A Month of Arcolnets

Arcolnets are the latest part of my Revisualizing the Visual project (the earliest aspects are here), and every Monday and Friday in February I will be posting examples of them.

Arcolnets (=Arbitrary Color Networks) also build on the arbitrary numbers from images, just as Cyclartcy does. The basic idea is simple, and has three parts:

  1. Select points/pixels from an image in some way
  2. Construct an abstract network/graph, by connecting points/pixels based on some criteria
  3. Draw (=visualize) the abstract network in some way

If I were Sol Lewitt I might leave it that. But I’m not, so I don’t.

Selecting the points can be done in a variety of ways, from purely geometric (for example, a grid of 100 x 100 points), to random, to arbitrary, to some combination of geometric and random or arbitrary. While I have experimented with all of these, I have settled on using either arbitrary or geometric + arbitrary selection.

Similarly, the criteria for connecting points/pixels can be purely geometric (for example, connect two points if they are closer than 5 units apart), random, arbitrary, or based on some color property (for example, connect two points if they have similar hues). Not surprisingly given that the name of this blog is “Arbitrary but not random”, I do not use random criteria.

Finally, while there are numerous ways to visualize networks, I use standard node-link diagrams since the positions of the nodes correspond to the original points, with various parameters for how the nodes and links are drawn.

These three phases and the variations within them lead to an incredible range of visualizations, perhaps more than any other of my Revisualizing the Visual projects. When I was first exploring the breadth of Arcolnets, I felt like a visual gourmand, feasting on the richness of the resulting images. For the month of February, I’ll give you a taste of that feast, using the same photograph as the basis for all of the Arcolnets. Technical details will follow later.

As an amuse-bouche, here are two Arcolnets whose visualizations were inspired by these two Wikipedia entries about random networks. (“SJP” in the names refers to the original photograph taken in San José, California) Click on the images to see them larger. Bon appetit!

SJP: RSG © 2022 Chris Culy

SJP: Unit © 2022 Chris Culy