Bikes are a longstanding love of mine.  When I last worked in an office that wasn't part of my own house, I became an enthusiast for cycling to work, even when it involved changing into office wear in the building's disabled loo, not being able to have a shower, and taking an elderly bike up to the fourth floor.  I started writing about biking to work, the obstacles and the incentives.  Now that my morning commute involves ambling upstairs from my kitchen with my fifth cup of tea, I have no need to cycle to work, so I find myself biking somewhere for lunch, or trying to do my grocery shopping by bike.  And after questioning the usefulness (and beauty) of infographics in data visualisation in last week's post, I thought it was only right to show the attractive image below.

Created by Nau from the data collected by Bikes Belong, this image is more of a poster than an infographic - in fact, the only section of this which I would describe as a true infographic is the 'bar chart' about three times as many new bikes as cars being sold annually.  For the rest, it is simply an attractively designed way of communicating data; a less thoughtful design could simply have involved typing these numbers onto a stock image of people on bikes.  So, given that this demonstrates all the worst criticisms of infographics (what's the point of it?), why am I showing it here in the hallowed halls of Thunderfly?

Well, I think it is important in this context to consider the audience for this image.  This is the kind of picture that could be printed out and posted up on a noticeboard at work; the bright colours and cartoon-y images draw attention and could start the discussion about transport between workplace and the home.  It acts as a tool for advocacy, showing that there is the possibility of reducing the reliance on cars and increasing bike travel, whilst asking us to consider the need for more facilities (secure bike parking, bike lanes, showers or just increased consideration from drivers) and how that might be achieved.  And it is inclusive, by showing cycling as a real alternative (particularly given the financial costs of running a car), rather than simply as a leisure activity, or as something only done by people in tight lycra.

So, this isn't really an infographic.  It's more than that.  It's an illustrated thought-provoker. So what do you think?

A few weeks ago, the Guardian's datablog published an article on the backlash that seems to be gathering against infographics.  Although they describe it as "gathering steam", some of the sentiments they describe aren't new: it's just a pretty picture but it doesn't actually tell you anything; the design choices obscure the actual data; is this going to be the pie chart that looks like Pac Man again?  In fact, here's a critique of infographics which is nearly two years old.

The main point of the Guardian's article is that tools that have developed in recent years allow people with all sorts of expertise and specialisms to create infographics (rather than just those who know about data, or about design).  Sometimes, this means that the folks putting those infographics together don't follow some of the rules that you'll hear about often at Thunderfly; and sometimes an infographic is used in the same way as stock photography - simply a colourful illustration to break up the text, rather than communicating a message on its own terms.

Now, I know that infographics are just one branch of visualising data, and I'm not averse to a bit of colour.  But I found myself in sympathy with the critics when I encountered this infographic, created for the political social media aggregator, Yatterbox.

Here are the issues as I see it.  First of all, though, you'll need to take off those sunglasses.  No, I don't know why the designer has chosen a tartan background, unless he particularly wanted to bring out the way it clashes horribly with the Union Jack header.  So, first issue: the designer wants to pack in all sorts of information, using a number of different techniques, but the background image draws immediate attention to itself at the expense of communicating their insight.

The stacked bar chart of social media usage isn't too bad; the colours used are related to the service in question (turquoise for Twitter, dark blue for Facebook, poor old Flickr gets white) so the design draws upon our pre-existing brand knowledge as a design shortcut.  But adding white space between the bars makes it tricky to draw comparisons, and the rounded corners also change the shape, and therefore the accuracy, of the sections.  I'm not convinced that the orange bar for RSS feeds looks more than twice the size of the blue Facebook bar.

The bar chart on 'When they joined Twitter' has left me questioning the scale.  Is that a percentage of the people they follow? Raw numbers? I can see that early 2009 was a popular time to get a Twitter account, but how easy is it to compare the second half of 2009 with the first half of 2010?

I'm not sure how relevant - or indeed reliable - the infographics are that are generated from Klout data.  Listing the Twitter handles of the 'most influential' or 'most influenced' means that I don't know whether they're real people or just bots that retweet from elsewhere.  And finally, although the last few snippets are interesting, they're not really 'Trends to Watch'.

What do you think? Are infographics just treated like pictures? What are the positives of the example I've picked out? And does it matter whether infographics are accurate?

I have a longstanding penchant for taking data visualisation into the real world, whether taking pictures on my holidays of 3D pie charts in the wild, or being enchanted by handmade visualisations with bar charts in the flower beds.  So I was delighted to see that there's a data visualisation side to the #Occupy protests. Occupy George is a project to use the ubiquitous dollar bill as a way of circulating infographics about the distribution of wealth within the United States.  Templates are provided to enable participants to print the infographics (onto their own money!) and enter them into circulation, though I'd hazard a guess that they might not last long, either being withdrawn as defaced currency, or kept as a souvenir by somebody who ends up with one in their pocket.

The graphics are simple, clear and get their message across perfectly.  Top marks also for accompanying each of the infographics with a link to the original source of the data, whether that's a conclusions from a think tank report, analysis of public data, or even a 'fact check' piece on a Michael Moore speech.  It strikes me as an elegant way to protest about a matter dear to all our hearts - money.

I've just got back from spending four weeks in North America, taking in California, Oregon and spending some time in my second home of Vancouver, British Columbia.  Driving through California provides a chance to consider how much the culture of the west has influenced perceptions of America (especially via Hollywood).  I also had plenty of time to think about quite how big California is, and as a consequence how big (and diverse) the USA is.  Of course, as soon as I got home, I spotted this amazing map, which led me to similar conclusions from the comfort of my desk.

Using a dataset from the US Geographical Service, the National Hydrography Dataset, the author has colour coded the frequency of different terminology for waterways across the US.  'River' and 'creek' are ubiquitous, and so are symbolised in grey.  The colours clearly show the patterns of settlement and expansion throughout history.  As Watkins himself comments,

Lime green bayous follow historical French settlement patterns along the Gulf Coast and up Louisiana streams. The distribution of the Dutch-derived term kill (dark blue) in New York echoes the colonial settlement of “New Netherland”... Similarly, the spanish-derived terms rio, arroyo, and cañada (orange hues) trace the early advances of conquistadors into present-day northern New Mexico. Washes in the southwest reflect the intermittent rainfall of the region, while streams named swamps (desaturated green) along the Atlantic seaboard highlight where the coastal plain meets the Appalachian Piedmont at the fall line.

The area I visited, the west coast, shows its Spanish influences in Southern California through the appearance of 'rio' and 'arroyo', with 'slough' and 'fork' appearing further north as I travelled into Northern California (wetter, forested) and on to Oregon (the start of the Pacific Northwest, home of the rainforest, i.e. wettest).  It is fascinating to see the patterns emerge in other parts of the country, and reminds me that the history of this country has been action-packed during the short time since Europeans first arrived on its shores.

A similar map has been pulled together for the UK, by James Cheshire at Spatial Analysis.  

The debate is already on as to terms that Cheshire might have included, issues of rerouting of water courses and whether local waterways are even named in the original dataset.  Why not check it out and join the debate?

 

 

Last week, Warren wrote about Apple's underwhelming visualisation of the carbon footprint of the iPhone 4S.  Of course, the launch of the product was almost immediately overshadowed by the untimely death of one of Apple's founders, Steve Jobs.  Here at Thunderfly, we have often held up Steve as an example of an excellent presentational approach, and so it seems fitting to mark his passing by pointing out a tribute based on data visualisation, put together by Twitter - the place where I, and many others, found out the news.  In the days after Jobs' death, as many as 5 of the top 10 trending hashtags referred to him, so Twitter collated the following image, made up of tweets under the "#thankyousteve" hashtag.  Although not without its faults, this image is a moving demonstration of the impact that Jobs has had on the modern world.

 

 

The new iPhone was unveiled this week with the usual frenzied discussion about its merits, or lack thereof. Omitted from the media coverage was any conisderation of the phone's environmental impact. Unsurprising perhaps, when there is the sexier fare of talking assistants and errr, debating the model number, but correspondants can't be excused by a lack of data to go on.

Following a run-in with Greenpeace a few years ago, Apple now publish an environmental report for every new product they launch. The reports are not particularly detailed, but they do include estimated greenhouse gas (GHG) emissions for a product over its entire life cycle (i.e. including those caused by using the phone).

Here is the data published for the new iPhone 4S *pie chart klaxon*:

Pie charts are, at best, overused as a data visualisation technique (at least this one isn't 3D). This  does quickly convey some useful information: while production unsurprisingly accounts for the biggest chunk of emissions, customer use makes up almost a quarter of the total. The presence of recycling is also of note, a handy reminder that breaking down and resuing electronics is not an energy-free, or even safe, activity.

So we have a mildly interesting breakdown of the emissions sources alongside a total figure of 70kg of GHGs. Overall, I go away with a relatively good feeling about the product's environmental credibility, mainly as the pie chart seems to be made of wood.

What is lacking from this display is a comparison over time, in particular we have no context for the total GHG figure which is the data central to any environmental analysis. Apple have already published comparable data for the previous two iPhone models, it would have been very easy to include them all in one place. It only took me about three minutes to do the bar chart below, which is very revealing. Indeed, if one were cynical maybe it would be a bit too revealing for Apple to publish themselves:

This chart doesn't tell us what a kg of GHG really means (one of the climate change agenda's difficulties is the intangibility of its core principle) but we do know that the figures should be decreasing over time. 

Compiling the data from three pie charts in separate reports into one bar chart shows that across most parts of the lifecycle, iPhone emissions are on the rise, with a 27% jump between the iPhone 4 and 4S.

Not good.

What's more the seemingly relentless rise in production emissions was only offset on the iPhone 4 by a huge drop, of almost 50%, in those estimated from customer use. Sadly, there isn't much detail published in the methodology for these figures. I have no reason to doubt them, other than to point out that such a large change is... well... surprising.

So what has this simple exercise told us?

1. Pie charts can convey a very limited amount of information and, like other data visualisations, are easily sullied by daft colour schemes. Bar charts almost always trump pie charts.
2. Context is key: by adding in comparison over time we get a much better understanding of the numbers, even for pretty abstract stuff like GHG emissions.
3. Apple's environmental reporting might be a (small) step in the right direction, but poor visualisation and manipulation of the data is obscuring an increasingly disturbing trend in their environmental record.

[Thanks to Darragh Browne from Carbon Calculated, whose initial spot prompted this post.]

We are shameless magpies here at Thunderfly, and so I am never happier than when passing on a tool or tip that I think people might find useful.  And so it is that I'd like to highlight a tool which Warren and I have mentioned during our courses, but not yet on the blog - the Junk Charts Trifecta.

First things first, time to give credit where it is due.  Junk Charts is a reference to Edward Tufte's concept of 'chartjunk', coined in the classic (and much recommended by us) Visual Display of Quantitative Information.  As Wikipedia tells us, Tufte says:

The interior decoration of graphics generates a lot of ink that does not tell the viewer anything new. The purpose of decoration varies — to make the graphic appear more scientific and precise, to enliven the display, to give the designer an opportunity to exercise artistic skills. Regardless of its cause, it is all non-data-ink or redundant data-ink, and it is often chartjunk.

The blogger behind Junk Charts, Kaiser Fung, has said he aims to recycle the chart junk he encounters into junk art. The blog showcases the occasions on which heinous crimes against data visualisation are brought to his attention, and he does his best to extract the meaning (like sunlight from a cucumber, as Farquarson would have it) and display it in a more meaningful way.  

Now, we've covered checklists (including one from the estimable Stephen Few, which Warren put to good use) before, but Fung has developed this triangular checklist, which he calls the Trifecta, and which might conceivably be easier on the eye if you print it and put it up by your desk.  Successful data visualisations have all three elements in harmony, and Fung checks both the original visualisations, and the ones he develops to replace them, to ensure they meet the criteria.

You can address the three elements in any order, but perhaps it makes sense to start at the top and ask what the question being asked is - what question is the data answering?  This was something mentioned by John Kay in his series of superhero recommendations.  You could be overstepping the mark if you use data to assert something that it doesn't actually show.

The second point of the triangle asks what the data says.  This is the section where your expertise or area of interest guides you to pick out the important information that you wish to communicate.  It is hard to offer concrete guidance in this area; this is where we remind you that you are the expert, and to have the confidence in the decisions you make.

Finally, the trifecta asks you to check whether the chart or figure you've designed communicates both of those aspects.  If all of these three elements are working for you, you're onto a winner.

 

The concept of your lizard brain is one that Warren has mentioned before, but it was brought home to me, repeatedly and painfully, over the weekend.  Having happily left my stabilisers behind 25 years ago, I spent last weekend in Wales, relearning how to ride a bike. I wanted to get to grips with riding off road, going downhill and over rocks, roots and even jumps. 

I’d love to pretend this is me, but it really isn’t. Photo by Dave Cheeseman.

The mantra of the weekend was ‘brakes are not your friend’; the idea is to reduce your speed when you approach an obstacle, then release the brakes while actually riding over it.  This sounds straightforward, until your lizard brain takes over.  I approached a small step and released my brakes as instructed. The front wheel dropped and the back wheel followed, by which time I was going a bit quick, and my lizard brain leapt in, jamming on my front brakes as hard as I could.  Over the handlebars I went, in what was – apparently – a spectacular yet graceful encounter with the ground. 

The term ‘lizard brain’ was coined by Seth Godin, to describe the resistance we all encounter when we try to do something challenging.  The lizard brain is a remnant from our evolution, and it wants us to make life as easy as possible.  It wants us to be warm, fed, comfortable and preferably not being chased by large predators.  When we’re not in a survival situation, the lizard brain still has an impact, but now the drive is to make life comfortable and to avoid modern difficulties or hazards.  This weekend, the lizard brain kept yanking on my brake levers.  When you’re presenting data, the lizard brain makes you put this year’s numbers into a chart or table that you originally designed last year, or the year before.  After all, nobody complained, so it must have been alright. 

The lizard brain suggests that you stick to using slides you’ve prepared from previous presentations.  It makes you revert to using bullet points and complex diagrams that take ages to explain.  And the lizard brain always says that, because your colleagues think it’s OK to take an hour to prepare for a 30 minute presentation, you can only spend that amount of time too. 

We all do it.  We set out with the best intentions: this time, I’m going to redesign this data and make it really shine; this time, I’m going to ride with the brakes off; and the lizard brain pops up.  But if you want to overcome your lizard brain, here are three things that I’ve taken away from my weekend on a bike, and that you could bear in mind when you need to overcome the resistance to visualising your data or preparing your presentation differently.

1.  It’s uncomfortable

Your instinct is to be cautious, to not make yourself a target for criticism, to do what’s universally accepted.  This is, of course, totally sensible.  So when you’re trying to do something new, expect it to feel awkward.

2.  It takes time

Habits, whether working habits, or the habits of a lifetime (so far) of riding a bike, take time to break.  It also takes time to learn new habits.  Try and factor that time in, whether it is blocking off some time in your diary to look at good examples elsewhere, to finding images, or to make sure you put aside as much time as you can to prepare a presentation.

3.  It brings its own rewards

Yes, it feels awkward, or difficult to justify to colleagues.  Yes, it doesn’t come naturally, especially when you’re changing long-standing habits.  But yes, it does feel good when you’re able to fight back and overcome your lizard brain.  Not just achieving whatever it was you wanted to do: design a new approach to communicating numbers; give an excellent presentation; get that funding; but also knowing that you’ve had to consciously decide to do things differently.

 

A search for 'Worst Infographic Ever' reveals a crowded field jockeying for the honour of ultimate sacrilege against Tufteism data presentation. Infographics are *not* something I had planned to cover on this blog - the time and skills required to produce one are far in excess of those available to most people looking for the best way to present their data. I also like to offer friendly, constructive advice on data presentation. Having said all that the latest dumb-shell from Microsoft (albeit not the first) is too rant-worthy to pass over. More importantly, it also offers an extreme reminder of the importance of simplicity in everyday data presentation:

Out of data on 11 survey questions displayed on this monstrosity only one - "How well do you understand cloud?" - is displayed in anything like an intelligible format, albeit with pointlessly rounded bars and a distracting cloud (geddit?) floating across the middle. The remainder is a dizzying tour around the world's worst ways to present your data. Looking around CloudWorld we find bar charts curved around hot air balloons, a flattened 3D bar chart on a race track and - incredibly - a transparent, diagonal, cylindrical, stacked 3D stake bar whose sections don't add up to 100%.

Remarkably, all of this bar-loney is put in the shade by the "57% Email" (probably the first thing you noticed on the graphic) hovering over CloudWorld's sun, as the question it seemingly answers floats off into the heavens. Even in the unlikely event of sun-rays becoming a credible means of displaying data, there are still three major flaws:

• the survey answers are ranked in no discernible order
• having to turn one's head to read content is unacceptable. Text should be horizontal because *this is the way we read*. Remember the Microsoft sun next time you label an axis.
• most staggering of all, the 57% email figure displayed so prominently compared to the others *isn't even the highest figure* - 58% of respondents are using cloud computing for 'servers'. This is an extreme example of how one can include all the data while heavily skew what the reader perceives on the page/screen (perhaps in this case, for commercial reasons).

OK, enough with the unloading on Microsoft, let's nerd this up with a five-minute Thunderfly redesign:

 

Straight away, the reader can see that servers and email are *both* well out in front as usages of cloud computing. Scanning down the list, the reader can quickly see the most and least common usages and easily pull out any data of particular interest to them, and not obstructed by the heavy editorialising of the author (of course, the author will always decide which data is to be displayed, but those decisions must be credible).

Now, I am not (yet) living in a nerd bubble. I realise that while my worthy bar chart displays the information in a clear manner, it may not contain quite the level of marketing pizazz Microsoft are looking for. So by all means, Microsoft, continue with CloudWorld as a backdrop (even if it does look strangely familiar), but don't let it get in the way of your data.

And for us mere mortals who don't have money to burn on fancy infographics, Microsoft's latest disaster is a testament to the wider perils of putting form before function.

(Hat-tip to 2toria for originally posting the infographic).

 

Despite the holiday mood, there's still plenty of financial news about; the UK, Europe and the USA continue to make headlines, while they grapple with the ongoing economic slump.  I was prompted to think of this by a posting from a friend on Facebook, who was trying to put the numbers of the recent American budgetary wranglings into a comprehensible context:

• U.S. Tax revenue: $2,170,000,000,000
• Fed budget: $3,820,000,000,000
• New debt: $ 1,650,000,000,000
• National debt: $14,271,000,000,000
• Recent budget cut: $ 38,500,000,000

Remove 8 zeros and pretend it's a household budget.

• Annual family income: $21,700
• Money the family spent: $38,200
• New debt on the credit card: $16,500
• Outstanding balance on credit card: $142,710
• Total budget cuts: $385

Making the broader economic context accessible is really important; all of us are affected by the financial turmoil, so broadcasters, analysts and commentators have to make considerable efforts to get the public interested in the numbers behind the doom-laden headlines. Warren and I often remind people who come on our courses that if you're using a figure, it needs to do something that a simple table can't do (this was also something I mentioned in an earlier post here).  The Economist's 'Daily Chart' blog has taken a number of approaches to show different pieces of the financial picture, and they obviously subscribe to the same rules, as they often use tables, both online and in the printed publication. Here's one from earlier this month.

Even though the table layout is simple, there's a lot of information and it does require a bit of thought to engage with it.  Of particular interest is the fact that countries in this table are ranked on a composite measure - that is, the Economist's team have calculated each country's rank for the first three measures of indebtedness, and then combined those to produce the rankings shown in the table. Once you've grasped that fact (even if your understanding of how they've done it, or even what those measures actually mean, is a bit hazy), it means you can quickly extract some basic facts.  Who's worst off? (Japan). Who's best? (Sweden, of the countries they've decided to show). Are there any numbers in that table which jump out at a casual viewer? (What's going on with Norway's net debt?).  And if you're so minded, you can dig deeper.   

At the other end of the scale, the Economist's team also produce interactive graphics (something that their colleagues on the print edition aren't able to do), allowing the audience to explore the numbers intuitively.  In their post "Owe dear", the table above is supplemented with a clickable world map. The colour of each country demonstrates each country's debt, as a percentage of their GDP.  Colours are used in an immediately understandable way, going from green (not too bad), through orange, to red (oh dear indeed, particularly from a UK point of view).  Rolling over each country shows the percentage in number terms, and clicking through shows a time series of debt across a number of categories. Some of those graphs come with a health warning - they're stacked line charts, so are tricky to read (as Warren commented in his post on stacked bar charts), and they don't all start from the same year (the UK data goes to 1987, while Germany's numbers start in 1991 and France's in 1994, with no explanation as to why), but there's a lot of information, presented in an attractive and engaging way, enabling comparisons to be made, or suggesting connections - look, debt increases in all categories, Government debt doesn't change too much, financial debt increases enormously compared to household debt - in a way that would be less likely with separate charts.

But for a completely different approach to making the big economic picture comprehensible, there's still nothing quite like the short animation created by Nigel Holmes.  Called "The Surplus and the Debt", this isn't the sort of approach that is open to everyone, but it does show another way of adding context to the big numbers being bandied around.  It opens a conversation about the numbers - and at the end of the day, that's what anyone who is presenting data or information really wants, isn't it?