Harnessing Quantitative Eye Tracking Data to Create Art: Interdisciplinary Collaboration and Data Visualization

Abstract

Interdisciplinary collaboration in the use of digital tools serves to illuminate new means to employ humanities and social science technology to produce aesthetic objects. Eye tracking technology permits volumes and types of data that were hitherto unimaginable in cognitive science-based methodologies, and the software tools of an eye tracker such as ours allow for interesting and useful empirically-based understandings of the data. Yet, in our explorations of the data we conclude that a purely empirically-based output has limitations: the data can be put to further uses, pushing into the realms of data visualization, art, as well as into epistemological considerations for the processes involved in managing and exploring data. How can eye-tracking data serve both objectively-based aims and artistic ones? Our specific focus in this paper is to document our deliberate move to shift the data toward ‘data art’, ‘mind art’, and other aesthetically-oriented modes as we develop interventions with the large volumes of data that the advanced technology of our eye-tracker produces.