Deconstructed Viz – Male vs Female in the UK Houses of Parliament

Houses of Parliament Membership

This is a fairly powerful visualisation, but I’ve got a few problems with it…

1. What’s the story?

You kind of already know the answer before you see the results! So there are more male MPs than there are female – that ain’t news! This is a common weakness in many visualisations – it’s not showing you anything new, but rather its a pretty picture of a statement we already know to be true?

2. What’s the purpose of the visualisation?

Do we even need a graphic to get across this particular message? Is it adding any real value – we’ve already made the very bold statement in the title of the visualisation – “More male MPs were elected in 2010 than the total number of female MPs ever”. That clear statement is arguably enough on its own – I’m not sure the graphic is doing anything to drive that argument home?

3. Make it a fair argument!

It’s a leading question and that’s what I really don’t like. The author had a clear agenda – to highlight discrimination against women. Don’t take sides and try to let the user explore the data and draw their own conclusions.

Visualisations can and should be powerful – they should prompt a debate and discussion, but they should be based on a level playing field for that debate, with no obvious bias.

4. More questions than answers?

What about the context? The first thing I think when I see this graphic is ‘ok, but how many women actually stood for election?’.

We are implying that people aren’t voting for women, but we aren’t backing that up with evidence. We aren’t telling the whole story and we have to be very careful when we do that.

This is only part of the picture. Try to paint as complete a picture as you possibly can. That’s not always possible, but try to at least be honest about the gaps in your data.

Don’t leave them wanting more, or more confused than they were to begin with.


To the Red Planet

This is a great visualisation that I spotted in WIRED magazine. This is an excellent technique for summarising a reasonably detailed data set in a very clear and immediately digestible way. A great example of what can be achieved with a bit of careful thought and some good design.

Mars Viz
Paul Butt

The 60s space race to the Moon was a mere sprint compared to the decathlon to Mars. Using Nasa’s archived data of both US and international missions, Paul Butt’s graphic illustrates the history of Mars exploration by robotic probes, and the many successes and failures along the way. “For each launch, I read through the mission planning and execution to interpret what the mission hoped to achieve, and what it actually did,” explains Ipswich-based Butt.

The result is a story of how these mission objectives grew more ambitious: ranging from the US Mariner 4’s first successful fly-by in 1964, which took 21 pictures, to landing rovers on the planet — something the Americans, again, recently achieved with Curiosity. Although the Americans dominate the successes, the graphic also shows the determination of the Soviets in the face of repetitive failure. In December 1971, two years after the US conquered the Moon, the Russian Mars 3 was the first to manage a landing; sadly, it malfunctioned after 20 seconds. “[The Russians] were remarkably ambitious,” Butt says. “They were trying to drive rovers across the Moon’s surface in the 70s — it took the Americans another 20 years to be able to do that on Mars.”

You can read the original WIRED article here. Credit to Stephen Kelly and the guys at WIRED for this content.

Vincent’s Vortices

A NASA animation of changing ocean movements. This visualization shows ocean surface currents around the world during the period from June 2005 through December 2007. The visualization does not include a narration or annotations; the goal was to use ocean flow data to create a simple, visceral experience.

The size and shape of the flows are influenced by wind, density, gravity and temperature.

This visualization was produced using model output from the joint MIT/JPL project: Estimating the Circulation and Climate of the Ocean, Phase II or ECCO2. ECCO2 uses the MIT general circulation model (MITgcm) to synthesize satellite and in-situ data of the global ocean and sea-ice at resolutions that begin to resolve ocean eddies and other narrow current systems, which transport heat and carbon in the oceans. ECCO2 provides ocean flows at all depths, but only surface flows are used in this visualization. The dark patterns under the ocean represent the undersea bathymetry. Topographic land exaggeration is 20x and bathymetric exaggeration is 40x.

This visualization was submitted to the SIGGRAPH 2011 Computer Animation Festival, but it wasn’t selected by the jury.


First read in WIRED (UK) magazine, credit to original authors.