Data visualization isn’t something most people get all het up about.
This is a pity, though, because we live in a world that is swimming in a sea of data. More than at any time in the past, massive amounts of information are being collected, sorted, collated and used. Where is it getting used? Governments, NGOs, Charities, and good old fashioned corporations. Where is it getting collected from? You.
As I discussed in my last post, the amount of user data out there is just staggering. I won’t go into that again, because this time I want to focus on the best uses for that data. And the best use is data that ultimately improves something: makes a better consumer experience, a better school system, a better program for distributing water and food in emergencies.
But it’s very hard, conceptually, to wrap your mind around the masses and masses of data we now have. Spreadsheets are wonderful tools, but they don’t exactly capture the imagination. And if you can’t get your message across about why a particular change should be made or what the impact of a particular event has been, then you’ve effectively said nothing at all.
For this reason, there is an increasing recognition of the importance of how we communicate the data that we have. There are a lot of different techniques out there. Some of these are more businessy, and some of them are more arty. My favorites are the latter, but it’s also important to keep in mind what the purpose is–not just “ooh, neat, it’s a graph made out of a bendy straw”, but “blimey, we should do something about this…”
It’s amazing what you can uncover when it’s put in the right format. For instance, the size of the world suddenly became a lot clearer when I looked at this map of countries superimposed over Africa. Want a new perspective on the glass ceiling? Just have a look at this map of the percentage of women in senior management positions (circa 2009). Neither the US nor the UK are in the top 20.
Just as revealing, though in a very different way, is Digital Urban’s ‘London Twitter Island’. Now, you could map the same data to a more traditional heatmap (showing density of tweets in different areas of London) but something about this imaginary map is much more engaging than that could ever be. It makes you think really differently about the places (the real places) to which it relates.
That’s why I do get all het up about data visualization: I think there are so many situations where we could be doing a better job of getting information out there in a way that it will actually have an impact. It’s not just about gathering and processing the data–the key step is generating understanding.