[last updated October 2017]
A snapshot of a variety of current visual journalism
The New York Times’ most recent Year in Visual Stories and Graphics (scroll right down for data-driven examples)
Website of the annual Malofiej SND conference, in Spain, every Spring
There’s a slight US bias given this was done for an event there, but still a great data vis who’s who if you want to know what’s happening at the forefront of data visualisation.
Listen to the lastest discussions of what’s happening in the field with the fabulous Data Stories regular podcasts.
There are some really helpful, fully annotated remakes of some data visualisations on The Why Axis.
And for those just starting out in the field:
There’s also useful advice for charities starting out with datavis from NPC.
An excellent (and free) series of exercises to walk you through the fundamentals of working with data from the School of Data.
And a blog post I wrote on how to present numbers with the appropriate amount of detail. Rounding, significant figures, decimal places, that sort of thing.
Another illustrated blog post of mine on whether there’s something more interesting you could use your numbers to show (levels of interpretation of data).
An analysis of the simple but very effective Economist chart style by JP Koning.
And if you’re writing numbers look at the ONS’s style guide.
For design and layout Inkscape is a free, open source vector illustration programme. (To see its potential have a look at NRS’s work). For easy-to-access, but templated, graphic design solutions have a look at Canva.
For the tools with tiered pricing structures, don’t forget to ask about special rates if you are a student or a charity.
Not sure which tool to go to for a particular type of chart, look no further than Andy Kirk’s Chartmaker Directory, brilliantly illustrated with examples.
For newcomers to the field, have a look at DataBasic.io.
The Office of National Statistics have published their guidelines for creating infographics. More advice direct from organisations using datavis: National Records of Scotland and New Philanthropy Capital.
Style.ONS is worth mentioning again if you’re writing about statistics, also includes a section on data visualisation.
The Government Statistical Service have published lots of guidelines: see the ‘presenting statistics’ tab in particular.
Everyone should read When to use a map by NYT’s Matthew Ericson
For research, best source for UK accuracy and detail are OS’s maps. Either select that option on Bing or use Streetmap.
For more obscure and international requirements try Perry-Castañeda Library Map Collection
When creating maps, start with the ONS’s Open Geography Portal that allows you to download accurate geographical reference data.
Useful colour blindness simulator to check your work as you go
Designing research posters
While there’s a lot of advice out there, this captures the essentials well, from the Wellcome Trust.
Other reference material and resources
Andy Kirk’s tools for visualising and communicating data, books too
Data Driven Journalism’s useful resource for data journalism
School of Data does what it says in the title!
Alberto Cairo’s main recommended reading list on infographics (search his site for updates).
There are lots of people out there doing great work, but my nomination for being good at doing what you do in today’s environment would be the Government Digital Service. GDS. If the words digital, agile, iteration, users, data, design and openness mean anything to you you’ll find lots of interest on their blog. Both their digital and design principles are well worth a look too.
And if you want an insight into how the world looks to a designer?
Some of my favourite pieces of visual journalism you can find on this blog by searching under the tag example
The answer to improving your presentations isn’t to introduce infographics, one of Tim Harford’s three useful tips.
Useful, practical guidance from Jesse Desjardins here and here.
And a how-to guide from Nancy Duarte to present visual stories that transform audiences.
A good resource aimed at non-experts, to help them make sense of data visualisations which covers key terms, how data visualisations are made, factors that influence our experience with them and a chance to rate a few yourself.
Think there’s something I should include that’s not here? Please let me know!