My old hackerspace [Workshop 88](http://workshop88.com) was recently commissioned by [MapR](http://mapr.com) to develop custom conference badges — wearable technology — for the [Big Data Conference](http://www.big-data-conference.com). The objective was to use that wearable technology, combined with MapR tech, to showcase the data being collected by the badges and transform it into an interesting experience.
In the last week or so of the project I was called in to help polish the game experience, create the web and data servers, and design the web visualizations through a combination of MapR tech, Apache Drill, Nodejs, and D3. Along the way we ended up redesigning most of the original experiential concept.
The badges had initially been designed to collect data and simply use it to dictate achievements. The idea was to use sensors to detect UV and IR exposure, eposure to other attendee badges, times of certain actions logged, and more, then upload it to a central server. From there, arbitrary achievements could be designed around them.
Coming from a game design background, this didn’t seem entirely compelling to me. The badge designs were great, but the experience coming out of them was still lacking. Achievements are not core to any good interactive experience, and people would likely lose interest in the arbitrary data quickly. So I started to brainstorm ways to use the data we were receiving from the badges into something more compelling.
#### One of the best ways…
to think about interactive design experience is to look at it as a balance between certainty and uncertainty. Too much uncertainty, and a game is too random. Too little, and it’s on rails.
When looking at the data coming in from the badges, the question became: how can we take a complete picture of information like the stuff we were gathering and use it to introduce uncertainty into the game? Another question was: how can we craft an experience by displaying the information in such a way as to allow attendees to make meaningful decisions? This is often referred to as *insights* in the big data world.
Taking a cue from games like Werewolf and Pandemic, I wound up arriving at a few conclusions about the badges:
1. The game needed more game-like elements. Seems like a simple conclusion to arrive at, but it isn’t always very obvious. Things like obstacles, negative and positive feedback loops, and player choice needed to be introduced.
2. The data that we were collecting needed to be used to create further uncertainty in the game. We would need to introduce an anomaly (in this case, a virus) into the game in order to generate that uncertainty.
3. An online interface that provided up-to-date information would be necessary for immediate feedback. With in-person games like this (often referred to as augmented reality games), providing players with feedback is key. This is the *insights* portion of the game.
Over the past couple days, I believe we’ve addressed many of these problems. The end result is the [Big Data Outbreak](https://github.com/poplicola/bigdataoutbreak) project: a virus outbreak-like experience that simulates the spread of disease within a population. By using a form of near field communication to allow the badges to talk to each other, and in turn the server (through the use of RPi kiosks), badges communicate the disease between themselves, and the outbreak spreads. As the outbreak spreads, people are forced to look for a way to heal themselves (using the kiosks), or perish.
In practice, we’ve created a real life simulation of an epidemic using only conference badges.
I’m quite excited — and nervous — to see how these badges turn out in the coming days. With the short development cycle for this game, we’ve been unable to playtest it to any meaningful extent. Yet there’s something about the potential of the information we’re collecting, and, I think, something about wearable technology that shows a lot of promise for augmented reality games. The true interaction between technology and the real world opens up many possibilities.