Generalized Section is a group of work in print and generative animation, illustrating the growing datascape of information permeating our lives. I am leaning on the visual tradition of generalized sections, a method of illustrating cross-sections of land where generalizations are made between points of data, producing speculative scapes for geological surveys. As an illustrator I have adopted tools in print and animation to help me celebrate, for better or worse, the aggressive growth of the datascape, as it systematically devours its prey, producing mounds of waste, piles of digital excrement extruded in disproportionately large sums to its input.
Working with as much "found" material as I can, I am writing software that scrubs the web for information, searching and sampling, treating it as a data and image bank for the taking. This requires some forfeiture of control, embracing a strong trust in the unknown as a legitimate method with which to illustrate. Images from the web flood into the animation, triggered by keywords and data originating from web-based sources. Editing becomes a lesson in probability and chance, with crescendos building and diminishing in relation to incoming information rather than that of a scored, linear, static edit. I address the data as if a chance at a formalist conversation is possible, however, the nature of the code is to consume outside of my control, in collaboration with unknown authors, producing structures without regard to such ideologies.
Generative animation is a form of moving image that is code based rather than video or film. Condition, my piece for the Generalized Section exhibition is a script, which depends on data, and images found on the web. It first parses RSS (Real Simple Syndicate) weather feeds for data and keywords. The data, such as wind speed and temperature are returned into the script to inform it as how to generate the visualizations. The keywords, such as windy or sunny are used to find images on the web that the script will alter and manipulate.
Condition refers to the ever-growing pile of data we are generating, as well; it refers to the structure of the code itself, which depends on a series of conditional statements to operate. This work states that land as something that is inseparable from data. As we continue to divide and parse land, air and water into smaller units of size and measurement, the task of illustrating the landscape relies on illustrating the datascape as well.
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