Small Data
Small Data
Experiments from Generative Design Workshop
Faculty Lead:
Zach Pino
Class:
Generative Design Workshop
Students:
Xuanyu Chen
Zeya Chen
Todd Cooke
Jesse Gao
Audrey Gordon
Grace Hanford
Hugo Hsiao
Kie Ichikawa
Sanya Karwani
Yuta Katuyama
Jessica Nelson
Mithila Kedambadi Prasanna
Adithya Ravi
Jason Romano
Jiani Sapathy
Catherine Wieczorek
Kelvin Yu
Mend by Audrey Gordon
The combination of the quantified self movement, generative design tools, and digital fabrication as a service for fulfillment and delivery has created new opportunities for contemporary designers to create personal products with personal data. We hear so often about the power of "Big Data" in design, but these 16 projects — inspired by the the data visualization works of Knut Synstad, Adrien Segal, Georgia Lupi, Stefanie Posavec, and many other generative designers — instead aim to activate "Small Data," datasets that are highly targeted, hand-logged, specific, or might be interpretable by only a single person.
These physicalized data objects aspire to reveal invisible patterns in behavior, and aim to support a newly empowered sculpting of the self — facilitated by informed data-gathering, intentionally legible and illegible data-visualization, and aesthetic provocation.
