Making Big Data Accessible Through Interactive Visualizations

Computer modeling and interactive data visualization can make big data significantly more accessible.

by / January 26, 2017

Big data, open data, the Internet of Things (IoT) and smart cities have become commonplace words. Yet most government leaders find difficulty connecting these words to their day-to-day challenges like reducing traffic congestion, improving resilience to extreme weather events, and making communities better places to live and work.

During the Resilient Cities Summit held in Santa Fe, N.M., in December 2016, we sat down with Resilient Solutions 21 CEO Charles Rath and Kameron Baumgardner, visual informatics lead, to better understand how computer modeling and interactive data visualization can make big data significantly more accessible. The interview has been edited for length and clarity.

Q: Tell me a bit about Resilient Solutions 21 and its mission.

Rath: We provide resilient solutions for the 21st century. We're two years old, we're a technology startup. We focus on helping communities, business and organizations solve complex challenges with big data and visualizations. We create highly accessible, insightful and immersive products that people can access through a simple Web browser. It's very user-friendly and easy to understand. We create data through satellite imagery. We layer data from a variety of different local, federal or state sources. We have a team of gamers and Hollywood special-effects folks, and engineers and scientists that collaborate to create these very cool products that drive policy decisions.

Q: What do you mean by immersive products?

Rath: Our interactive visualizations are the great unifier. What we found historically, is that if you're creating models and you're not able to allow your audience or your stakeholders to interact with that information, understand the assumptions, understand how it works, get their particular specific insights out of it, the likelihood of them trusting what you're producing or believing it or understanding it is incredibly low. There is an art to displaying complex information in a way that is honest, but it also insightful and easy to use and easy to understand. We focus a lot of our time on this. We have the engineers and the scientists that understand complexity theory, understand how these systems works. But the translating of how those models work to actual user experience, that's the art. That's where we bring in the special effects folks, the user experience experts, etc.

Q: The gaming issue you just touched on — is that a Sim City type of thing? Is that what you're talking about? 

Baumgardner:  Yes, essentially. Technology for the Web is getting to the point now where we can produce experiences that people would expect out of video games and see in the movies. The guy in Minority Report sliding all the information around, or the guys in The Martian figuring out where they want to land on the moon, is what you would expect analytic experiences to look like. We're finally getting to the point where easily distributed information can live through the Web and look like that, and you can have that kind of interaction with the data. The way that it looks is really influencing engagement. We use that engagement to drive decision-making energy. If you can provide people with the underlying assumptions, the underlying information and essentially let them find the results, then that's how we garner buy-in.

Q: How broadly do you see this being picked up? Where are you going with this?

Baumgardner: We haven't found anywhere yet that we haven't been able to pick it up. Using systems analysis and systems thinking, combining that with policy analysis data visualization, we've moved into a lot of different sectors and haven't found any that we've approached yet that can't use that kind of capability.

Rath: We've done work to help reduce youth violence in Mexico. We've done work to mitigate the urban heat island effect in El Paso. We are looking to get into health care and better understanding how socio-economic and behavioral trends impact health at a very micro scale. We are helping the transportation security administration better visualize how well their security posture is against a variety of different types of threats going into airports. The way that we tackle problems, as Kameron mentioned from a systems perspective, understanding how those parts are connected and understanding how they can be impacted. Understanding the social, the physical, the economic, the environmental angles of this. It's powerful and can be applied in a lot of different areas.

Q: Technologies like driverless cars and ride sharing will be driving change into city transportation and land use planning. It would seem that your modeling would be helpful. 

Baumgardner: Yes, absolutely. That's actually my academic background. I was trained as an architect, as an urban planner and then went into technology and computer science. Machine learning gives us a great, great capability to look at the underlying DNA of cities that function well, right? We are humans and that will not change. The ways in which we experience will. The underlying core values that makes cities great will have to be changed and adapted when driverless cars are no longer a novelty. Using our data collection capabilities, our machine learning capabilities, we can help cities adapt to huge social changes and figure out not only  the easiest way that we can react to this. Right? How do you rezone parking lots in cities that take up 40 percent of our urban landscape? Do you just open that up to commercial development? Is that some new opportunity for us to explore new ways that cities can interact with public? Or is there a new way that public space can exist in ways that are both resilient, sustainable and great economic drivers for taxable value?

Q: It seems that this technology and approach would increase confidence for city and community leaders in their planning. It's a more transparent approach to say, "Here's the data, let's explore things together." 

Rath: Dead on. That's absolutely right. The value of this is that it's not necessarily the mayor pushing something on someone; it's everyone discovering this issue together and then developing a good bipartisan solution, hopefully. 

Q:  Any final thoughts you'd like to share?

Rath: Yes. We're a huge proponent of open data initiatives that are going on across the country. There's a big wave. What we're describing in the work that we do, it's not bleeding edge. It's not thinking about "What's the future going to be like?" It's here. Many times we go into cities and we know more about the city from a data perspective than the city does. We can say, "Look at your data. This is what it's showing you." It's really empowering for the community, the private sector, for companies like ours to be able to do social and economic good for humanity.