How I Learned to Love the GIS Challenge
I am a newcomer to GIS but not really: I moved from one niche space, cybersecurity, to another when I joined Spatial Networks last year, and I can’t help but notice the parallel between the spaces. Most striking of all, though, is they are parallel because once you clear away the jargon and the trappings of each space a clear picture emerges. In many ways, both are applications of context or metadata that is truly a reflection of the people and the world around us. The key here is the word context, which I’ll come back to in a moment when we dig into the nature of metadata a little deeper.
What my brother Sam Curry, CSO at Cybereason, recently wrote in an article on privacy clued me into a powerful idea: Imagine a Tinkertoy representing the world and everything in it. This isn’t your average Tinkertoy, it’s the mother of all Tinkertoy constructs. It is a representation of every car, every person, every machine, every application, every datum everywhere. These are the “nodes” in the graph, borrowing from Graph Theory, and the “edges” are the relationships among them.
Here’s the thing: It’s alive. It’s moving. It’s changing. It’s dynamic. It’s actually a perfect reflection of the real universe. Sam talked about privacy, but I read it and was thinking about my own experiences in cybersecurity and most importantly in GIS. For me, this massive Tinkertoy when I wear the cybersecurity hat is about enforcing the right relationships and denying the wrong ones — the node for my bank account should be connected to me and not a criminal. Cybersecurity is the discipline, when we strip it down, of understanding which edges are good and bad, reinforcing and enabling the good and blocking the bad. Now there’s a lot more to it in execution; but if you look at the evolution of security, it’s all about the data and the context at any point in the data structures with respect to everything else.
The same is true in GIS. We are literally mapping this universal Tinkertoy with the aim to enable new connections, new insights, new opportunities. We might call it “intelligence,” but we are seeking to understand context among the nodes and to then make that context leverageable at scale.
Remember how it’s also dynamic and changing? Well, it is expensive to update and keep current, but that’s why GIS matters. We will progressively make it cheaper to understand this universal Tinkertoy and make the critical pathways easier to mine, access, and use. That’s our mission, of course: connecting people to the things they care about and helping them make life better for the communities they live in, by strengthening schools, growing more food, combating homelessness, addiction, and crime, with an eye to privacy as Sam mentions in his article.
I went to the grocery store the other day and was asked first by Google questions about the store: was it handicap accessible? Was there enough parking? And so on. I gamely answered a few questions because…why not? I’m not in cybersecurity anymore, after all :). Eventually, though, I got fed up. They hadn’t gamified it, and I had a sense that I was basically being used as free labor.
Then Facebook asked me the same questions, and my patience was much shorter. Is this really the best we can do? What is the incentive for me to answer the questions accurately and objectively? There are many opportunities for error — for example time, nature, human, or malice. What if I’m having a bad day or don’t like the location I’m being asked for information on? Can you really trust any random individual contributor? I don’t think so.
This is where the exciting work being done by the team at Spatial Networks on new products like Foresight is so valuable. It’s deeper and next level. Foresight demonstrates Spatial Networks’ ability to verify and analyze events with on-demand, trusted and verified ground-truth data. Collected by vetted professionals with specific details in mind for organizations that need to understand things like disease outbreak, competitive landscape, consumer demands, natural disasters, economic realities, etc.
The challenge for GIS is to make the collection of this data more automatic, more intrinsic, more real-time and verifiable. We need to bring the context in as close to real-time to pierce the fog and show us the beauty of that universal Tinkertoy and then to make sure, first, that it isn’t abused for the wrong uses (privacy!), and second, that it is enabling a brighter, empowering, delightful world where services are personal and almost magical. We have a long way to go, but I’m up for it.
Are you?
