Revealing Networks
by Tim McGee, Helena, MT, USA on 06. 9.05
Networks are everywhere. My world is increasingly described by networks: my cell network, my blog network, my networks of friends, and job network. Even in my research I find networks in biology, (and spend a good deal of time trying to understand the relationships - I know...I'm a geek). Indeed, networks are a wonderful way to model the behavior of complex systems -for example an ecosystem. But it is not always easy to determine which part of that network is important to the structure or function of the system, or even what role any one part may play in the network- until now.
Biological physicists from Budapest Hungary have devised a way to lay very complex networks bare. In a recent article titled "Uncovering the overlapping community structure of complex networks in nature and society" featured in Nature, they describe a process to evaluate a network that takes into consideration the multiple levels of organization and 'membership' each component has in multiple sub-networks. Thus, it is now possible to look at much more complex networks, and predict the significance of any part of that system. Kind of like peeling away an onion, this method allows us to peer at different layers of the system. From looking at the interaction of large networks, to seeing which networks any individual belongs to.
This advancement brings hope to those looking to understand a complex system, such as cancer, the ecosystem, terrorism, the web, or anyplace anyone has collected mountains of information. By expanding our ability to analyze and observe networks we can ask new questions, and develop better predictions for how systems might behave. In a real sense, everything is a system.
On that note, looking at networks can be tricky. I’m usually a visual kind of guy. I like pictures. In my search for describing networks to folks, I came across Levitated. Their site has an amazing selection of open source software for visualizing information. I think the combination of visualization software from levitated and algorithms like those released this week in Nature will reveal the mighty networks around us in all their glory. Any thoughts as to what networks you’re a part of?
This is fascinating information on networks. I'm wondering just how far reaching the application will go. I'm trying to work with the city of Austin, Texas, to see if they'll re-thinking the layout of pedestrian and bicycle trails to follow the stucture of a network, structured around main "hubs" of activity. I'm confident such a structure would be more efficient and effective, but the factors to consider when evaluating such a network seem insurmountable.
I love this problem Joe –it is an excellent example of thinking about networks, and gives me a chance to whip out my biomimetics thinking cap. I’ve noticed that most often networks are organically constructed- by which I mean that they are not usually constructed in one sitting by an architect or urban planner, but through time they evolve. Just look at the city streets in any non-planned city -like Boston. At the other end of the spectrum check out L.A. - it does not have a network construction…and people notice. Los Angeles is not a friendly place to bicycle or walk. So, your task is to mimic ‘organic’ growth of a network for Austin which enables people to enjoy their strolling and biking while hitting the major hubs in the city.
For your problem there probably already is a network of geographical locations in Austin people want to visit by bike or by hoofing it. The trick now is to figure out the groups of people who use these locations and what else they are doing –or what other networks they are a part of. The algorithm described in the nature paper above is EXACTALLY what you need for this. I think this is a very interesting project- perhaps other Treehugger readers have some ideas for your network, or know of a way to grab data about Austin.