Scholarship in the Networked World
Oliver Smithies Lecture
6 June 2013, 5pm
Christine L. Borgman
Professor & Presidential Chair in Information Studies
University of California, Los Angeles
Oliver Smithies Visiting Fellow and Lecturer
Balliol College, University of Oxford
Scholars are expected to publish the results of their work in journals, books, and other venues. Now they are being asked to publish their data as well, which marks a fundamental transition in scholarly communication. Data are not shiny objects that are easily exchanged. Rather, they are fuzzy and poorly bounded entities. The enthusiasm for “big data” is obscuring the complexity and diversity of data and of data practices across the disciplines. Data flows are uneven – abundant in some areas and sparse in others, easily or rarely shared. Open access and open data are contested concepts that are often conflated. Data are a lens to observe the rapidly changing landscape of scholarly practice. This talk is based on an Oxford-based book project to open up the black box of “data,” peering inside to explore behavior, technology, and policy issues.
Christine L. Borgman is Professor and Presidential Chair in Information Studies at UCLA. Currently (2012-13) she is the Oliver Smithies Visiting Fellow and Lecturer at Balliol College, University of Oxford, where she also is affiliated with the Oxford Internet Institute and the eResearch Centre. Prof. Borgman is the author of more than 200 publications in information studies, computer science, and communication. Her monographs, Scholarship in the Digital Age: Information, Infrastructure, and the Internet (MIT Press, 2007) and From Gutenberg to the Global Information Infrastructure: Access to Information in a Networked World (MIT Press, 2000), each won the Best Information Science Book of the Year award from the American Society for Information Science and Technology. She conducts data practices research with funding from the National Science Foundation, Sloan Foundation, and Microsoft Research. Current collaborations include Monitoring, Modeling, and Memory, The Transformation of Knowledge, Culture, and Practice in Data-Driven Science, and Empowering Long Tail Research.