This could become a habit and is certainly unlikely to win me many friends but here goes anyway.
This morning the Guardian published a map of road accidents and deaths over the last ten years produced by the clever folk at ito World who have produced some of the most stunning visualisations of transport and OSM data that I have seen. So what do you think of this?
At first sight it is just a mass of dots which do not indicate any spatial pattern. If I zoom into my area I am presented with a complex array of symbols that indicate for fatalities the type of victim(cyclist, pedestrian etc) by colour, the age of the victim, the sex and adult/child status, the year of the crash plus further symbols for serious and minor injuries. Wow, that is a lot of information in one map!
I am struggling to understand any trends or patterns in the data even when zoomed in to my local area. I would like to be able to filter by year, perhaps view some trend information, perhaps filter the different categories, maybe understand whether the data is average, better than average or worse (when rated against what I am not sure but I imagine a transport) and even view some more info on the accident (assuming that is available in the opendata). Bottom line is a mass of points even when elegantly and cleverly symbolised is not giving me any insight.
The Guardian have been great advocates for OpenData and have achieved some breakthroughs in opening up geodata, they have also been at the forefront of the new discipline of data driven journalism , now they need to demonstrate how OpenData can provide new insights into important issues like road safety. We need more than pointilism or as I have said before “Just because you can stick it on a map …” although in this case there is certainly a lot of insight that could be derived from a more analytical product.
5 thoughts on “Another week, another map, some #opendata but where is the insight?”
I think the example itself isn’t important, it is the overall principle that matters – to unlock the real power of all this open data, we need to find some better ways of interpreting/analysing and cross-referencing datasets. Intesting post.
To be honest, I would say that this map conveys its message rather clearly: that road accidents affect everyone, everywhere. It’s a “political” map, rather than a technical map, and as such it’s pointilism is somewhat acceptable as I think it makes its message more striking.
What I would have changed is the use of the keys: make them clickable to switch on/off part of the visualization, rather than mere keys. This would have made the map data easier to analyse.
Very interesting to read your and Ken’s comments.
In response, I’ll describe what we were aiming for. We prepared this in time for the World Day of Remembrance for Road Traffic Victims. It was intended to be simply a presentation of the data – analysis will come later. The ‘insight’ is just that there is “an awful lot of death and injury”. We felt that people had been shown the headline numbers as statistics many times before and that we wanted to show what that data ‘felt’ like translated to individuals across the countries and in their area. The choice of symbols was to try to emphasise the fatalities as individuals – we found the addition of age and sex made each loss more human.
Given the focus on individuals, we didn’t want to aggregate them in any way. We were happy that the lower zoom levels would just be thumbnails, hinting at the mass of data, encouraging people to zoom in or search. Maybe we need something more to guide users to this.
Of course, this release wasn’t without constraints, and further releases will address filtering, neutral base maps, symbol overlaps, clickable details, etc. There are a number of other views onto this data available ( https://news.bbc.co.uk/1/hi/uk/8401344.stm , https://crashmap.co.uk/ , https://www.road-injuries.info/map.html ) and we wanted to start by focusing on the overall picture. We are just about to release a similar map for the USA, then follow with some more specific versions, and then some analysis.
Hopefully that explains a bit more about what we were attempting, and that we weren’t just “sticking it on a map” because the data had some coordinates…
Thanks for the explanation Hal. It would have helped if the article introducing the data had included some of that as context.
I remain unconvinced that this map helps to convey much more than that there have been a lot of accidents although getting that point over is important. I look forward to exploring the more analytical products that will follow.
I like this map for one simple reason…it is trying to show complex data in a simple, cartographically effective way. It is trying to go beyond what most maps do which is to aggregate data to meaningless totals and present them as a random collection of points (pointilism as you say). the road traffic accident data is well symbolised.
That said…you rightly point out that the scalability offerred by a web map makes the points cluttered and meaningless at many scales. It also needs a neutral basemap as the clash between the symbols and background are confusing.
So…much work to do to harness web maps effectively but at least we’re seeing an improvement over the single coloured, generic marker.