The following paper was recently presented (May 7, 2016) and published in the Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. The version below was made available by one of the co-authors.
Irene V. Pasquetto
Ashley E. Sands
Peter T. Darch
University of Illinoi
Christine L. Borgman
Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems via Selected Works of Christine L. Borgman (bepress)
Open access to data is commonly required by funding agencies, journals, and public policy, despite the lack of agreement on the concept of “open data.” We present findings from two longitudinal case studies of major scientific collaborations, the Sloan Digital Sky Survey in astronomy and the Center for Dark Energy Biosphere Investigations in deep subseafloor biosphere studies. These sites offer comparisons in rationales and policy interpretations of open data, which are shaped by their differing scientific objectives. While policy rationales and implementations shape infrastructures for scientific data, these rationales also are shaped by pre-existing infrastructure. Meanings of the term “open data” are contingent on project objectives and on the infrastructures to which they have access.
Direct to Full Text Paper (13 pages; PDF)