This is so much a blog post as a dumping ground for bits and pieces relating to Olympics data coverage…
BBC Internet blog: Olympic Data Services and the Interactive Video Player – has a brief overview of how the BBC gets its data from LOCOG; and Building the Olympic Data Services describes something of the technical architecture.
Computer Weekly report from Sept 2011: Olympic software engineers enter final leg of marathon IT development project
Examples of some of the Olympics related products you can buy from the Press Association: Press Association: Olympics Graphics (they also do a line of widgets…;-)
I haven’t found a public source of press releases detailing results that has been published as such (seems like you need to register to get them?) but there are some around if you go digging (for example, gymnastics results, or more generally, try a recent websearch for something like this: "report created" site:london2012.olympics.com.au filetype:pdf olympics results).
[PDFs detailing biographical details of entrants to track and field events at lease: games XXX olympiad biographical inurl:www.iaaf.org/mm/Document/ filetype:pdf]
A really elegant single web page app from @gabrieldance: Was an Olympic Record Set Today? Great use of the data…:-)
This also makes sense – Journalism.co.uk story on how Telegraph builds Olympics graphics tool for its reporters to make it easy to generate graphical views over event results.
PS though it’s not data related at all, you may find this amusing: OU app for working out which Olympic sport you should try out… Olympisize Me (not sure how you know it was an OU app from the landing page though, other than by reading the URL…?)
PPS I tweeted this, but figure it’s also worth a mention here: isn’t it a shame that LOCOG haven’t got into the #opendata thing with the sports results…
So the Olympics is over, and now’s the time to start exploring various views over the data tables in a leisurely way:-)
A quick scout around shows that the New York Times (of course) have an interactive view of the medals table, also showing a historical dimension:
Channel 4’s interactive table explores medal table ‘normalisation’ according to population, GDP and so on…
GDP and population data have also been taking into account in a couple of visualisations created on Many Eyes – like this one:
Not wanting to not be part of the fun, I spent a bit of time this evening scraping data from the Overall medal standing table and popping it into Many Eyes myself.
(Note that there’s lots of mashable stuff – and some nice URLs – on the http://en.beijing2008.cn/ website… why, oh, why didn’t I think to have a play with it over the last couple of weeks?:-(
Anyway, I’ve uploaded the results, by discipline, for the Olympics 2008 Medal Table (Top 10, by Tally) and had a quick play to see what sort views might be useful in visualising the wealth of information the data contains.
First up, here are the disciplines that the top 10 countries (by medal tally) were excelling at:
Treemaps are one of my favourite visualisation tools. The Many Eyes treemap, whilst not allowing much control over colour palettes, does make it easy to reorder the order of the hierarchy used for the treemap.
Here’s a view by discipline, then country, that allow you to see the relative number of medals awarded by discipline, and the countries that ‘medalled’ within them:
Rearranging the view, we can see how well each country fared in terms of total medal haul, as well as the number of medals in each medal class.
The search tool makes it easy to see medals awarded in a particular discipline by country and medal class – so for example, here’s where the swimming medals went:
A network diagram view lets us see (sort of) another view of the disciplines that each country took medals in.
The matrix chart is more familiar, and shows relative medal hauls for gold, silver and bronze, by country.
By changing the colour display to show the disciplines medals were awarded in, we can see which of the countries won swimming medals, for example.
Enough for now… the data‘s on the Many Eye’s site if you want to create your own visualisations with it… You should be able to reduce the data (e.g. by creating copies of the data set with particular columns omitted) to produce simpler visualisations (e.g. simpler treemaps).
You can also take a copy of the data to use in your own data sets, (e.g. normalising it by GDP, population, etc, etc.)
If you do create any derived visualisations, please post a link back as a comment to this post :-)