The Art of Transforming Data into Great Stories

What happened last week in the world of data visualization? This category provides you with remarkable visualizations – they can be remarkably beautiful, remarkably interactive or just remarkably interesting. Visualizations differ on so many levels, and so does their content. Let’s take a look at what week #13 brought us.

Scaner of 100 Goals Shot by the Trident

The Spanish sport magazine Mundo Deportivo devoted several visualizations to the goal scoring abilities of FC Barcelona’s superstars Messi, Suárez and Neymar.

A couple of weeks ago we presented a tennis-related visualization by the Financial Times. Since in sports it is all about results that are usually displayed as numbers and enriched by statistics, it therefore appears logical that sport journalist base their stories on data. So did Mundo Deportivo in the field of football. The journalists integrated the visuals about the three top scorers as header of the main text. Since the handling is unusual, those responsible decided to add small notions that help understanding and handling the visualizations correctly. That works very well and increases the usability. Furthermore, the single categories are consistently created and easy to access – although some Spanish knowledge might be useful for international readers.

What is missing? A link or at least a disclosure of the data source. That won’t ruin the nice design and would improve its credibility. The outstandingly successful trident will most probably keep on scoring in the next weeks – so why not updating the graphs and improve it. Once the source is clearly evinced, this visualization will be even more convincing.
Scanner 100 goals - Messi, Suarez, Neymar

Videogame Collapse

To be fair, the following is not a classical journalistic story, nor are the concrete data sources available. Nevertheless, it is very well done, data-based and definitely tells a story. Since it is basically advertisement for a computer game, it tends to be overdramatic in text. However, it deserves it place at this week’s recap. Have a look at the video game introduction ‘collapse’.

In figurative sense the user is patient zero of a virus and thus the origin of a worldwide pandemic. The underlying question is how long it takes for the user to let the world collapse. He or she playfully interacts by taking decisions that have a direct impact on the development of the pandemic. You can set any starting point you want, for instance your home address. The possible choices are based on real data; therefore, you might find your favorite supermarket or the pharmacy that you trust on the list. Even though the lists of possible answers are not complete, it is impressing how well real life data in incorporated in the game.

Apropos data: the user needs to actively look out for more information about the sources of the data in use, and will just receive vague answers. Even though that mantra might be boring by now, we can’t stress it out too much: do yourself and your readers the favor and name your sources as concrete as possible. You will be rewarded with credibility and trust. Apart from this, the video game developer demonstrated with this public mini game that data can be processed in a playful context. Undeniable it is fascinating (and a bit scary at the same time) to see how the virus is spreading.
Video Game Collapse

Income in Comparison

We just talked about sport and video games, which are quite entertaining topics. But let us get a bit more serious and talk about money, more specifically about income of different age groups. Surprisingly, this time the nostalgic but popular saying that everything was better in the old days, bears a tiny little bit of truth.

The visualizations by the Guardian enable the user to interactively explore and compare the income of different age groups with generations in the same age in the last decades. All visualizations are based on line charts that the user can filter. The great thing about it is that the default settings can be changed in accordance with the user’s life situation, for instance into a person of 35-39 years and from France descent. As the usage of multiple line charts suggests, the visualizations themselves are not spectacular – but straightforward and very easy to understand. Also a dynamic and partially funny text is included, hence, the interpretation of the charts is supported. Furthermore, not only a comparison between age groups of one nationality, but several nations such as UK, France and Australia are added to the filter. This options make it easy for the users to tailor the charts according to their own characteristics.
income historical comparison

About the author : Eva Lopez (DW)