We Are Royale
Like any mysterious organization that deals in ephemeral nostalgia, We Are Royale has its own even more mysterious Skunk Works. You name it, we’re working on it. Like taking a tour of Q’s infamous foreshadowing room, stepping into the Royale Labs often requires a flak vest and sunglasses. In one of our more approachable and tame studies, we set out to collect vast amounts of personal data on our employees while they attended SXSW for multiple years. With HR breathing down our neck on what is too “personal,” we limited it to a focused data set that explored a Royale experience at SXSW.
We ended up making two Data Visualizations that explored our beverage and social activity as well as one that tracked our traveling and designed a narcissistic transit system that would only benefit us. The takeaway is two unique data narratives that explore what a data visualization can be and just how far we can push our own exploration of data narratives.
SXSW Transit Map
We like to call this one the Narcissistic Transit Map because, while it may look legit, this transit map is truly built just for us. When we first set out to SXSW 2016 we knew we wanted to record our locations and travels to build a visualization of it afterwards. What we left open was just what kind of visualization that might be, which we did on purpose. We didn’t want to limit ourselves or create a conscious bias in our data collection. We even had a double blind setup where two Royale SXSW scientists didn’t even know they were being recorded. HR!
After the festivities, we started organizing and collating our data. Our process involved a number of quick visualization systems that rapidly show various mapping types. What we found was a pattern in a few prominent locations that ended up making the map all about the conference. Knowing we ventured well beyond the doors of the convention center, we set out to organize and design our data in a way that helped convey just our exploratory our trip was.
Ending up on designing a transit map may not seem like the obvious solution for our data but it’s also an exploration in narrative devices. In this case, the turning point was a simple comment around the lunch table; “looking at this data, it would have been nice if we had our own bus that went from the house to the coffee shop.” Yeah, that would have been nice. And that got us thinking, what other lines would be created based on this data?
Developing our own transit system wasn’t a simple process; we wanted to do it right. So we turned to urban planning and transit structures and studied the processes and considerations that go into actual transit planning. Our data set is considerably smaller than what a municipality might require for planning but we knew we had enough to start building context.
The map we ended up with was an exploration of creative storytelling mixed with city transit design research. A weird combination so say the least, but one that ended up telling a wholly unique story. These lines express our most popular destinations, common routes, popular hours, and that one night that just went on and on and on. These revelations and many more lie just under the disguise of a classic wayfinding device.
SXSW Imbibe Map
In the spirit of, well, spirits, we wanted to collect and visualize just how much indulging we took part in while meandering the after hours of SXSW. Austin Texas certainly makes it easy to find a drink so we made it harder on ourselves. Not only are we recording alcoholic beverages, but we would record ALL beverages and categorize them as they are. In addition, we want to compare this with how many people we meet up with while partaking in said beverages. So yeah, plenty to record.
We gave ourselves a simple logging system where, once underway, we could quickly log drinks by type, quantity, and who we were with. The fun part was deciphering this data when the whole experiment was done. As you can imagine, around 4am, the data set gets a little iffy.
Plotting all this data out is pretty straightforward. All plots are around locations and the size of the colored circles visualize consumption amount in volume. The interesting comparative factor here ended up being the amount of people we met up with compared to the total drinks consumed. And, of course, there are some locations like our favorite coffee shop that only had big, blue, non-alcoholic beverages.
To cap this data off, we placed a ring around the outside of the map that divides the data set into five 24hr ring segments. On this line, you can see when we got thirsty, how much, and just what kinda drink ended up quenching that thirst. Stay hydrated!
So this whole VR thing is kind of big right? Well some of our eggheads down in the lab decided to build out the Transit map as a virtual model sort of like those cool model cities you love looking at. Since we’ve been exploring various narrative devices, we tossed the map into a VR experience and took it for a spin. Pretty cool and ultimately just the tip of the iceberg. How can we merge VR experiences with Data Narratives? Don’t worry, we’re still working on that.
In the meantime, check out this fun experiment using your own VR goggles. Just click the video linked in the image above to take it for spin (not literally though. Spinning and VR goggles don’t mix. Trust us, we’ve had experiences.)