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Preprint . 2017
License: CC BY
Data sources: Datacite
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ZENODO
Preprint . 2017
License: CC BY
Data sources: Datacite
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Textility Of Code: A Catalogue Of Errors

Authors: Griffiths, Dave; McLean, Alex;

Textility Of Code: A Catalogue Of Errors

Abstract

This article presents a series of informal experiments in software and weaving, most of which were conducted as part of the Weaving Codes, Coding Weaves project. Different aspects of weaving, including plain weave, a four-shaft loom, tablet weaving and warp-weighted weaving are simulated, in order to gain greater understanding of the craft from the perspective of computer science. The production rules of L-Systems are employed to begin to explore the expansive possibilities offered even by our simple simulations. In order to test our models and gain deeper understanding, the languages we produce are interpreted both as computer simulations and by our human selves, through the weaving of textile by hand. Physical user interfaces are introduced, in order to help communicate the structures and thought processes of weaving. Finally, we share our approach to representing a weave from the point of view of a thread. Throughout, our aim is not to simulate a weave in its entirety, but to gain and share insights into its complexity, and begin see how the long history of weaving, as a fundamentally digital yet ancient craft, can inform the younger fields of computer science and engineering. This is the open-access author’s version of a closed access article published by Taylor and Francis in TEXTILE: Journal of Cloth and Culture, May 2017. It is shared under the terms of the Creative Commons Attribution 4.0 license, with doi: 10.5281/zenodo.832582 .

This work was supported by the Arts and Humanities Research Council, under Grant AH/M002403/1 (Weaving Codes, Coding Weaves).

Keywords

Weaving, Coding, Simulation, L-Systems, Digital Craft, Looms, Scheme, Haskell

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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