Crisis Mapping, Dynamic Visualization and Pattern Recognition

My interest in dynamic networks and data visualization dates back several years. Indeed, one of the reasons I participated in the Santa Fe Institute’s (SFI) Complex Systems Summer School (CSSS) back in 2006 was precisely because of my long-time interest in applying this area of research to conflict analysis. But it wasn’t until recently that I began to connect those dots to my current research on crisis mapping and pattern recognition in complex emergencies.

Below is one rendering of a dynamic network that I used when co-teaching a  graduate seminar on “Managing Complex Systems” in Fall 2007. The visualization depicts flight patterns across the US. I used this simply to illustrate that certain patterns emerge when data is visualized geographically and temporally across multiple scales.

Another example is the dynamic rendering of information flow in the Blogosphere. I’ve included a picture below but the video for this animation is also worth watching. What does this have to do with crisis mapping? The point is to provide comparable visual renderings of dynamic conflict data at multiple levels of analysis, both spatially and temporally. When doing so, potential patterns and linkages can emerge. Mapping the “fluid dynamics” of conflict, or contagion effects, can be particularly insightful.

One really stunning rendering of a dynamic network was recently posted on the BBC’s technology news site. Using satellite imagery and ground breaking computer imaging we can for the first time visualize stunning patterns that emerge across the UK as seen from the sky. Like the flight tracking video above, this short BBC video is also highly worth watching.

These examples may serve as worthy goals for the new field of crisis mapping analytics, or CMA. It remains to be seen whether we can pull this off. More importantly, however, the question is whether this exercise will get us any closer to saving lives in complex emergencies.

Patrick Philippe Meier