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

Tim Berners-Lee and the World Wide Web’s 29th birthday

Just two quoted sentences as a suggestion to read the whole story here:

The divide between people who have internet access and those who do not is deepening existing inequalities — inequalities that pose a serious global threat.’

‘The web that many connected to years ago is not what new users will find today.’

LOD MOOC

Massive Open Online Courses (MOOC) are available worldwide and offer tons of topics, also about Linked Open Data (LOD). An easy way to enter the semantic web.

Two examples:

HPI

snip_opehpi

The Hasso Plattner Institute, Potsdam provides, for some years now, a course in Linked Data Engineering with a certificate. I did it some years ago and enjoyed it.

FUN (INRIA)

snip_lodcourse2

The French platform FUN offers a LOD course, too. (Thanks to Adrian at zazuko.com for the hint)

And books

Step by step Bob DuCharme introduces RDF, SPARQL, LOD …

snip_ducharmesparql

.

snip_ducharmesparql-preface

Look at the Elections

18 October 2015

On October 18, 2015, Swiss voters elect a new Parliament for the next four years.

snip_201510181systemSource: https://www.bk.admin.ch/

More about Swiss elections here

For the National Council (200 members), 3,802 candidates and more than 22 political parties take part.

And the winners are …

The polling stations closed at 12 AM. The results arrive canton by canton and are presented in an interactive visualisation – minute by minute.

snip_201510181.overview

Results as of 5 PM

By clicking one of the symbols, the details for a canton appear.

snip_201510181detail

The results are updated in a database, and a script generates a visualisation on the spot. An easy way to follow the elections!

It’s the Statistical Atlas of the Federal Statistical Office that enables this presentation. And it’s no longer Adobe Flash needed to do it ;-).

100 Years

Comparing statistical visualizations over a period of 100 years is quite rare. The newly published Atlas of the Swiss Federal Statistical Office offers just this possibility.

1914

100 years ago Statistics Switzerland published a Graphic-Statistical Atlas. It was a wonderful visualization of dozens of topics and developments. All the diagrams and maps were hand-made and of superb quality.

Atlas1914

2015

In order to honor this great work, Statistics Switzerland did it again. A facsimile of the old Atlas is now accompanied by quite the same diagrams and maps but filled wth data from our century. With this technique, a visual overview of changes during the last century becomes possible and gives fascinating insights.

Atlas2014mak

The Atlas is available in Geman and French at http://www.bfs.admin.ch/bfs/portal/de/index/news/publikationen.html?publicationID=6327

Accidents

1901-1910 original visualization

Atlasunfaelle1900.

2001-2010 updated visualization

atlasunfaelle2000.

Births

1901-1910 original visualization

Atlasgeburten1900.

2001-2010 updated visualization

Atlasgeburten2000

Your Life – Our Life – Best Wishes for 2015

What would YOU do with these data sources?

UNdata, Institute for Population and Social Security Research, Population Reference Bureau, GeoHive, timeanddate.com, Exploratorium, Cardio Research Web Project, US Geological Survey, Geoscience Australia, Global Volcanism Project, Carbon Dioxide Information Analysis Center, Intergovernmental Panel on Climate Change,National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, International Programme on the State of the Ocean, Food and Agriculture Organization of the United Nations, US Energy Information Administration, BP Statistical Review of World Energy 2014, Live Science, Discover Wildlife,World Wide Fund for Nature, ICUN Red List, California Department of Parks and Recreation, Enchanted Learning,Astropro ©1997-2000 by Richard Nolle, Wikipedia.
.

BBC had an idea

BBC had a great idea personalizing these data to our life and visualizing developments that arrived during our lifetime.
2014-12-30_BBC1.
2014-12-30_BBC2.

 And: blogstats wishes a Happy New Year!

SEO: Abbreviate and Facilitate Conveying Information

Copperplate Charts

When William Playfair started using visualisations in his books he saw it as a means to bring information faster to his readers:

2014-08-11_IntroPlayfair

From William Playfair’s ‘Lineal Arithmetic; applied to shew the progress of the commerce and revenue of England’, 1798

And he did it with copperplate charts, like this:

2014-08-11_copperplate

 

Search engines

Today search engines have the same ambition: to open up information fast and efficiently. And tons of articles help making  this better than competing information providers. The following table does this in visual form like Playfair would have done (?).

2014-08-11_125944

For statistical websites these elements play a positive role: Cf, Lq, Ln and Ta. Some work has surely to be done for Sr and Ss.

Aerial Views

Depict reality with photograps has a long tradition: On Wikimedia Commons the Swiss National Library published a series of old and stunning aerial photographs made by the pioneer of ballooning Eduard Spelterini (June 2, 1852 – June 16, 1931).

2014-05-31_wikimediacommons

http://commons.wikimedia.org/wiki/Category:Eduard_Spelterini

 Alps

CH-NB_-_Matterhorn_-_Eduard_Spelterini_-_EAD-WEHR-32053-B.tif

Matterhorn, January 1 1910

CH-NB_-_Mont-Blanc-Gruppe_-_Eduard_Spelterini_-_EAD-WEHR-32070-B.tifMont Blanc, January 1 1909

Egypt

CH-NB_-_Aegypten,_Totenstadt_-_Eduard_Spelterini_-_EAD-WEHR-32040-B.tifEgypt, Town of the Dead, January 1 1904

CH-NB_-_Aegypten,_Pyramiden_von_Gizeh_-_Eduard_Spelterini_-_EAD-WEHR-32044-B.tif

Egypt, Pyramids Gizeh, January 1 1904

More >>>>> http://commons.wikimedia.org/wiki/Category:Eduard_Spelterini