Like molecules floating in water the main navigation on the website of the Präsenz-Zentrum slowly glides over the screen. When touching them they make waves and strengthen the impression of floating bubbles. Despite this fancy navigation the website still should be usable for everybody, no matter if using a PC or a mobile phone. To make this possible the ad agency Schlögl + Schlögl asked me for help concerning the technical implementation.

Almost immediately people started digging into the data and before one week has passed we can already admire some interesting and useful projects.
Looks like people are mainly interested in Toilets and Budget Data http://data.wien.gv.at/apps/

Of course I also had a look a the data and came up with some first thoughts.

Two kinds of Data

By now there are two kinds of data: statistical data (census, budget) and location data. My first guess was that people will be trying do use statistical data for visualizations and create tools for every day use out of location data. By now it looks like my guess was right. Similar to my recent Push Snowboarding Visualization I tried to find a less occupied niche as I believe it would be a shame if the use of that data only focuses on Budget Visualizations and Toilet-Finders. Don’t get me wrong – those are great applications and really interesting and useful. It just doesn’t make sense to have 20 variants of each.

So what I started thinking about was making sense of the location data beyond just searching and displaying it on a map as it is. I looked for ways to extract further information from what we have. One idea immediately came to my mind:

Infrastructure coverage

Imagine you are looking for a new house, a flat or just a hotel to spend some nights. Normally you would just check on the internet which areas are deemed nice and start searching on some real estate website mainly focussing on price and the house/flat/room itself. Especially if you don’t know the city well.

But aren’t there some other things that are quite important as well? What if you’ve got kids and want to have a kindergarten or a school nearby. Or the other way around – you’re looking for a calm place apart from screaming kids. You’re a semi professional swimmer and want a public swimming bath just around the corner. You’re in the city just for a weekend of cultural exploration and want to be as close to museums as possible.

The list goes on and on and actually for these situations we already have most of the data we need. So why not give it a go?

The perfect spot

So I fired up Processing and started exploring what we have. As I really just did a quick and dirty sketch of my idea to get it running for tomorrows OGD Platform Meeting I won’t go into (technical) details for now. I plan to clean up the code and publish it as soon as I can find time to do so.

Anyway I just want to go through my sketch quickly and outline some of the findings I had.

Of course the first thing I did was to load all the location data and simply display it. For testing I did choose the hospital data as some hospitals are really close and some are far away from any other, which seemed perfect for testing.

Next I calculated the minimum distance to the next hospital. The darker the map, the closer the hospital. I also experimented with some more colours to get more detail than what was available just with shades of grey.

I also played around with things like segmenting:

Then I finally returned to what was the initial idea: Finding areas that conform to certain criteria. Therefore I needed to combine various datasets.

So I visualized the scenarios outlined earlier on:

Someone looking for silence:

• at least 1km away from any school or kindergarten
• and at least 3km away from hospitals (ambulances!)

A swimming-enthusiast:

• at most 1.5km to the next public swimming bath
• or at most 1.5km to the next bank or beach

More examples can be found on flickr.

Final thoughts

I believe that this application and Open Government Data in general do have a lot of potential. I am aware of the fact that e.g. for the amount of silence there are plenty of other factors apart from kids and hospitals. But this can easily be expanded if more data like traffic, factory noises,… become available. I will definitely try to explore this further and publish the code as soon as I do find time to clean it up a bit.
In the meantime I’m eagerly watching what other people are coming up with. Feel free to comment on this as well – I would appreciate any kind of Feedback!

And again it’s time to say: Attention Schlaumeier! Now the third CD of the SCHLAUMEIER entdecken Mathematik series with a whole lot of brand new exercises is finally ready. Thanks to the random generator there are again an almost endless number of exercises and all of this without any installation. So what are you waiting for – put your CD in and get started.

In search of a new Key Visual for the “Kultur Burgenland” brand the Kultur-Service Burgenland and the Zentrum für Kreativwirtschaft held a contest. After thinking about it for some time I also entered with a concept.
As culture is a process, an ever shifting mixture of people and their interests and experiences a flexible design seems to be most fitting – a generative approach. With fitting parameters (geographic location of cultural venues and events, size and reach) the different aspects of culture in Burgenland are visualized. Like this we get a Key Visual that individually adapts to a concrete usage scenario while still preserving a common appearance by relating to colour and style of the existing logo. With the corresponding program an almost endless amount of variants can be generated to e.g. easily integrate new events and venues into the portfolio of “Kultur Burgenland”.

Much like Matthias Müllers portfolio my colleague Christoph Kerschbaum needed an unobtrusive website showcasing his photography. I actually used a quite similar design with an individual welcome page and added some decent branding to the mix. So why not have a look at what Christoph has been shooting!

The amazingly talented Matthias Müller and his great illustrations really stand out from the crowd. To give them the stage they deserve I created a very unobtrusive website. It lets you browse through his works easily  without ever distracting from what it is all about – great illustrations you should really check out!

For more details have a look at the portfolio page of this project.

Let’s start off with having a look at the final result:

Okay how did we end up here, step by step:

The data

When looking at the data offered by the Push Snowboarding Website you can easily be overwhelmed by the sheer amount of several thousand sensor outputs for just a single ride of a couple of minutes. Also there are a lot of different sensors available, some sampled by various internal (Nokia N8) and external sensors: GPS position, acceleration, compass, gyroscope, heart rate, rush and foot pressure.

So my first thought was that I had to stay focused and concentrate on a meaningful subset of the sensor data and try to capture a certain aspect of the ride the data represents.

When looking at the videos it dawned on me that it’s all about snowboarding. A fun sport, one that isn’t only athletically challenging but also features a huge amount of beautiful artistry. So why not use the data to capture this beauty in some way? As I have some experience with generative design I decided to proceed this way.

The visualization

The next step was to decide on which data fits this approach best. As its about the experience of the ride I decided to start from the GPS coordinates of the ride and enrich it with the speed, rush, and heart rate.

The most obvious thing is the path of the ride. You can see it curve down. No explanation needed there.
While the particles run down the track they sometimes spread out and orbit around the track path. This happens when the speed falls below a certain threshold. So if the rider stops the particles start buzzing around just to immediately rush back to the path when the rider is speeding up again.

Particles orbiting at the start of the track just before the rider departs

The last remaining data being rush and heart rate are combined into color. The higher the heart rate the more red and the higher the rush the more blue is spread alongside the path. If heart rate and rush are high at the same time this leads to this purple-pinkish hue. If the rider is totally relaxed you won’t see any color at all.

calmly speeding down the hill

the riders heart is pumping and he is sweating like hell

Use cases

As nice as this may look – what is this image good for? I can imagine a vast variety of applications. Let me just outline some:

You are on a marvelous ski holiday or even taking part in a race. But when it’s over it’s over and you wish you had a visual souvenir of that experience. So why not just print the visualization of your data on a canvas and hang it right on the wall in your living room?
Or why not give tribute to the mobile phone that helped you collect the data in the first place – use the image as wallpaper for your mobile phone:

Finally my personal favorite: Why not even print it on a snowboard that you can use later on to collect the data for even more amazing snowboarding visualizations.

I hope you like my approach. Even if not feel free to let me know by commenting below. By then I am really looking forward to the other contest entries and how they made use of the data.

Push Snowboarding ist eine Kooperation zwischen Nokia und Burton die mittels einer Reihe Sensoren und einem Nokia N8 Daten eines Riders sammelt. Jetzt haben sie einen Wettbewerb gestartet, um diese Daten zu visualisieren.

Beim ersten Blick auf die Daten kommen einem sofort Ideen zu einer Informationsanalyse für Trainingszwecke oder für statistische Analysen. Da mir das jedoch zu offensichtlich erschien habe ich versucht einen anderen Zugang zu finden.

Es geht um Snowboarding, einen Fun Sport der nicht nur athletisch anspruchsvoll ist sondern auch zu einem großen Teil von artistischer Schönheit lebt. Warum also nicht diese Daten dazu verwenden diese Schönheit in einer abstrakten Weise einzufangen? Auf diese Weise könnte man die Schönheit des Boardens in einem Bild bewahren dass man sich dann an die Wand hängen oder als Hintergrund für sein Nokia N8 verwenden kann. Oder warum das Bild nicht gleich auf ein einzigartiges Snowboard drucken mit dem du dann noch mehr Daten für noch mehr beeindruckende Visualisierungen sammeln kannst.

Nähere Informationen über diese Visualisierung finden sich in einem extra Blog Post zu diesem Projekt.

28.02: As I’ve just been informed I won the competition!
Push Snowboarding is a collaboration between Nokia and Burton that equips a rider and his board with a number of sensors and a Nokia N8 to record detailed data while out on the piste. Now they have started a small competition how to visualize and make use of this data.

When first looking at all the data collected by the sensors some kind of information analysis to be used for training purposes or statistical analysis immediately pops in your mind. As this seemed too obvious for me I tried to find a different approach towards the data.

I soon realized that it’s about snowboarding. A fun sport, one that isn’t only athletically challenging but also features a huge amount of beautiful artistry. So why not use the data to capture this beauty in an abstract way? Like this you can save the beauty of a snowboard ride in an image that you can then print and hang on your wall or use as a wallpaper for your Nokia N8 that helped you get to this in the very first place. Why not even print it on your unique snowboard, that you can use later on to collect the data for even more amazing snowboarding visualizations.

If you want to get more into the details of my take on the data have a look at my blog post about this project.