info systsems...

David McCandless makes infographics. These simple, elegant ways to see information boil down the too complex or too big, small, abstract or scattered to otherwise be grasped by most ( at least while just looking at it with out being bias or being in an information overload). Also his topics are sometimes quite comical. McCandless's work is if the Processing diagrams of Casey Reas and Ben Fry where frozen in space and time.

we are the world...

Chris Harrison from my alma mater Carnegie Mellon University has made these beautiful diagram of the Internet Map of the World. H retrieved his information from the Dimes Project which provides several data sets that describe the structure of the Internet. These magnificent drawings use their most recent data at the time of their creation in Feb 2007.
Chris created a set of visualizations that display how cities across the globe are interconnected. This is by router configuration and not physical backbone. So even if you try to zoom into your house, we wont see you with your laptop in your underwears. There are 89,344 connections total according to the Dimes Project. I have recently emailed him to find out how he made these, what software, and where he got his info. How reminiscent is this work to the flight 404 action? mmmm It smells like open source urbanism to me!

Movie Making Machine:

As all the pieces continue to fall (off points elevation), they are landing
in my lap in to a big pile. What if I make a machine to help collage and collate
the clips and images?

This script is supposed to work like the neurons and electrons in your brain.
Valentina Vasi and myself are making a movie making machine with processing.
Our amazing professor, Roland Snooks, has been helping us tremendously and also finds the
project to be quite interesting.

The plan is that each neuron is connected to a clip. the electrons move in between the neurons,
attracted to different assigned qualities.

Below is the code:

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import kGeom.*;
import kRender.*;

kSpace space;
brain brain1;

int envSize = 250;

void setup(){
size(500,500,P3D);

brain1 = new brain();

space = new kSpace(this);
space.cam.jump(-600,-550,-500);

// loop to make random neurons
for(int i = 0; i < i =" 0;" neurons =" new" electrons =" new" connectlist =" new" i =" 0;" n =" (neuron)" i =" 0;" e =" (electron)" i =" 0;" n =" (neuron)" i =" 0;" e =" (electron)" neuronnumber =" _neuronNumber;" history1 =" new" historyconnections =" new" magnatude =" 30;"> 0){
    // find neuron neighbors
    // loop through all neurons and find the closest
    neuron nCurrent = (neuron) neurons.get(neuronNumber);
    float closestNDist = 1000000;
    int closestN = 0;

    for (int i = 0; i < ntest =" (neuron)" ntarget =" kVec.clone(nCurrent.pos);" ntestpos =" kVec.clone(nTest.pos);" ndist =" nTarget.distance(nTestPos);" same =" false;" j =" 0;" ntesthist =" (neuron)" same =" true;" same ="="" closestndist =" nDist;" closestn =" i;" conint =" {" neuronnumber =" closestN;" nhist =" (neuron)" magnatude =" magnatude" i =" 0;" nstart =" (neuron)" nend =" (neuron)" ln =" new" currentconarray =" (int[])" duplicates =" 1;" j =" 0;" otherconarray =" (int[])" pos =" _pos;" connectthreshold ="100;" pt =" kVec.clone(pos);" class="html">
Source:
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