Halloween is here. It’s a time when the weather gets colder and the leaves fall from the trees. A time when kids dress up in fun costumes and go trick-or-treating. A time when we start thinking about how to spend the holidays with our family and friends.
And if you’re like me, it’s also a time when you really start to worry about an impending zombie apocalypse.
Say what now?
Hey, I’m a rational guy. I’m into the whole “science” thing. (I like it a lot, actually.) But the concept of the dead rising from the grave? Man, that’s just too intriguing to ignore. In the unlikely event it ever did happen, I’m going to be well-prepared. I’d have a cache of food and water, and a whole host of other zombie-appropriate gear.
But the one thing that would set me apart from my fellow human beings awaiting the undead? I’d be one of the smart ones using data visualization to track the spread of the zombie virus, and the movement of local walkers (they sure are quiet when they need to be).
Yes! What would be a common problem to most panicked survivors in these situations? They wouldn’t know where the zombies were located! Well, the local news station might tell them (before it shuts down), but they wouldn’t provide anything as useful as a map detailing the level of risk in different areas. Imagine if CNN could provide you with an image like Figure 1. I don’t know about you, but I’d be heading north to Canada, or out into the desert. No way would I head to those “emergency” shelters in the big city. (It’s a fact that these would often be overrun very quickly.) Pop out my laptop, launch JMP, and bing bang boom… I could assess the threat in a manner in which I could easily convey to others. No more arguments on which way to go!
Now, you may ask, “How on Earth would you geocode all of that zombie data”? We’d have you covered. Download a free JMP add-in to geocode geographic locations. (Download requires a free SAS profile.)
That’s not all. With access to maps from OpenStreetMap (OSM), you could easily map the location of the undead in the local area. For example, Figure 2 (click to enlarge) shows the results of a simulated zombie outbreak in downtown San Francisco. Larger zombie size is an indication that walkers may be traveling in herds.
Or, you coud track their movement over time and attempt to predict where the zombies will end up next. Below is a simulated example. Zombie movement is based on a random-shuffle (ha!).
[iframe title="YouTube video player" width="560" height="315" src="http://www.youtube.com/embed/_w1vUy_95rY" frameborder="0" allowfullscreen]
Imagine the edge I’d have knowing where the undead would go, and how easy I could communicate this to the team. “Hey, guys! Zombies are heading to Fisherman’s Wharf for some seafood – they see food running and they eat ’em!”
I know what you’re thinking: How in the world could I possibly track the undead? This is where you have to suspend reality again and consider a world where tracking devices are installed in every newborn baby. Then it would be a piece of cake! (It is not that far-fetched to think that Night of the Living Dead could have made that kind of impact on the government in the late sixties). I could use Data Filter to remove signals coming from any source with a normal human body temperature. Yup, I thought of everything.
It’s likely we may go another 75 to 100 years without having to worry about the walking dead. But why take chances? I’m using every tool at my disposal. And if data visualization is useful enough in the office, it’s got to be handy when the dead walk.
Many thanks to John Ponte for the awesome zombie graphics and a new twist on the classic “seafood joke.”