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Session Submission Type: Traditional (Closed) Panel
What can we make of data that is neither raw nor pure? STS social scientists have long studied the ways in which data are heterogenous, originating in a multiplicity of contexts, as well as hybrid, composed of diverse entities and activities. Ongoing research in this area, now dubbed critical data studies, is focused primarily on the political and ethical implications of understanding communities shaped by data. In parallel to these efforts, we pursue critical data practices, which make use of design inquiry to reframe the way those communities do their work. In the spirit of the theme of (In)Sensibilities, this session will call particular attention to design, art, craft, and other making practices that strive to render data as coherent, despite the seamfulness of both data and the hands-on practices we employ. Across our individual presentations, we will explore a common theme: how to slow and reconfigure existing practices in order to better understand, appreciate, and in some cases foster the heterogeneous and hybrid entanglements of data, rather than simply rushing to make data work in instrumental ways. In particular, we seek to reimagine the balance of digital and analog methods in collecting and constructing data, the interplay of humans and nonhumans in data practices, and the organizational and technical infrastructures that make data legible. Throughout our individual presentations, we will draw attention to designerly forms of inquiry, and how those methods and techniques mesh and contrast with those of social science.
Civic Data Practices as Care - Carl DiSalvo, Georgia Institute of Technology
Socio-Technical 'Patchwork' in the "Smart City": Predictive Platforms, Civic Imagination and Anticipatory Urbanism - Laura Forlano, Illinois Institute of Technology
Data Biographies for Critical Data Pedagogy - Catherine D'Ignazio, Emerson College; Yanni Alexander Loukissas, Georgia Institute of Technology
Meaningful Inefficiencies: Encounter, Play and Dialogue in the Smart City - Eric Gordon, Emerson College
Decomposing Data - Hanna Rose Shell, Massachussetts Institute of Technology