In this manifesto, we put forward the idea of data alchemy as a narrative device to discuss storytelling and transdisciplinarity in visualization. If data is the prima materia of modern science, how does one perform the Great Work? We use text-to-image diffusion-based generative art to develop the concept, and structure our argument in ten propositions, as if they were ten issues of a comic novel on data alchemy: Ad Disco Diffusionem. To follow the argument, the reader must immerse themselves in our miro board, and navigate a multimedia semiotic topology that includes comics, videos, code demos, and ergotic literature in a true alchemic sense. By accessing this paradigm one might find new sources of inspiration for scientific inquiry in familiar places, or get lost in the creative exploration of the unknown. Our colorful, sometimes poetic, exposition should not distract the reader from the seriousness of the ideas discussed, but ultimately it is about the journey.
Cite
@article{arxiv.2208.03998,
title = {I Learn to Diffuse, or Data Alchemy 101: a Mnemonic Manifesto},
author = {Victor Schetinger and Velitchko Filipov and Ignacio Pérez-Messina and Ethan Smith and Rodrigo Oliveira de Oliveira},
journal= {arXiv preprint arXiv:2208.03998},
year = {2022}
}
Comments
Submission to IEEE alt.vis 2022. Short paper containing a 4-page comic, and an immense amount of content in a linked miro board