Abstract
US science agencies have or will soon have a requirement that externally funded projects have “data management plans.” Projects with a large budget or a tradition of data access and repositories do not see the impact as significant. However, the impact of the requirement can be particularly challenging for single investigators and small collaborations, especially in multidisciplinary research. These data represent what is known as Dark Data (Heidorn, 2008) in the long tail of science, where the data sets may be relatively small and the funding and expertise for handling also small. But just developing tools or putting computer scientists with the investigators is not sufficient.
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Heidorn, B.P.: Shedding light on the dark data in the long tail of science. Library Trends 57, 280–289 (2008)
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© 2011 Springer-Verlag Berlin Heidelberg
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Spengler, S. (2011). Data Scientists, Data Management and Data Policy. In: Bayard Cushing, J., French, J., Bowers, S. (eds) Scientific and Statistical Database Management. SSDBM 2011. Lecture Notes in Computer Science, vol 6809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22351-8_32
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DOI: https://doi.org/10.1007/978-3-642-22351-8_32
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