Jason Salavon is an artist whose medium is primarily computational data and algorithms. His own designs analyzes a wide variety of communal material, such as art, media, and places, that have some form of irregular similarity, and then blend them together into shifting images that become more generalized and more typical of the common things seen in everyday life. He has his own custom software that typically overlay a multitude of photos, which then averages the visual results into an artistic composition, or takes in processed media into various layouts. Essentially, Salavon seeks out individual elements of highly diverse visual culture and determines hidden norms that could link together a relationship between groups and individuals. He presents a different perspective to things that are commonplace, thus making the material interesting again.

<Color> Wheel is a data composition piece that reorganizes thousands of images from search engine data that has been received by queries for color terms. The software produces a standard, tertiary ROYGBV color wheel made up of the search result images recorded based on their dominant color. An expansive color wheel produces a different lens to look through search engine data, from the regular to the more amoral information being requested by users.

I became interested in a project called Random Shopper made by Darius Kazemi. It demonstrates random consumerism. It is basically an automated browser that helps users to purchase random things with a total of under $50. Users will not know what the purchased items are until they are shipped.

This project makes me think of some current clothing rental platforms e.g. Le Tote that make use of people’s obsession towards such randomness to rent random items out to users each month. A mail box containing random items will be shipped to users’ house based on their dressing preference. And users pay monthly rental fees for the service.

Similar projects like this make me think of more possibilities we may create in the future to make use of such randomness and people’s preference towards surprises than things that are fixed. This sense of out of control yet in control gets me interested.

In his 2015 Eyeo talk, Zach Lieberman talked about his interaction with points and lines with code, as well as discussing the connections and stories that comes from them. He also talked about the School for Poetic Computation that he co-founded. The school fosters an open environment and culture for projects that works in the realm of code and poetry, both physical and digital.

Lieberman talks about one of his projects, Play the World, where he created a piano that plays different sounds from different parts of the world. He took music and sounds from various radio stations and used a program to find instances where it plays or sounds like it is playing a certain music note. Each key on the piano would then be able to play its note from various parts of the world. Lieberman also allows the user to visualize where the note originated from, by having the location highlighted on a world map. With the installation of this project, the piano is surrounded by a circle of speakers, with each corresponding to an area of the world. When the piano plays a note from a certain area, the sound will come from a certain speaker. Thus adding a directional aspect to the project that is based on sound.

Artist: Mimi Onuoha

Project: Pathway

As part of the 2014-15 Fulbright-National Geographic Digital Storytelling Fellowship, Pathways was created by data researcher and artist Mimi Onuoha. In this project, she collected a month-worth’s geolocation data and message metadata from four groups of Londoner, including a family, a couple, roommates and three co-workers. All the data was collected between November 2014 and April 2015. The aim is to use mobile data to see how common relationship can be reflected by digital data. For example, co-workers were wondering if their friendship was just about work or if it extended beyond that, and they wanted to know if they cans see this on the data. Roommates were about to leave each other, and they want to see how Goodbye looks like on their data. The data of family was gathered before and after 2 weeks of birth of their first child, so the data was about a new person coming into the world. And the couple was in a long-distance relationship, so Mimi collected their social metadata about how and when they contact with each other, as if the data was telling their love stories.

here’s pictures of some data.