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A Proposed Standard for the Scholarly Citation of Quantitative Data

Presenter 1
Micah Altman
Harvard University
Presenter 2
Gary King
Harvard University

A critical component of the scholarly and library community is the common language of and the universal standards for scholarly citation, credit attribution, and the location and retrieval of articles and books. We present a proposal for a similar universal standard for citing quantitative data that retains the advantages of print citations, adds other components made possible by, and needed due to, the digital form and systematic nature of quantitative datasets, and is consistent with most existing subfield-specific approaches. Although the digital library field includes numerous creative ideas, we limit ourselves to only those elements that appear ready for easy practical use by scientists, journal editors, publishers, librarians, and archivists.

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