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:

The Guardian Tue 10 March 2009
https://www.theguardian.com/news/datablog/2009/mar/10/blogpost1

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

Data Journalism avant la lettre

From Data to Insight

Where there are data, there is insight. However, insight needs know how – know how about data sources, know how about analyzing data (with particular tools), about the context of the data and – last but not least – know how about presenting and communicating the insight.

.

William Playfair

These steps characterize what for some time now is called data journalism. More than 200 years ago we can find a brilliant example of ‘data journalism avant la lettre’ by the person who is thought to have invented statistical charts (or ‘lineal arithmetic’): William Playfair.

In his book ‘Lineal Arithmetic’ published in 1798 he presents several short articles about trade relations and the income produced by this trade. His aim is to describe long time developments not the actual situation in his difficult period of revolution and war. Mercantilism seems to be the context of his argumentation, but his primary interest surely is to demonstrate his innovative visual presentation.

.

Open Data 1798

Playfair gets his data from the House of Commons’ yearly accounts. Open Data 18th century!

Analyzing and presenting

Playfair’s data research is quite easily done. There aren’t big data to be traveled. Some time series of import and export data are the result. It’s  his presentation that marks the point!

Visual!!

Playfair presents his findings in a new form. The visual presentation of data is his invention, and he proudly explains this visual ‘mode of representing‘ in the introduction of his work. That’s scientific and convincing.

,

And to make his readers familiar with charts, especially bar charts, he gives a fascinating explanation leading from real-world  money staples to abstract bars of a painted chart:

‘This method has struck several persons as being fallacious, because geometrical measurement has not any relation to money or to time; yet here it is made to represent both. The most familiar and simple answer to this objection is by giving an example. Suppose the money received by a man in trade were all in guineas, and that every evening he made a single pile of all the guineas received during the day, each pile would represent a day, and its height would be proportioned to the receipts of that day; so that by this plain operation, time, proportion, and amount, would all be physically combined.
Lineal arithmetic then, it may be averred, is nothing more than those piles of guineas represented on paper, and on a small scale, in which an inch (perhaps) represents the thickness of five millions of guineas, as in geography it does the breadth of a river, or any other extent of country.’ (p.7/8)

 

Context

Charts and textual explanation go hand in hand. Playfair discusses all charts in short texts. For chart 3 (Germany)  – see above – it looks like this:

.

Communication

‘ … to aim at facility, in communicating information’ (p.8)

Communicating information is where Playfair excels. And he has studied how to do this and where his target groups are:

‘ …. we think it better to confine this work to mere matter of fact, as much as possible, being’ fully satisfied that in this small volume is contained what every man in this country, who aims at the reputation of a well-informed merchant, ought to be acquainted with; at the same time, that the Statesman will find in it things which he perhaps already knows, but which are here painted to the eye in a more agreeable and distinct manner than is possible to be done by writing or figures. It is on these grounds that this small, but compendious volume, claims the public attention.(p.4)

.

 The title has the message

Data Journalism: A Handbook, Guides and a Competition

A Data Journalism Handbook is about to be written by a group of well-known authors.  The structure of the handbook is ready, waiting to be filled with useful information helping data journalists to find interesting data and write exciting stories.

Click the picture to read the Handbook in Google Docs.

.

Official Statistics could …

… give a little help as this topic has been discussed on many occasions and has led to several documents:

.

Source: Statistical dissemination and communication (DissComm) – UNECE.

.

Some reflections about Statistical Storytelling …

— may also contribute

Storytelling revisited. IMAODBC Vilnius 2010

.

A data journalism seminar (in German)  may be seen as a kind of handbook too:

Datenjournalismus. Übersichtsseminar mit praktischen Übungen zum Thema Datenjournalismus, Wien 18.11.2011

.

And now: A Data Journalism competition

‘The European Journalism Centre, a non-profit based in Maastricht, has been running data training workshops for several years. It is producing the Data Journalism Awards website and administering the prize. “This new initiative should help convince editors around the world that data journalism is not a crazy idea, but a viable part of the industry,” says Wilfried Ruetten, Director of the center.

Projects should be submitted to http://www.datajournalismawards.org. The deadline is April 10, 2012. Entries should have been published or aired between April 11, 2011 and April 10, 2012. Media companies, non-profit organisations, freelancers and individuals are eligible.

–> More

Easy reading is damn hard writing.

Nathaniel Hawthorne

Timelines: past and future

Future

In the past nobody was perfectly right in predicting the future of (communication) technologies. This does not prevent from crystal ball gazing. It’s always  exciting!

And so Envisioning technology from Stockholm, Sweden did it and got an impressive sketch:

Interesting: linked data is mentioned within the interval 2011 to 2015.
Disappointing: interplanetary internet is far away -;) (Who will use this? In the Space elevator!)

‘“Envisioning technology” is a work in progress, researched and designed by technologist Michell Zappa.‘

Dip into the past

Internet (r)evolution documented in the light of various manifestos .

Original comment  from OWNI: ‘Depuis que le réseau est apparu, avant même que le terme Internet n’entre dans les usages, de nombreux usagers ont éprouvé le besoin d’écrire des textes pour encadrer ce nouvel espace et indiquer dans quelle direction il fallait l’orienter, esquissant chacun une vision du Net. ‘

OWNI presents its mission: ‘OWNI is a social media which brings you the very best news and prospective ideas on the ever-changing digital age – today in France, tomorrow all around Europe’. (English: http://owni.eu/. French: http://owni.fr/). OWNI gets money not from selling news but from developping apps for news, like the above internet timeline.