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Peter Darch
Assistant Professor

Peter Darch
Peter Darch is an assistant professor in the School of Information Sciences at the University of Illinois at Urbana-Champaign. Prior to joining GSLIS, Darch worked as a postdoctoral researcher in the UCLA Department of Information Studies and Center for Knowledge Infrastructures, with which he continues to collaborate on studies of the building, running, and effects of information infrastructures that support scientific collaboration.

His dissertation for the DPhil in computer science from the University of Oxford (2012) addressed how scientists and software engineers in online citizen science projects manage members of the public to process and generate large datasets. This doctorate followed an MA in the history and philosophy of science and medicine (Durham University, 2006) and an MMath in mathematics from the University of Oxford (2004). He is particularly interested in the profound changes in the organization and conduct of contemporary scientific research that result from the interaction of technologies that afford collection of increasing quantities and types of scientific data with broader socio-technical factors.

To study these changes, he conducts longitudinal ethnographic studies of large, multidisciplinary scientific projects, applying theoretical approaches from science and technology studies to examine relationships between contexts in which these collaborations are embedded, information infrastructures, and scientists’ day-to-day data practices. His work has been published across a range of venues, including the International Journal on Digital Libraries and Philosophical Transactions A of the Royal Society, and he has served as a reviewer for Computer-Supported Cooperative Work journal and the Web Science conference.

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Phone: (217) 265-6595

Past CIRSS Events

December 4, 2015
Using scientific data produced by others: Trust practices shaping infrastructure, or infrastructure shaping trust practices?
Abstract:Scientists in many domains increasingly need to use data produced by others in their own work. They may be using data produced by collaborators, or they may be reusing data produced by scient…