|AM08 2008||START Conference Manager|
The growth in data production and storage related to science, technology, engineering, and mathematics (STEM) research has been attributed to the development and proliferation of enabling technologies and computer networks associated with cyberinfrastructure advancement, including sensors and sensor networks, high-throughput technologies and instrumentation, automated data acquisition, and computational modeling and simulation. [NSF, 2007] While the technical and societal forces encouraging scientists to produce this born-digital content continue unabated, attention to their resulting burden of managing this content for access and use has lagged behind. LIS-trained practitioners could contribute information management infrastructure to aid scientists but this infrastructure would have to be oriented to the variety of local, idiosyncratic, field-based approaches currently extant. [Borgman, 2007] A campus-wide census of data management practices at a Carnegie Classification Research II institution identifies what the variety of faculty data management practices is across the STEM departments.
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