The UTS Data Arena uses open-source software to transform numbers into interactive 3D geometry, enabling this user-friendly technology to be shared by all.
UTS Data Arena technical capabilities
User-friendly technology to be shared by all
The technical capabilities of the UTS Data Arena include:
- Software: OmegaLib and Equalizer provide a load-balanced rendering system running on a cluster of 7 high-end servers with a combined 448GB RAM and 25,920 GPU Cuda Cores.
- 3D animation software from the feature film industry is used to generate geometry.
- Data is first organised into channels. Each channel is then mapped to a geometric attribute such as (x,y,z) position, rotation, (r,g,b) colour, icons, even 3D sound, etc.
- Data can be aggregated from any kind of digital device – from microscopes and mobile phones to transport cards and fitness apps.
- Interaction via smartphone, 3D mice, motion capture video markers, PlayStation controllers, Virtual Reality Wands, WiFi devices (iPad), Midi, OSC, USB, and Bluetooth input devices.
- Uses open-source software, meaning users are at liberty to take the fundamentals of the existing source code and tailor it to their own purpose.
Data Arena data pipelines are maintained in open-source git repositories meaning they are constantly shared and improved. The software is also available as a free download, allowing offsite development in a virtual machine on your own device/s before taking it into the Data Arena environment.
Visualise this: UTS Data Arena
[Music]
Male: The data is a 4 metre high screen that surrounds you in 360 degrees. It is 10 metres wide, so it's like half a tennis court. In that space we can interact with data in 3D stereo. It's a completely different experience. Instead of just playing a video that's canned and doesn't change, this is an interactive immersive experience, so we're able to explore the data set and move around it.
[Music]
The software that we're using in the data arena is open source, which is one thing that makes it unique. It allows us to use many computers in collaboration, in a cluster, so that they're working in concert to show one data set. At the moment there's two of us creating the underlying software for the data arena. There's myself and [Darren]. We can already create that pipeline so that you can insert your data here and get your data set there. Now, the thing that makes the data arena slightly different is it doesn't end there. You can then interact with that data set. You can make some changes and see how that data then impacts to create different geometry that you can then visualise.
[Music]
Interaction with the data is what the data arena is all about. We can interact with even iPhones and android devices so that everyone together in the room can interact with the data.
[Music]
We should be able to fit about 30 people in the space, and so I can show you what I've been doing. I can show you the problems that I'm dealing with. We can collaborate. We can possibly look for new ideas or the next step. We can explore the possibilities of the data set.
[Music]
One of the interesting things about taking data into the data arena is representation, is how do you represent that data? Quite often, when it's your own data, that's when it's really quite exciting. You never really know what you're going to find. It can quite often just be quantitative, like I just want to see what data I have. Quite often you don't get a final result. You just know where the next step is.
We've had a couple of recent examples where we've loaded data sets in just to prototype the data arena. Already we're finding anomalies in the data, things that we didn't expect to see. Now, it's very hard to see this when it's in a spreadsheet, but once it's up on the screen, suddenly, we've had people go I have to go back and have a look at the data again, I've seen something new.
[Music]
I've wanted to build one of these data arenas for a very long time. These are very special spaces. It's really quite a different thing to be able to see your data set in 3D in full surround. It's really satisfying to know that we're building something that UTS can use to explore their own data. There's an enormous amount of data here at UTS, and to be able to get it up on to the screen and to show people what we're doing, and to then be able to bring in new collaborators where people see things and think hey, I know what that is and perhaps I can participate as well.
Beyond just the hardware that we have here, we're building a community, and that's what's really exciting, is that people will come together, initially, just to look at the data set in this data arena; but then who knows where we go beyond that.
[Music]
