Archives for category: Chapter 5: Data Journalism

Matthew Ericson writes about when to map – and when not to map:

“[S]ometimes the reflexive impulse to map the data can make you forget that showing the data in another form might answer other — and sometimes more important — questions.

“So, when should you use a form other than than a map?

“1. When the interesting patterns aren’t geographic patterns

“2. When the geographic data is more effective for analysis”


Tom Steinberg of MySociety writes simply about visualisation:

“There are only two kinds of data visualization in the modern world. They are Story Visualizations and Answer Visualizations.

“Story Visualizations are those produced by one set of people with the goal of telling a story to an audience. Think of a newspaper graph showing deaths during a war, or a map showing where within the country unemployment is highest.

“The second kind of visualisations are Answer Visualisations. Answer Visualizations are produced to supply an answer to a single question posed by a particular person.”

Worth bearing in mind when you begin to visualise your data: are you doing it to tell a story, or to answer a question of your own?

A post on the Help Me Investigate blog expanding on the option described on page 64

While I’m blogging diagrams (see previous post), here’s a flow chart on gathering data that I published a couple weeks ago which attempts to clarify how you might obtain different data using different tools, depending on the type of data you’re after (click to see a larger version):

Gathering data - a flow chart

Thanks to Bas Timmers for emailing to point out that Swivel is no longer operating. There are plenty of alternatives on that list, but just in case you need another, try Number Picture, which hosts a number of particularly impressive template styles.

Another resource if you are looking to mix and map geographical data is GeoCommons. This not only has dozens of datasets that you can map using the site, but also allows you to upload and map your own data.  You can also combine data if they share the same piece of classification, such as country, city or region.

Kaiser Fung has a ‘Trifecta Checkup’ to help clarify visualisations. He writes: “All outstanding charts have all three elements in harmony. Typically, a problematic chart gets only two of the three pieces right.” The diagram below illustrates this – it’s an excellent reference point if you’re creating an infographic.

Kaiser Fung Trifecta Checkup

If you’re trying to decide what sort of chart or visualisation to use, try the Choosing a good chart (PDF) Poster by A. Abela. Also useful is the Chart Chooser by Juice Analytics, where you can also download Excel and PowerPoint charts.

Page 63 mentions DabbleDB, a service for creating, sharing and visualising databases. The service was closed in March 2011. Google Fusion Tables remains a useful alternative, as is the Firefox plugin SQLite Manager.

In ‘Closer Look: taking it further – resources on programming’ the website Scraperwiki is described as providing an environment for Python programming. The site has since added Ruby and PHP languages.