How has Mexico moved from 2 cartels in the 1970s to 9 cartels today? That is the question the Mexican website Animal Político wanted to answer when in January 2015 they started to work on NarcoData, a data journalism project that shows the evolution of 40 years of drug dealing in Mexico, home to the most violent cartels in the world. Carla Pedret reports.
The origin of the project was a document Animal Político journalist Tania Montalvo obtained in October 2014 from the country’s Attorney General’s Office, after a request under the Mexican Freedom of Information law. Continue reading
Ben Fry published his book Visualizing Data in 2007, before the term ‘data journalism’ had entered the professional vocabulary. Since then, Fry has been developing Processing, an open source “language for learning how to code within the context of the visual arts”, and he is a principal at Fathom, a Boston design and software consultancy which has created visualisation projects for National Geographic; Bill, Hillary & Chelsea Clinton Foundation and Bill & Melinda Gates Foundation.
Catalina George asked him a few questions about his current work and his advice to aspiring data journalists.
Visualisation, a reinvented tool
For a better view of the world calories consumption, the user can see how much this differs from China to the UK @Fathom
One of your Fathom projects was a data visualisation for National Geographic’s “What the World Eats”. The graphic part can play a great role to enrich our perception and understanding of reality. But what does the development of visualisation mean for journalism?
I think what’s called “visualisation” has been around a long time for journalism. Otto Neurath was doing this in the 1920s. I think it’s been receiving more attention in recent years because we have the means to more easily distribute interactive works, which is a boon for more sophisticated takes on data. Continue reading
In a previous post I explained some of the considerations in deciding to use a map in data visualisation, and went into detail about mapping points and heatmaps. In this second part, taken from the MA in Online Journalism at Birmingham City University, I’m going to look at other types of maps: shape-based maps and image maps.
A more ambitious alternative to mapping points is to map shapes: in other words, instead of each data point being placed on a specific point on a map, instead different areas on that map are drawn and coloured/labelled according to the relevant data. Continue reading
When it comes to data visualisation, everyone loves a map. More exciting than a chart, easier than an infographic, it’s generally the first thing that journalists and journalism students alike ask: “How can we create a map?”
But just because you have some geographical data doesn’t mean you should map it.
Here’s why: maps, like all methods of visualisation, are designed for a purpose. They tell particular types of stories well – but not all of them.
There is also more than one type of map. You can map points, shapes, or routes. You can create heat maps and choropleth maps.
I’ll tackle those different types of maps first – and then the sorts of stories you might tell with each. But the key rule running throughout is this: make sure you are clear what story you are trying to tell, or the story that users will try to find. The test is whether a map does that job best. Continue reading
In a guest post for OJB, Ion Mates interviews Tom Levine and Roman Heindorff about the role of audio in data journalism.
Audiolisation (sometimes called ‘auralization‘ or ‘sonification’) is the process of turning complex data to sound.
Instead of using graphics and bar charts, one can represent the contents of a spreadsheet by assigning sounds to different kinds of data.
In the above example, the activity of newsrooms is represented by verses, phrases and different rhythms. The author is Thomas Levine.
Beginning to represent data as audio
Tom started playing with computers from an early age. His main interest was to design things towards them being easier to use.
In a guest post for OJB, Natalia Karbasova explains how, with no coding experience, she used German carpool data for the basis of a data visualisation project.
Some time ago I was working on a new blog on the sharing economy, lets-share.de. It was high time to add some data-driven stories visualising important issues of the sharing economy, which change our lives.
Mitfahrgelegenheit.de is the popular German version of Carpooling.com. I decided to create a visualization which would show carpooling patterns between cities in Germany and, possibly, reveal hidden connections. Continue reading