a Newsroom and what is the underlying vision and strategy? Discussion |
Understanding user types and choosing the right chart -Thinking about your content through the eyes of your reader. Some truths about statistical literacy among everyday people and how this should impact on how we talk about and visualize statistics. -Learning to use charts as editorial devices. How to extract stories from data and illustrate them effectively. Tips on picking the chart type that will best exhibit your data |
| 11:00-11:30 | Coffee Break | |||
| 11:30-13:00 | Education Data for Science. How much do we measure? How much do we use for policy analysis? Case study of Lithuania. Group work | 11:30–12:15 Lean management -Concepts and definitions -Principles and approaches -Kaizen, PDCA, DMAIC, Six Sigma -Voice of the customer -Value stream mapping -Examples of good practices 12:15–13:00 Group work 1: Quality in production |
What is Innovation? Definition and innovation types. Drivers for Innovation. Innovation within Government Institutes. Open Innovation and Co-creation. Management of Innovation. Discussion |
Critiquing and improving existing charts Practical exercises: -The visual vocabulary: Thinking about charts in terms of the statistical relationships they describe -What would you do: Critiquing some published charts and putting the morning’s lessons into practice by creating your own improved versions |
| 13:00-14:00 | Lunch Break Riverside Restaurant (Radisson Blu Hotel Lietuva) |
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| Afternoon session | ||||
| 14:00-15:30 | Presentation of group work. Discussion | 14:00–14:30 Group work 1: Discussions 14:30–15:00 Lean tools and techniques -Waste elimination -Capabilities -Daily instruments: Kanban, Takt, 5S, JIT, Jidoka etc -Examples of good practices -Technical solutions 15:00–15:30 Group work 2: Quality improvement action plan |
Innovation at CBS. Examples in practice. Communication on innovation. How to use social media as a successful tool in the strategy of dissemination. Using three kinds of content: Hygiene, Hub and Hero (3 H-s). | Applying the principles of journalism to writing about statistics -Understanding the difference between publishing statistics and storytelling -Thinking about your audience: why is it important to help the general public make sense of your data? -Some important considerations when telling stories with data – contextualising figures; how many decisions do you want the reader to have to make; where and how do you explain methodological information? -Writing like a journalist -Examples of data journalism using official statistics -Discussion: clarifying vs “dumbing down” |
| 15:30-16:00 | Coffee Break | |||
| 16:00-17:15 | How different is genetic data? Curse of dimensionality |
16:00–16:30 Group work 2: Discussions 16:30–17:15 Lean transformation -Strategic, tactical, and operational improvements for value creation -Examples of good practices and lessons -Roadmaps -Contexts |
Media monitoring: how to monitor your content in the media by using a fully automated application. Free discussion on today’s topics |
Writing your own story -Choose a dataset and create a story outline – this could be a headline and an intro, a chart or a social media post |
| 17:15-17:30 | Wrap-up and Conclusions | Discussion and conclusions | Wrap-up and Conclusions | Wrap-up discussion and main lessons learned |