Author: Ozioma Chukwukeme

As I work on my final project my vision for it continues to morph. However, at the foundation of my inspiration lies topographic maps and the interaction between vision/color and sound. When looking for line inspiration I stumbled upon works by Joshua Bagley. Bagley uses processing to create intricate works of art which feature a lot of geometric figures. I was especially drawn to his line-based works that reminded me of doodles but are able to convey different personas.

I specifically used instagram as a resource to find what artists were creating under the #p5js tag so I could find inspiration for techniques that I would actually be able to employ. I also personally resonated with works by Andrea Diotallevi who uses p5js to create colorful linework which is almost exactly the same idea as my topographic-esque doodles.

I then looked for examples similar to the scene above, but also incorporated motion. For that I checked out openprocessing.org for inspiration. Here I found tons of examples of line animation using processing with fairly simple code:

I was surprised to find that a lot of artists who post their work on processing had similar ideas to mine. I would like to take my work a step further however by incorporating sound which I plan on using Google’s Magenta.JS to do. Magenta is a javascript library/API that uses Google’s machine learning models.

The project I dove into is called “Architecture of Radio”. It is an application created by Richard Vijgen in 2016. The project is meant to visualise the invisible radio signal networks that we are constantly surrounded by dubbed the “infosphere”. The infosphere is an interdependent environment of invisible networks that is made up of “informational entities”. These signals come from cell towers, wifi routers, and various types of satellites. The application is site-based meaning that it’s appearance morphs based on your geographic location and where your device is pointed to. In the video demonstration we see the lines of the network shift, shrink, and grow as the user moves around which shows us how these invisible networks actually behave in 360 degrees. The application relies on openly available data which includes almost 7 million cell towers, 19 million wifi routers, and hundreds of satellites. 

What drew me to this project was the initial appearance of it. The blue and white map reminded me of something I’d see in some futuristic sci-fi movie. Like some piece of technology that’s meant to look completely advanced and impossible, however the Art of Radio is very much a living representation of the present and not the future. Vijgen could’ve represented the infosphere in so many ways: dots, lines, pink or green or yellow circles but he chose this specific appearance for the project. It’s clean and simple, yet is a spectacle once you understand what you’re looking at. It opens the observers eyes and lets them into a world that you’d never get to see otherwise. I suppose the algorithm that makes this infosphere visualization might be quite complicated. It’s constantly taking in millions of data points that change each frame, and mapping them out. For this I’d assume the code takes in the coordinates of the current location and the signals passing through it at that exact time, then draws a line to symbolize the origin, direction, and destination of the signal.

Mimi Onuoha is a Nigerian-American researcher and artist who has produced work examining the implications of data collection. In her Eyeo Talk – “How We Became Machine Readable” Onuoha discusses the practice of data collection, and how something seen as objective and accurate can be skewed and riddled with bias in reality. 

In data science, people are seen simply as objects of data collection. In project called *69, Onuoha uses men who catcall her as objects of data collection. She was moved by emotion which is evident in the fact that she took note of how she felt after every “grotesque” interaction. To collect her data on these catcallers, Onuoha puts herself on the frontlines of the experiment by handing a fake phone number to the assailant herself. She then uses an automated system to send them a message about how their actions made her feel. In this specific project Onuoha notes that neither the manner in which the numbers were collected nor what she did with them afterwards have any importance. What matters is what led to the generation of the dataset–a factor which is often overlooked. In this case it was men who couldn’t keep their vulgar comments to themselves. Someone who reviews this data with all its context has no choice but to feel the emotion that Onuoha felt firsthand: confusion, anger, vulnerability. Onuoha puts humanity back in data, or in her words, “reunites artifacts with the process of collection”.

In her experiment to reveal subjectivity in data disguised as a “visualisation project” Onuoha collects geolocation data from various groups of people–families, coworkers, roommates, partners–and comes to another conclusion about data: “If you haven’t considered the collection process you haven’t considered the data”. Datasets are the results of their means of collection and scientists tend to prioritize things that fit patterns of collection in order to eliminate outliers. However these outliers are essential to a complete dataset. Although it tends to resist metrification, is harder to collect, and can even be beneficial in its non-existence, these”complicating factors” as Onuhoa calls them reveal patterns of exclusion that are all too common in data collection, and can negatively impact entire communities of people.

By sharing this knowledge with people, that data collection is “contextual” and “mediated”, Onuoha hopes to level the knowledge playing field and prompt people to think more critically about where their data is coming from.