So graphs (and its companion graph theory) are apparently the talk of the town. Cool. Graph based databases (neo4j) and other related graph based things are popping up in places where complexity is high and low.
I found graph theory mindtickling a couple of months ago when I read an extremely basic introduction to it while tinkering with AI. The first time I met it was when I started out with Processing. But the AI book was the first time I read that graphs can be anything and everything. As a graphic designer I interpreted that as a solid foundation for creating things while keeping structure intact. A math book I borrowed from a colleague (the book is way over my head) said that “apart from drawing funny pictures it can be used to calculate things in the graph” i.e. the traveling salesman problem etc. I stopped at the funny pictures-part and decided that it was something to look into a bit more. Way too heavy on the math side, but I found via Processing that algorithms are best in practice. Good if they are understood but not a necessity as long as they work (in code) as expected, and if you don’t want them to do something slightly different which I often do. The Anar library for Processing looks good for trying things out even if it focuses a little hard on parametric modeling. I intend to show information, not the architectural structure. So, the struggling to understand continues. I look forward to get it visually controlled as soon as my mind allows me to. But hey, I can always sketch in the meantime. 🙂
Graphs and graph theory has been around a long time. So nothing new really. But for a non-math designer, using the graph and its structure gives birth to lot of rules (restrictions) and thus the mind makes new paths and new stuff pops up. I will not be surprised to see a cool information graphic that looks like a flower but is really a graph underneath.