1. Tell the reader what the data means
Tools like Tableau make it really easy to make exploratory visualisations, giving the user the ability to sift through the data and localise it to themselves. However, as tempting as this can be, the role of the data journalist it to tell the reader what the data means — if you have a dataset that includes the entire country but only a handful of locations are relevant to your story, an exploratory map isn’t the best approach. Aim for explanatory visualisations.
2. Simple is usually better
A quick glance through the examples page of d3js.org reveals a wealth of different and unusual ways to visualise data. While there are definitely occasions where an exotic visualisation method communicates the data more effectively than a simple line or pie chart, these are really rather rare. The Economist’s use of series charts to efficiently summarise an entire article in a tiny space demonstrates how effective the “classic” visualisation types are — there’s a reason they’ve stood the test of time (The Economist’s incredibly clear descriptions and simple writing style also really help here). Meanwhile, I don’t think I’ve ever gained any insights from a streamgraph, pretty as they are.
3. Code for quality
Ændrew Rininsland is a senior newsroom developer at The Times and Sunday Times and all-around data visualisation enthusiast. In addition to Axis, he’s the lead developer for Doctop.js, generator-strong-d3, Github.js and a ludicrous number of other projects. His work has also been featured by The Guardian, The Economist and the Hackney Citizen, and he recently contributed a chapter to Data Journalism: Mapping the Future?, edited by John Mair and Damian Radcliffe and published by Abramis. Follow him on Twitter and GitHub at @aendrew.