This week our data-journalists are going stir-crazy in their mid-summer hibernation. We're singing, training for the Olympics, taking a stroll through the history of thought...and playing with Lego: It's The Week in Data
Paule d'Atha désigne l'équipe des journalistes de données d'Owni : Julien Goetz, Sylvain Lapoix et Nicolas Patte. Twitter @pdatha.
Once won’t hurt – this week we’ll start off more on the LOL side of things, and end up getting a bit more serious.
Launched by Florent Maurin, Dalalalataviz captures songs by the great artists (Abba, the Jackson 5 … Britney Spears) in data visualisations, with hilarious results. If you feel so inspired, everyone is free to submit their own visual translations to this “open source” project.
The various sizes and colours of Lego bricks are perfectly suited to data visualisation and infographics, as illustrated by the Expoviz event and workshops. Lego has also been used to explain simply the principle of infographics: Moving from a messy data set which is then sorted and arranged, and finally represented visually.
Where do you stand on the scale of global obesity? After letting us know how many people were alive on the planet on the day we were born, and evaluating the extent of losses during World War II in comparison with our number of Facebook friends, the BBC continues its range of applications combining graphics, global data and high levels of customisation.
Here, the “calculator” asks you to enter your age, gender, weight and country, and then calculates your place on the global scale. The results can be quite surprising: the average weight in Jamaica, for example, is higher than in the United States.
Even on planet Data, we can’t escape sports news. Starting on July 27, London will host the Olympics. The Guardian Datastore has played its part by creating a special section devoted to 2012 Olympics data. This includes graphic comparisons between the three Olympic Games hosted by London (1908, 1948 and 2012), a complete list of British athletes competing in the competition, and more.
The section also points you towards some relevant visualizations, such as this specially-adapted map, made for the group Join In by Kiln, a specialist in this technique, who notably created The Carbon Map.
This map of the Olympics visualises the origins of British athletes according to their sport. While certain facts seem obvious (athletes competing in sailing come more often from coastal areas), other less familiar ones are highlighted. For example, the prevalence of the south as the origin of tennis players, the curious north/south balance within basketball teams, which overcomes all regions.
About a month ago, Simon Raper, a British statistician, tried to represent the history of philosophy and influences between authors. He inspired Brendan Griffen who reproduced his idea by scraping Wikipedia and selecting parts that mentioned “influenced by” or “influencing”. His methodology is explained here.
The result is impressive. Both in size (note the loading time) and in content. On this graph, produced with Gephi graphics software, the size of the nodes is proportional to the number of connections between two elements. The bigger the node, the greater the influence of this person. Not surprisingly, Nietzsche, Kant, Hegel, Hemingway, Shakespeare, Plato, Aristotle and Kafka dominate the connections. However, other connections are also worth a look: the strong influence of artists like Andy Warhol and Marcel Duchamp, for example.
The choice of graphics or type of visualization is essential in making readable graphics or data visualizations. To simplify this phase, certain tools have begun to appear, such as the table of visualization methods, which uses the concept of the periodic table of chemical elements.
Andrew Abela, a professor of marketing and a design consultant, has made a graphic about choosing graphics, in the form of a test. The main question is placed in the middle: “What would you like to show?”. Then, following your response (a comparison, a composition, a distribution, relationships) and the characteristics of the data (whether static, progressive, accumulative) that the reader wants, the graph that seems most appropriate is displayed.
The Juice Labs team has also produced an interactive version, but it’s less readable because it doesn’t keep all the elements on one page.
Here’s a beautiful visualisation to end this week’s edition: John Nelson’s work on worldwide earthquakes since 1898, represented according to their magnitude. John Nelson used data from the NCEDC (Northern California Earthquake Data Center), the USGS (U.S. Geological Survey) and the University of Berkeley, and the images came from a NASA image bank. Aside from the aesthetics allowed by the basic map, information on the most dangerous areas is clearly shown. John Nelson has also successfully visualised the major fires that have hit the United States.
A happy data-week to all!