Presentation is here.
Set Theory is a branch of mathematics that studies sets, or the collection of objects. In relation to Big Data, the cataloging and the creating of collections of information is where this project begins. Today, we experience this phenomenon in entirely new ways. Our whole life is cataloged and archived. Whether it be a tumbler page, an Instagram page, a digital folder of the images of your life, or a digital archive from the Metropolitan Museum of Art, everything today is both a singular data point, but also, when collected, becomes part of a set. And what defines any data point is the metadata that links it to that set of data.
<META> Methods attempts to extract beauty in the superset of information. This projects looks not at the individual (micro) but at the whole (macro) and attempts to find relationships, whether contextual, graphical or mathematical, by examining metadata.
This project also reimagines digital curation and asks the question: can a collection of digital assets become an asset, or work of art, in and of itself? Is metadata the “paint” that we can mix together, through algorithmic search, to create new “colors” in our digital “canvas”?
By applying mathematical theory to the analysis of a digital collection (set) of objects what new relationships can be uncovered and what new art can evolve? If you look at enough metadata, would you find that the set is self-similar (fractal)?
