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Hey look, the Goodyear Blimp!

 I've just seen a tweet from a US sportscaster on the Man Utd result

"With the win, Manchester United is 90.4% favorite to win PL title, per SPI. Odds were 77.1 pct before weekend."

Fair enough - but that isnt the way most of everyone else talks about football. The things people want evidence on are not the things that supply obvious data. This is why football is a different game than most US sport(s).

We want depth - but not of that stuff. A big project at the moment (separate from the MC work) addresses this.

And so does an upcoming article.

More soon.

Why People Love Maps

Hey! Look! A map!

We love maps because we know how to read them, but there are other reasons that many visualisations end up as maps and unfortunately the answer doesn't always have the end user in mind.

Designers love maps because-

- they are easily understood by users, most people can read a map

- they are easy to make - plenty of them online or as vectors to buy and / or trace

- clients want them because they see them, use them and know what they are

- (I also think that on a deeper level, our brains work like maps, with co-located repositories of certain stuff on tap and that we recognise this almost as looking in a mirror when we see one)

But anyway...

I think the main reason is that one of the cleanest and most robust data-sets available these days is map data - location , gis gps etc data. And people have trouble finding good data to build with. So they resort to map data.

When projects at the concept stage discuss data product possibiities, many end products are imagined. But when the investigation of available data (some say materials) happens, it often happens that the reliable data that the project requires is not available.

But there is always some map data and most things are based somewhere so that's that solved. It's a map.

The answer is to put planning into finding data that will fuel your true product aspirations.

The answer is to add data sourcing to the list of data science skills and data engineering aptitude. A data sommelier if you will.

Doing something about health? Don't just do a map because the government data sets are all geo based. Just as Apple finds new raw materials to build thinner laptops, or buys companies who can make 10% better batteries, so should data engineers insist on the right materials to build with.

They may not own enough domain expertise to understand where these data sets lie/ Is it them? Is it an IA job? It's probably one of the new jobs springing up these days.

All I know is "what data shall we use" is a vital pillar of any product concepting session.

People love maps and rightly so but in a hundred years they'll be literate in other useful visual tools - we can't make these without being interested in what they are made of.

We cant make these without getting good at sourcing and making new data.

BBC Dimensions at NYC MOMA!

 

As the headline says, Dimensions has made it to the new Talk To Me exhibition at the New York Museum of Modern Art, along with other work by BERG who made it.

Here is the MOMA 'Talk To Me' site with a bit more stuff

I commissioned it with BERG a few years back, when I was at BBC Vision. We were looking for was to make history/news accessible and interesting- So well done again folks at BERG - it is still excellent work.

Here's my take on it at the time.

Here's their take on it at the time.

Here's their write up of other BERG stuff at MOMA. 

 

The Pretending Layer, Zombies, a Venn How-to

As mentioned by Russell Davies, many hum-drum experiences are a lot better when they let you pretend.

One of the best examples of the use of a pretending layer to get people to pay attention is this from the US CDC - Centre for Disease Control. 

 
They obviously have a hard job convincing people to plan ahead for bad news - who would read this in their free time?

So they thought to draw attention to ideas of preparedness by getting people to consider something they are more likely to have considered preparing for - a zombie attack.

It sounds odd - but just as lots of teenagers have given serious credence to falling in love with a vampire, so have many people considered what they would do should the dead rise and walk the earth.

The clever thing the CDC saw was the the cross-over. They they assembled official advice pertinent to more likely disasters - you can fantasize, but also earn something.

Like most stuff it is  a Venn diagram. 

You need that cross-over, where the concerns of the fictional world (infrastructural chaos and possible death) cross over with the real world (infrastructural chaos and possible death).

You want to mitigate against too much reality (antibiotic replenishment, urban evacuation) because it is (thankfully) so alien to people as to be irrelevant.

You also want to avoid the excesses of fiction ("pack a Ruger 10/22 for decent mid-range protection and light ammo") as it is too far from the core needs of practical advice and possibly nutty.

So pretend needs to tread a line of credibility - as they say "all the best lies have an element of truth".

Sentiment Analysis hocum

What could he mean?

In last weeks Economist, there's a semi-decent article on reading sentiment from large masses of anecdotal data (tweets, mainly).

It's only semi-decent because it doesn't go the whole hog and say 'this doesn't work yet'.

Many smart senior people (un-named because their companies are involved in this snake-oil sale)  have confirmed this for me, saying "sentiment analysis software? don't bother"

The number of pitches from software firms I have attended in the last few years promising automated sensemaking of data says more about my patience than their products.

Not all is lost...

The data that twitter can supply is good for basic mentions, the basic smell of the situation - just not it's meaning -good/ bad, action required, not required. It's a canary in the mine, but it can't tell you what gas it is. This what many brand/ marcomms research dashboards supply - but many aren't optimised for the 'now take action' moment - they are mostly like webcams of rivers - an ongoing situation goes on.

What does work is smart , linguistics trained researchers, alerted by flagged moments in data inputs, then raking through data/ tweets to find meaning. Machines are useful for sorting these out but real meaning comes from human analysis still. Your engineers could help by writing some scripts that help the sifting/ alerting.

Everywhere data is used for analysis, a human is required for the real interpretation. The robots just aren't that smart yet.

Job done, but which one?

JWT have teamed up with Millward Brown research to visualise the annual MB 'Brandz' study.

They've done it by visualizing the brands as characters. Some work some don't. But it is cute. It's a bit like the schools in schooloscope (but their limiting of characteristics made them more legible)

As visualization it us questionable but I don't think that is the purpose.

Millward Brown are known for being a bit dry (though very reliable) and this sends a message that they are addressing that, or at least reaching out to ad planners who like this sort of thing, a key audience for them.

So it seems to fail in it's primary purpose of info dissemination but I don't think that was the prime purpose.

It's like the google Im feeling lucky button. It is a SUPFTAFABJ.

A seemingly useless product feature that actually fulfills a branding job.

By having it there, Google are saying, "We aren't that serious - we're Gooogly!"

And that is what MB are trying to do I think. 

Just because it is the pictures...

News from the Daily Mail, UK (3m 'readers')

I have just put my name to this piece on the Nieman Foundation for Journalism.

It basically says 'stop doing shit infographics'.

You can read the more reasoned argument for yourself.

I would add to their words the following:

Thinking that you can elaborate rumours with a graphic is insane. Graphics or illustrations make clear what was previously not clear. Keep any vagary textual.

The English press has spent a good century using our highly flexible and nuanced language for some of the most scurrilous and underhand speculation which stopped short of actual slander only because of deft opacity of the writing.

You can't do that with pictures. They expose you and commit you to showing. Which is possibly why the english press are so bad at using pictures. But that is another story.

Well done Juan and Alberto.

Visualisation, HypeCurves and Years of Dispute to come

Having highlighted Stephen Few's blog yesterday, an ex-BBC colleague, the super smart Lulu Pinney, pointed me to this discussion, where Few is manning the barricades,Rourkes Drift-like, against thousands of oncoming David McCandless fans as they rush screaming towards him.

He seems to deal with them pretty well (and for any 2000AD/Slaine fans it seems "he didn't think it too many")

Lots of metaphors there.

But the main thing is that Visualisation is firmly climbing the hypecurve. It takes public figures like David, (who I like and respect) to bring a new popular way to the table (not just Doing the work but Publicising it too - which he does very well). Without this approach and work, there would be no hype. Hype needs  a product, a face and point of view, an idea that is spreadable if tangible or not.

What happens next is that professionals like Few (or Nielsen/ Norman, before) (who are often more versed in reasoned debate rather than design-blog/ you tube emotionalism ) then point out that this stuff could benefit from some other (user) perspective. Their tone often rallies their opposite numbers who see thhem as aloof and outmoded.

Then there is a scrap that goes on for years. And it is a fight invisible to the general public.

The design press/blogs then move on to something else and declare "x is rubbish, as the plane loaded with all the counter arguments crashes groundwards.

Then nothing. Well, not nothing, just a period of no hype, heat debate, just lots of doing and practice, as people influenced by all camps - and others too set about their careers and making.

A few yesrs later, the industry has assimilated all the arguments at a wiser level and can draw on ideas of utility as well as engagement.

Absorbing new and counter-intuitive ideas takes time and it is natural to argue/ disagree at first, but just you wait. Soon we'll have fantastic data apps as common place just as we have largely good and usable websites as standard where we didn't ten years ago.

And it is all down to these different voices entering the debate, their messages gradually being absorbed and digested  into something good. Long may it continue. And it will.



A Few good men

This looks to be a very good blog from Stephen Few.

In the same way a generation of 'web designers' were infused/mentored by HCI veterans. (respect as always to Jakob Nielsen et al), we may be seeing a similar thing for the data vis community.

The recent generation of young turks is doubtless having fun with data scrawling but at some point it will pass people by unless there is a purpose or utility to it. They've got the engagement sorted. These things are mostly usable. What they are not is useful.

That is where peopel like Few come in. They work in analytics - using data for decision making. They are ideal real-life mentors, solving real life problems. They can point the way to thinking of these apps as tools for whatever outcomes.

So, read all of his blog - all the archives too (i will) before you go anywhere near popcorn-data-blogs again.

Solution in search of a problem

Just thinking as to why I shudder when asked to Interact with many visualisations - unless it is a pet interest or I know what I need from it, being asked to 'interact' with something throws me back to the days of 'hidden navigation' and other such bollocks.

It's because these things re put together by experts and they expect you lot to have the same level of interest in their often way too clever take on stuff.

"Lets the user explore" - well, you could do , like you could shw someone all the parts of the toaster rather than selling ot to them

I'm a bit more into task based stuff now anyway - tools that help people with business problems - people that need to show data as proof/evidence (in market research since you ask) . Maybe other people need such tangible problems too.

A colleague said of one visualisation - "its a solution in search of a problem".