GVU Center Brown Bag Seminar: Yanni Loukissas " All Data Are Local: Thinking Critically in a Data-Driven Society"
All Data Are Local: Thinking Critically in a Data-Driven Society
In our data-driven society, it is too easy to assume the transparency of data. Instead, Yanni Loukissas argues in All Data Are Local, we should approach data sets with an
awareness that data are created by humans and their dutiful machines, at a time, in a place, with the instruments at hand, for audiences that are conditioned to receive them. The term
data set implies something discrete, complete, and portable, but it is none of those things. Examining a series of data sources important for understanding the state of public life in the United States--Harvard's Arnold Arboretum, the Digital Public Library of America, UCLA's Television News Archive, and the real estate marketplace Zillow--Loukissas shows us how to analyze data settings rather than data sets.
Loukissas sets out six principles: all data are local; data have complex attachments to place; data are collected from heterogeneous sources; data and algorithms are inextricably entangled; interfaces recontextualize data; and data are indexes to local knowledge. He then provides a set of practical guidelines to follow. To make his argument, Loukissas employs a combination of qualitative research on data cultures and exploratory data visualizations. Rebutting the "myth of digital universalism," Loukissas reminds us of the meaning-making power of the local.
Yanni Alexander Loukissas is an Assistant Professor of Digital Media in the School of Literature, Media, and Communication at Georgia Tech, where he directs the Local Data Design Lab. His research is focused on helping creative people think critically about the social implications of emerging technologies. His new monograph from MIT Press, All Data Are Local: Thinking Critically in a Data-Driven Society, is addressed to a growing audience of practitioners who want to work with unfamiliar data both effectively and ethically. Originally trained as an architect at Cornell, he subsequently attended MIT, where he received a Master of Science and a PhD in Design and Computation and completed postdoctoral work at the Program in Science, Technology and Society.