Over the last few months there has been a shift in how we are seeing news media use data, in that the tools and skills are now embedded enough in mainstream news organisations (and blogs and other sources) to see instant responses to particular news stories.
Perhaps not surprisingly a lot of this has been related to the entertainment business. So I was fascinated to see how the record company Beggars Banquet “seeded” the new album by the the British band XX with a single fan and saw it go around the world. Read how they did it here and here. The artist and technologist Aaron Koblin has long been a leader in visualisations and has frequently presented at Manchester’s FutureEverything festival and his work was the inspiration for this particular P.R. event. You can still watch the visualisation on the website created specially for the event.
Big album launches have large budgets and a long-lead time – and in this instance – as the “stream” was being hosted by themselves the record company were able to feed this data into their planning; but we’re also seeing people beginning to use regularly available data sources, APIs and feeds to show things visually. Again, relating to the music industry, this week’s announcement of the shortlist for the Mercury Prize (which is an annual award for the “best album of the year” in the UK) had an effect on the iTunes chart position of many of the lesser known or older albums on the list as mapped here.
The Emoto project, which involved FutureEverything’s Drew Hemment tracked emotion online (via Twitter comments) over the period of the Olympic and Paralympic games.
I’m sure there are many other recent examples. What is interesting is that (a) these visualisations are becoming (at least for the time being) “news stories in themselves as they evidence visually the stories behind the data (b) they show the range of approaches and data sources that are out there – some readily available; some more restricted; and (c) they provide compelling examples that those of us looking at releasing “public data” can use as examples and inspirations.
I’d be interested in any information about other visualisations that you’ve seen and have impressed you – and any thoughts on what these mean.