Crowdflow: pretty pictures with our iPhone localisation data

Smartphones have changed the way we think about pretty much all aspects of communication. We’re used to having internet access in our pockets, GPS, barcode readers – you name it. There are thousands of applications to make our lives easier and fun, to make us more connected and better informed. I personally only got into the world of smartphones very recently, I’ve only had my HTC Wildfire S, which is a very basic smartphone, for about a month. So, I have to admit, I don’t really have that much first-hand experience with all the cool applications. However, I had stumbled upon some awesome data visualisation quite a while back – it was a world map with Facebook connections, and in addition to being informative, it looked really pretty (here’s the article on BBC tech news from December 2010 with artwork that inspired me to look into this topic). I found it fascinating at the time that aesthetically extremely pleasing results can be also informative.

So, when I started thinking about applications that about mobility, I thought of those visualisations, and started digging. That’s how I found Crowdflow. I had never heard of it, but the pretty pictures had me straight away. Crowdflow works on the concept of data donation, which I find fascinating, because in addition to embracing the possibilities of smartphones with their localisation software, they are also crowdsourcing the data they use for making those visualisations.

Crowdflow states their mission on their website:

You probably know by now that your iPhone collects the position data of wifi and cell networks near by.

We would like to combine as many of these log files as possible, create an open database of wifi and cell networks and thus visualize how these networks are distributed all over the world.

So please contribute your iPhone log files and help us to create an open wifi and cell database.

As I mentioned before, all data they use in their project, is donated to them. More precise instructions on how the process goes, can be found from the project website. All data is shared under the Open Data Commons Open Database License. The data is donated anonymously and the Germans use their custom software to create the visualisations. With projects like this, data retention is always a hot topic, because there are obvious controversies regarding mobile phone tracking data storage (e.g. like described here, a German politician sued Deutche Telecom). The privacy issue has been redeemed with the fact that on Crowdflow, all data is anonymous and given out through free will, so the issue of some higher organisation storing very detailed private data (such as available to our mobile phone providers through our reception and wifi connections) is left aside in this app.

However, Crowdflow has one major limitation – it only works with iPhones. They justify it with Android data being more difficult to access for regular users. Apple has also answered some of the biggest questions that arise about storing location data on their website (probably worth having a look at, especially for iPhone users, along with this more concerned view on Apple’s location tracking), the following paragraph is also from there, explaining how Apple gets the data.

The iPhone is not logging your location. Rather, it’s maintaining a database of Wi-Fi hotspots and cell towers around your current location, some of which may be located more than one hundred miles away from your iPhone, to help your iPhone rapidly and accurately calculate its location when requested. Calculating a phone’s location using just GPS satellite data can take up to several minutes. iPhone can reduce this time to just a few seconds by using Wi-Fi hotspot and cell tower data to quickly find GPS satellites, and even triangulate its location using just Wi-Fi hotspot and cell tower data when GPS is not available (such as indoors or in basements). These calculations are performed live on the iPhone using a crowd-sourced database of Wi-Fi hotspot and cell tower data that is generated by tens of millions of iPhones sending the geo-tagged locations of nearby Wi-Fi hotspots and cell towers in an anonymous and encrypted form to Apple.

What I think is remarkable about projects like this is the fact that something so completely abstract for most mobile phone users can be turned into something so tangible, into a beautiful form of art. This application of data that has a lot of controversial debate around it is truly creative and I think it embraces what technology is capable of at its best. It doesn’t even matter that only a number of iPhones is shown (the willing donations), and the informative side isn’t very reliable. It’s a complex process of retrieving data, sorting and cleaning it and using sophisticated software for the final visuals, but at the same time very simple and therefore pretty ingenious, if you ask me.

Below are two of my favourite outcomes of this project.