Associative Forms for Encoding Multivariate Climate Data

Francesca Samsel, Greg Abram, Catherine L. Bowma, Daniel F. Keefe

Room: 103

2023-10-24T23:45:00ZGMT-0600Change your timezone on the schedule page
2023-10-24T23:45:00Z
Exemplar figure, but none was provided by the authors
Abstract

We are perpetually present in our environment, experiencing it with our senses. Scientific data describes the same environment quantitatively. Our goal is to use scientific and artistic methods to combine these environmental expressions and personal experience through the creation of glyphs visually abstracted from and associated with forms in nature in the representation of climate data. The use of these glyphs removes the distinctions between scientific data and sensory experience, to allow a fuller intuitive association between the two, creating an embodied experience and increasing awareness of the climate effects and changes all around us.