Visualisation of the year 2015

There was never any doubt about this one. It had to be Dear Data. Earlier this year, I posted a six-page handwritten blog post about it, which is not something I do all the time.

Other dataviz bloggers and tweeters with end-of-year lists have cited Dear Data because it’s different, or cute. I think it’s much more important than that. I think the detailed examination of the process, and the fact that the pace required constant innovation and experimentation from creators Stefanie Posavec and Giorgia Lupi, makes it a uniquely detailed exemplar for datavizzers present and future to read, think about and learn from. It doesn’t try to be perfect all the time, and that’s fine too. Many of the notes on production reflect on how things went a bit wrong (or in some cases, spectacularly wrong (and I am reminded not to put bottles of water into rucksacks without thorough checks)).

Over time, you get a real idea of personal style preferences and interests. Lupi is keen on symbols, which is something you see in her work with Studio Accurat too. One of the first pieces of theirs that caught my eye involved elongated triangles. I had been thinking about depicting movement in two dimensions. The obvious choice is arrows, but at a glance they can become terribly confusing as soon as the movement is not smoothly laminar. I then realised the Accurat triangles were much more experimental and not to be taken with such scientific conservatism; they didn’t work for me because I always take Cleveland’s advice: dataviz is a translation of data into vision, and for it to work the viewer has to be able to translate it back to numbers in their head – and I add and do so easily. Posavec’s work is generally more artistically informed and less about data in the journalistic or scientific tradition, yet somehow features more parallel lines and tree structures. I still think Phantom Terrains is an incredible piece of work, partly because it ticks almost all the Robert’s Interests boxes – maybe include some Neolithic monuments next time? – but also for the way it weaves together different types of data and design seamlessly.

Notably, none of the postcards contains a single axis! This is not the place for that sort of thing. Has Dear Data inspired me to do more? Yes, I think so, or even to publish it here and then try to drum up some funding to expand on it. So, expect to see my London noise pollution map and code appearing at some point in 2016. Why? Mostly because it’s surprisingly a lot of fun to collect data and make pictures from it.

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