A Language Beyond …

Hermann Burger, the so versatile Swiss writer once noted: “To be a writer means to have language beyond death”.
For Hans Rosling (1948-2017), working hard to make statistics not only understandable but also respected and used, this is equally true. Once thanks to his bestseller ‘Factfulness‘ and now also thanks to a newly launched idea: “The Project Rosling”.

Project Rosling

Project Rosling has its origin in the UN World Data Forum in Bern (October 2021) and wants to continue the spririt of this event. The project website paraphrases this as follows: ‘The Project Rosling aims to bridge the gap between the data and statistical community and a diversity of stakeholders to advance data ecosystems and provide the information needed for a fact-based worldview’.

And in even more detail: ‘The Project Rosling follows the Road to Bern, an initiative of the Swiss Confederation that aimed to prepare discussions before the 3rd UN World Data Forum 2021 in Bern and to engage the public in the 2030 Agenda (more information here). Over one and a half years, conferences, debates and activities with the general public created a momentum within the data and statistical community that the Project Rosling will seek to maintain and expand.
As such, it has two aims:
> Expand the data and statistics dialogue
> Deepen knowledge’
(-> go to source)

In memoriam

This meritorious project and its ambitious mission recall and continue what Hans Rosling pursued in his life and what was his interest and project. In an interview in 2013 he expressed himself as follows: ‘My interest is not data, it’s the world. And part of world development you can see in numbers’.

More about Hans Rosling:

The Challenge of Smart Data

Official statistics have never been exempt from the changes taking place around them. Numerous organisations at national and international level are constantly dealing with it and it is always interesting to see what the current 2019 assessment of future challenges is.

One example

Here is an example: Kurt Vandenberghe from the EU Commission (Directorate A) in his closing speech at the conference on New Techniques and Technologies for Official Statistics (NTTS 2019).

He focuses on data collection – especially smart data – , necessary qualifications and possible support from AI. Dissemination, contact to data users and questions about the comprehensible presentation and correct use of the data are left out. And also no reference to the potential of linked data, with which more can be pulled out of existing sources.

The following text includes the last part of Vandenberghes speech with the conclusion. I have adjusted the layout a bit with highlights:

‘So how will the future look like?

I recently came across a statement on a Eurostat website that in the course of the third decade of this century “Most if not all data is expected to be organic, i.e. by-products of people’s activities, systems and things, including billions of smart devices connected to the internet”. In that new context there is a growing need to examine and make use of the potential of “B-to-G”, business to government data transfer. This involves data from social media, mobile phones, Internet of Things, etc. There should be a new role for statistical institutions, captured by the term
smart statistics”.
I quote from the same Eurostat NTTS related page: “Smart Statistics can be seen as the future extended role of official statistics in a world impregnated with smart technologies.” Finally there is the issue of trusted smart statistics, again with an important role for official statistics, ensuring not only the validity and accuracy of the outputs, but also respecting data subjects’ privacy and protecting confidentiality.

Privacy and confidentiality
are a growing concern and we need more research on techniques and technologies helping to avoid misuses of data on individuals and enterprises.

I guess what we will see in the coming years is, however, not one technique replacing existing ones, but a
coexistence of and synergies between
established and new data sources
and techniques, of public and private ones, and of general and specialised providers that complement each other. This will include traditional questionnaire-based surveys, and administrative data sources, alongside new techniques such as big data. While some of these sources will provide basic structural information in high quality, others will provide more timely data on key trends.
What will be increasingly important is to have rich meta-information and knowledge about the quality of these sources and to guarantee and create trusted statistics, including trusted smart statistics.

And in all of this we cannot forget the role that
people with the right skills
will play. We saw already in the last few years that there is a strong growth in Europe in the demand for big data analysts and for managers who know how to deal with big data. This is only expected to grow further. To avoid a skills gap we will have to encourage young people to take up studies in these fields and educational institutions to provide corresponding courses. In the debate around “the future of work”(future technological change might endanger traditional jobs), there is one thing that is certain: the need for data analysts will grow further.

And I guess it is safe to say that they will be increasingly supported by Artificial Intelligence.
Artificial Intelligence
can help to make sense of increasingly large amounts of data, to check the validity and improve their quality, relieving statisticians from routine tasks. Artificial Intelligence could help us analysing data with greater scope, scale and speed. In fact, a lot of what I said before and what you have discussed during the conference relates – directly or indirectly – to artificial intelligence – although AI does not seem very prominent on the programme. Paraphrasing Isaac Asimov’s quote about computers, we could say ‘I don’t fear AI, I fear the lack of it’. And maybe we should especially fear a lack of a European AI. Europe needs to lead on AI and develop AI that respects European values and makes the lives of Europeans better. The Commission is therefore increasing its annual investments in AI by 70% under the research and innovation programme Horizon 2020. It will reach EUR 1.5 billion for the period 2018-2020, and resources will grow further after 2020. ‘

Smart data and appropriate processes

Smart data is the challenge in data collection. What has to be considered, how the processes have to be adapted in order to connect the different data sources to the standard of public statistics – this is the subject of discussion. Here, too, are two examples (from 2018).


Are Current Frameworks in the Official Statistical Production Appropriate for the Usage of Big Data and Trusted Smart Statistics? Bertrand LOISON Vice-Director, Swiss Federal Statistical Office, Diego KUONEN CEO, Statoo Consulting & Professor of Data Science, University of Geneva

From the abstract:
‘As a sequential approach of statistical production, GSBPM (“Generic Statistical Business Process Model”) has become a well-established standard using deductive reasoning as analytics’ paradigm. For example, the first GSBPM steps are entirely focused on deductive reasoning based on primary data collection and are not suited for inductive reasoning applied to (already existing) secondary data (e.g. big data resulting, for example, from smart ecosystems). Taken into account the apparent potential of big data in the official statistical production, the GSBPM process needs to be adapted to incorporate both complementary approaches of analytics (i.e. inductive and deductive reasoning) … . ‘

[4] Kuonen D. (2018). Production Processes of Official Statistics & Data Innovation Processes Augmented by Trusted Smart Statistics: Friends or Foes? Keynote presentation given on May 15, 2018 at the conference “Big Data for European Statistics (BDES)” in Sofia, Bulgaria
(https://goo.gl/RMfpfB).

Towards a Reference Architecture for Trusted Smart Statistics
Fabio Ricciato, Michail Skaliotis, Albrecht Wirthmann, Kostas Giannakouris, Fernando Reis EUROSTAT Task Force on Big Data, 5, rue Alphonse Weicker, L 2721 Luxembourg

From the abstract:
‘ …. we outline the concept of Trusted Smart Statistics as the natural evolution of official statistics in the new datafied world, where traditional data sources (survey and administrative data) represent a valuable but small portion of the global data stock, much thereof being held in the private sector. In order to move towards practical implementation of this vision a Reference Architecture for Trusted Smart Statistics is required, i.e., a coherent system of technical, organisational and legal means combined to provide an articulated set of trust guarantees to all involved players. In this paper we take a first step in this direction by proposing selected design principles and system components …. .’

Visual insights

In large amounts of data, information is hidden that can hardly be recognized with simple means. Special methods for data analysis are in demand and visualization techniques in particular help to overview the information gained and to pass it on in an understandable way.

Media have recognised the potential of statistical and other data years ago; this has led to what has been practised as data journalism in various large newspapers and also in newspaper co-operations.

The Datablog

A pioneer is The Guardian, whose datablog celebrated its 10th anniversary in March 2019:

Computer-assisted reporting

 But hardly anyone is ever the first. Especially when it comes to the visualization of data, there are examples that date back centuries.
But a new era has dawned with the use of computers in data analysis to generate interesting journalistic stories.
Of central importance here is the person of Philip Meyer, who began to use computer-assisted reporting as a journalist in the 1960s.

In his book Precision Journalism: A Reporter’s Introduction to Social Science Methods‘, published in his first edition in 1973, Meyer describes the demands on journalism that are still valid today and that are becoming data journalism.

‘There was a time when all you [as a journalist] needed was dedication to truth, plenty of energy, and some talent for writing. You still need those things, but they are no longer sufficient. The world has become so complicated, the growth of available information so explosive, that the journalist needs to be a filter, as well as a transmitter; an organizer and interpreter, as well as one who gath ers and delivers facts. In addition to knowing how to get information into print, online, or on the air, he or she also must know how to get it into the receiver’s head. In short, a journalist has to be a database manager, a data processor, and a data analyst. …..
In the information society, the needs are more complex. Read any of the popular journals of media criticism and you will find the same complaints about modern journalism. It misses important stories, is
too dependent on press releases, is easily manipulated by politicians and special interests, and does not communicate what it does know in an effective manner. All of these complaints are justified. Their Cause is not so much a lack of energy, talent, or dedication to truth, as the critics some times imply, but a simple lag in the application of information science—a body of knowledge—to the daunting problems of reporting the news in a time of information overload.
….
Today’s journalist must also be familiar with the growingjournalistic body of knowledge, which, therefore, must include these elements:
1 How to find information.
2 How to evaluate and analyze it
3 How to communicate it in a way that will pierce the babble of infor-
mation overload and reach the people who need and want it.
4 How to determine, and then obtain, the amount of precision needed
for a particular story. ‘

(Meyer, p. 1-2)


‘Data is not just about numbers’

Today’s data journalism is closely linked to the philosophy of open data. Data should be available in easily usable formats and be evaluable for everyone. But the claim of current data journalism – as represented by the Guardian authors – still follows the essential ideas of Philip Meyer.

‘We keep some of Meyer’s approach alive in how we do data journalism and we work alongside reporters to get the most out of the combination of data and specialist knowledge. Data is not just about numbers, and behind every row in a database there is a human story. They’re the stories we’re striving to tell. ‘ The Guardian Sat 23 Mar 2019

Examples

Since then, data-based journalism has set a trend. Many others publish data using graphics and are always looking for new ways to communicate the analysed data in an understandable way.
One of many examples is the New York Times, which celebrates Upshot’s 5th anniversary in 2019:

‘Five years ago today, The New York Times introduced The Upshot with the aim of examining politics, policy and everyday life in new ways. We wanted to experiment with formats, using whatever mix of text, data visualizations, images and interactive features seemed best for the subject at hand.


In the meantime there are networks that share their knowledge and offer help for data journalism or Data Driven Journalism DDJ. One of them (mostly in German) is datenjournalismus.net

Outstanding

Among the thousands of data-based stories and their visualizations there are highlights again and again. I don’t want to withhold my recent favourite. It is the analysis and visualization of the internal migration after the German reunification. Die Zeit presented this with a lot of effort and fascinating results in May 2019.

… and much more

Two Years Ago

He was a pioneer and a great inspiration for what public statistics always strives for: more visibility, more understanding and more resonance. Two years ago Hans Rosling (27 July 1948 – 7 February 2017) died too young.

Demanding and enriching was an encounter with Hans Rosling. His demand for public statistics was urgent and a prerequisite for his enlightening work: that statistical data should be open to all. Here he saw successes. It was and is enriching how he conveyed these data combined with a message. With innovative, precise, entertaining and always very personal presentations, he clarified what had happened and what developments could be desired. He was a realist regarding his effectiveness and yet always an optimist ….. better: a “possibilist”. What remains for me is how he taught to see with numbers – a constant challenge for public statistics.

“One little humble advice” he gave to his audience at the end of a presentation in 2013:

Full presentation here:  
DON'T PANIC — Hans Rosling showing the facts about population

It Goes On

Gapminder (“a fact tank, not a think tank”), with its innovative tools and commitment, continues to live with Anna Rosling Rönnlund and Ola Rosling.

And recently Factfulness, a book by the three (Hans Rosling, Anna Rosling Rönnlund, Ola Rosling) has been published with the subtitle “Ten Reasons We’re Wrong About The World – And Why Things Are Better Than You Think”

“Factfulness: The stress-reducing habit of only carrying opinions for which you have strong supporting facts. “


Statistical Self-Defense

No day without numbers in (social) media, in everyday life. And they not only want to inform us, they also want to orient us in one direction or the other.

And every day are among them deliberately or unintentionally false or misleading numbers.

Therefore, statistics must arm themselves against incorrect use of data and repeatedly teach the correct handling of statistical data.

There have long been numerous works on this subject. Here is another quite basic presentation by the Dutch journalist Sanne Blauw.

She picks out five statistical sins.

The fact that such presentations often use numbers themselves, which would also have to be viewed critically, does not diminish the value of her warnings.

What are they doing …. ?

… and how do statistical institutions present what they do?

In times of fake news and austerity measures, statistical offices are feeling more and more the urge to orientate the public about themselves and the usefulness and necessity of trustworthy statistics.

But how to proceed?

Public relations specialists know countless ways to get messages to the target groups. A traditional and usually quite boring way are annual reports. They’re usually just an obligatory thing and treated accordingly.

Annual reports as ambassadors for public statistics

Is this still a quite boring lecture under the changing circumstances mentioned above? Let’s look at a few examples.

 

#1 European Official Statistics

The European Statistical Governance Advisory Board publishes the report, which focuses on fake news and trust issues. It’s  mainly a control report with recommendations to be re-evaluated next year.

Not everyone’s reading but with some interesting facts about the European statistical infrastructure.

ESGAB-Titel-2017

‘ … this year’s Report focuses on the importance of good governance to maintain and increase trust in official statistics, ensuring appropriate access to administrative and privately-held data, and the practical challenges of coordinating NSSs.
Chapter 1 looks first at the challenge of maintaining and enhancing trust in official statistics when there is conflicting information provided by non-official sources or when statistical indicators fail to relate to citizens’ actual experiences. Access to administrative records and privately-held data is then examined, highlighting some of the difficulties encountered by NSIs and the need to ensure that the transposition of the new Regulation on General Data Protection into national law does not hinder access to data for statistical purposes. Finally, the challenge of coordination within NSSs is discussed, particularly in relation to ONAs.
Chapter 2 provides ESGAB’s overview of the implementation of the Code of Practice, ..
Chapter 3 reviews ESGAB’s activities over its first nine years, … ‘ (p.10)
ESGAB-Recommendations-2017
p.8

Glossary
European Statistics
Code of Practice (‘the Code’)
The European Statistics Code of Practice sets
the standards for developing, producing and
disseminating European statistics. It builds on
a common definition of quality in statistics used
in the European Statistical System, composed of
national statistical authorities and Eurostat. ….
European Statistical Governance
Advisory Board (ESGAB, ‘the Board’)
ESGAB provides an independent overview of
the implementation of the Code of Practice. It
seeks to enhance the professional independence,
integrity and accountability of the European
Statistical System, key elements of the Code,
and the quality of European statistics …..
European Statistical System (ESS)
The European Statistical System is a
partnership between the European Union’s
statistical authority, i.e. the Commission
(Eurostat), the National Statistical Institutes
(NSIs) and Other National Authorities (ONAs) ….

Some interesting facts given in this report:

gdp-EU

.

#2 UK

UK is of a similar type to the EU. Somewhat more systematic, with clear performance targets and evaluated indicators …. and tons of financial data.

‘This year has been a challenging one for those of us working in official statistics. Numbers were very much in the news in the run-up to the EU referendum and since. Examples of bad use of numbers and misrepresentation of statistics can cast a shadow over the validity and integrity of evidence. However, information that can be accepted and used with confidence is essential to good decision making by governments, businesses and individuals.’ …’ (John Pullinger,p.4)
‘The 2007 Act requires that the Authority produces a report annually to Parliament and the devolved legislatures on what it has done during the year, what it has found during the year and what it intends to do during the next financial year. This report fulfills that responsibility.’ (p.9)
‘STRATEGIC OBJECTIVES
To achieve its mission, over five years the Authority will focus on five perspectives:
a helpful, professional, innovative, efficient and capable statistical service will, we believe, serve the public good and help our nation make better decisions.’ (p.9)
.
‘KEY PERFORMANCE INDICATORS
The Authority’s Business Plan includes a number of Performance Metrics through which we monitor performance. Our performance against these indicators is summarised in the table below. It is important to note our targets are always used to stretch performance ..’ (p. 9)
And some interesting facts:

 

#3 Sweden

Sweden reports concisely on a few central goals and with the obligatory information on the organisation and infrastructure.

‘Statistics Sweden plays a key role in public infrastructure. Its task is to develop, produce and disseminate official and other government statistics. The Official Statistics Act sets out a number of criteria concerning statistical quality, in which statistical relevance is a top priority.’ (Joakim Stymne, p. 4)

‘Punctuality in publishing remained high and amounted to 99 percent. No corrections that were considered serious were made to the published statistics during the year, and there were fewer internal error reports than in 2016.’ (p. 7)


‘During 2017, Statistics Sweden has studied how its customers and users view the agency and its products in different ways.’ (p. 10)

#4 Switzerland

Switzerland differs from other reports in two ways:
– The report shows not only the activities of the Office, but also the state of the country according to various topics (the milestones of the multi-annual statistical programme, and at the same time a small Statistical Yearbook).
– And it is very personal, responsible persons behind the statistics become visible.

German and French only

‘Die erste Halbzeit der Legislatur ist um und damit auch die ersten zwei Jahre des statistischen Mehrjahresprogramms 2016–2019. Die darin festgelegten Ziele und Schwerpunkte bilden die Leitlinien für die Arbeit der Bundesstatistik. Die für das Jahr 2017 geplanten Meilensteine konnten erfolgreich umgesetzt werden. … … der Auftrag der Bundesstatistik wie folgt zusammengefasst: «Im Zentrum des Auftrags der Bundesstatistik stehen die Erstellung und die Vermittlung von nutzergerechten Informationen zu wichtigen Lebensbereichen unserer Gesellschaft. Diese Informationen dienen unter anderem der Planung und Steuerung zentraler Politikbereiche, deren Stand und Entwicklung mit Hilfe der statistischen Informationen beobachtet und beurteilt werden können.” (Georges-Simon Ulrich, p.5)

The state of statistics in the topic areas: e.g. Population

And the targets for the future: focal points and priority developments in the coming year:

Some interesting facts about structure and publishing

Staff

Publishing

.

# 5 Germany

Germany is taking a quite different approach: the annual report is more like a scientific magazine. With interviews and contributions to focal topics.

D-title

‘ People are being guided more by their emotions and less and less by facts – this is how we might sum up the post-truth debate which reached its hitherto climax last year, culminating in “postfaktisch” (post-factual, or post-truth) being chosen as the German Word of the Year 2016. …
I hope that all of the other topics dealt with in this report provide you with a good insight into all matters figure-related and that, in so doing, we can enhance your trust and confidence in official statistics.’ (Dieter Sarreither, p.3).
.
The table of contents shows how this report is designed as a magazine
.
Some interesting information about the office
.
This report also gives itself a personal touch and shows the responsible management personnel

.

# Conclusion

Annual reports are certainly not the most effective way of informing the public about the activities and importance of statistical institutions. They must be approached with other measures; they must be embedded in PR measures. Then they can – especially if they are well made – contribute a lot to understanding official statistics.

 

 

 

 

 

Synchronously Visualized

Once again:  the New York Times presents an innovative graphic, which you always want to watch again and again.

It’s this Downhill Race at the Olympics:

.

Start

Run

Finish

 

The link to the moving graphic is below this picture:

For Statistics?

It would be exciting to follow such visualizations, e. g. on changes in unemployment, GDP etc. of different countries from today-minus-x to today.

Easy-to-understand Statistics for the Public

In a recently published EUROSTAT publication, the authors demand innovative forms of communication from public statistics in order not to lose their socially important role. Among other things, they demand ‘…. to tell stories close to the people; to create communities around specific themes; to develop among citizens the ability to read the data and understand what is behind the statistical process.’

Telling Stories

The UNECE hackathon that has just been completed responds to this challenge.
‘A hackathon is an intensive problem-solving event. In this case, the focus is on statistical content and effective communication. The teams will be challenged to “Create a user-oriented product that tells a story about the younger population”. During the Hackathon, fifteen teams from nine countries had 64.5 hours to create a product that tells a story about the younger population. The teams were multidisciplinary – with members from statistical offices and other government departments. The product created should be innovative, engaging, and targeted towards the general public (that is, not specialists). There was no limit on the form of the product, but the teams had to include a mandatory SDG indicator in the product.
The mandatory indicator was “Proportion of youth (aged 15-24 years) not in education, employment or training” SDG indicator (Indicator 8.6.1).‘ (Source)

Winners

And the hackathon shows impressive results, even if only a few organisations have participated.

The four winners are:

My Favourites

My favourites are number 3 from the National Institute of Statistics and Geography (INEGI-Mexico) and number 2 from the Central Statistical Office of Poland.

Why?

The Mexican solution…

…is aesthetically pleasing and easy to use. The interaction is left to the user and can be individually controlled by him/her in the speed.

The diagrams do not stand alone, but are explained by short texts while scrolling.

The results are not just being accepted. Rather, the concepts are explained and questioned – statistics are presented with the methodological background.

The Polish solution…

…starts with a jourmalistic approach. Here too, the interactivity can be controlled by the user at the desired speed.

At the end, the authors also seek direct contact with the users; a quiz personalizes the statistical data and gives an individual assessment of where the users stand personally with regard to these statistics.

Success Factors

The two applications mentioned above combine decisive user-friendly features:
– visually attractive,
– easy-to-understand navigation that can be controlled by the user according to his needs,
– the journalistic approach,
– concise and instructive explanations,
– personalization,
– hints on the methodological background.

Many of the other applications show the frequently encountered weaknesses: Too much information should be provided, no courage to leave something behind and concentrate on the most important elements. And this leads to long texts and complex navigation with the effect that users quit quickly.

The Good, the Bad and the Ugly

Communication of statistics in times of fake news

In a recent paper Emanuele Baldacci, (Director, Eurostat) and Felicia Pelagalli, (President, InnovaFiducia) deal with the ‘challenges for official statistics of changes in the information market spurred by network technology, data revolution and changes in information consumers’ behaviours’ (p.3)

Three scenarios

The status-quo or bad scenario:

‘Information will continue to be consumed via multiple decentralized channels, with new information intermediaries emerging through social platforms, digital opinion leaders, technologies that reinforce belonging to peers with similar profiles and backgrounds, including in terms of beliefs.’  … ‘Under this scenario it is likely that increased competition from alternative data providers will put pressure on the official statistics position in the information ecosystem and lead to drastic reduction of public resources invested in official statistics, as a result of the perceived lack of relevance.’ (p.8)

 

The ugly scenario:

‘Big oligopoly giants will emerge by integrating technologies, data and content and providing these to a variety of smaller scale platforms and information intermediaries, with limited pricing power for further dissemination. In this scenario, data generated by sensors and machines connected to the network will increasingly create smart information for individuals. However, individuals will not participate in the data processing task, but will be mostly confined to crowdsourcing data for digital platforms and using information services.’
‘In this scenario, official statistics will be further marginalized and its very existence could be put in jeopardy. More importantly, no public authority with significant influence could be in charge of assessing the quality of data used in the information markets. Statistics as a public good may be curtailed and limited to a narrow set of dimensions. …  Official statisticians will appear as old dinosaurs on the way to extinction, separated from the data ecosystem by a huge technology and capability gap.’ (p.9)

 

The good scenario:

The authors do not stop here. They also see a good scenario, but a scenario that implies a huge engagement.

This scenario is ‘predicated on two major assumptions.
First, the information market will be increasingly competitive by sound regulations that prevent the emergence of dominant positions in countries and even more important across them.
Second, official statistics pursue a strong modernization to evolve towards the production of smart statistics, which fully leverage technology and new data sources while maintaining and enhancing the quality of the data provided to the public.
In this scenario, official statistics will generate new more sophisticated data analytics that cater to different users by tailored information services. It uses network technologies (e.g., blockchain, networks) to involve individuals, companies and institutions in the design, collection, processing and dissemination of statistics. It engages users with open collaborative tools and invests heavily in data literacy to ensure their usability. It strengthens skills and capacity on statistical communication to help users understand in transparent manners what are the strengths and limitations of official statistics.’ (p. 9/10)

 

Actions needed to face the challenges ahead

The good scenario already depicts some needed actions to be taken by official statisticians. The authors conclude with proposals that are not really new, ideas that have been on the table for some time but are not so easy to implement.

‘It is important to change mindsets and practices which have been established, in order to put in contact the citizens with official statistics, to make data accessible, to expand the understanding of their analysis, to support individuals, business and institutions in the decision-making process.

The key issue is how to be authoritative and to develop quality knowledge in the new and changing information market. It is important to know the rules and languages of the media platforms used for communication; to overcome the technicalities; to tell stories close to the people; to create communities around specific themes; to develop among citizens the ability to read the data and
understand what is behind the statistical process. In summary, put people at the center (overused phrase, but extremely valuable):
⎯ communicate statistics through engaging experiences and relevant to the people who benefit from them;
⎯ customize the content;
⎯ adopt “user analytics” to acquire the knowledge of the “users” through the analysis of data (web and social analytics) and the understanding of people’s interaction with the different platforms.’ (p.11)

And the concluding words call for external assistance:

‘It will be essential for statisticians to build more tailored data insight services and team up with communication experts to play a more proactive role in contrasting fake news, checking facts appropriately and building users’ capacity to harness the power of data.’ (p.12)