Touching Big Data

Garden Street: Lower Level

Our traditional, ‘ocularcentric’ methods of visualizing big data allow researchers to mine information, decode patterns, and deconstruct complex networks. Data visualization is meant to increase understanding, but what if we wish to experience big data? My current research aims to make data palpable, tangible, and tactile through the integration of somatic informed dance practices, human-computer interaction (HCI) design methods, and digital humanities scholarship. It is here I ask, how do and why would we create palpable experiences of big data? Haptics is a rapidly growing research field, but it tends to relegate touch to the hands and aims to mimic real-world experiences such as walking on gravel or feeling cotton. Little has been done to explore its potential for representing abstract information such as big data. This is partially due to the conflict between traditional empirical approaches to design and the deep, first-person somatic knowledge needed to understand our sophisticated sense of touch. In this lect/dem, I will present my current research into somatic approaches to big data haptification. Using what Thecla Shiphorst calls experience modeling, my work moves away from the empirical need to categorize haptic aesthetics and aims instead to provide experiential frameworks for describing one’s own felt experience. To anchor the work, I will share two transdisciplinary projects. First is “Vibrant Lives,” a performance/installation that gives audiences a real-time experience of their mobile device’s data output. The second, “Me, My Quantified Self, and I” is a dance theatre performance in which big data is explored through live dance performance, digital music, and data haptification.