Visual Exploration of Complex Networks

jweebo writes "Seed magazine has a story on complexity, and how it can be visually represented with fascinating results. From the article: 'Complexity is everywhere. It's a structural and organizational principle that reaches almost every field imaginable, from genetics and social networks to food webs and stock markets ...Collected here are a few of the many intriguing, and often beautiful, images that illustrate how the whole is more than the sum of its parts.'"

Comments

visualizing large-scale information

[Nick Mitchell]

as far as I can tell, the article only gives one quantification of the scale these folks are dealing with: on the order of tens of thousands for that one case. is this what is considered large? the point of visualizations is to show patterns of nodes (and patterns of paths) in graphy structures. at some point, one runs into one or the other of various limits:

1. pixels on the display: 2 million or so.
2. insufficiency of the clustering algorithms: showing one pixel per node and random placement, or placement by DFS traversal? for trees, or for graphs where classification is the primary concern, then tree-map or "Csoft" views scale relatively well in this regard, but what about for more general problems?
3. implementations (or algorithms) that don't scale: e.g. graphviz uses n^2 (n=#nodes) space for its graph layout!

one must always think about the summarization criteria: what aren't you going to show? how will you indicate that summarization has occured? how do you denote drill-down capability? what will the form of drill-down be? what heuristics should you use to selectively deaggregate, in order to highlight potentially interesting subgraphs? for large-scale info, this is as important as what you will be showing, and how it will be shown! for our stuff, we have graphs with tens of millions of nodes.