A Proposed Standard for the Scholarly Citation of Quantitative Data
Micah Altman, Gary King. 2007.
"A Proposed Standard for the Scholarly Citation of Quantitative Data".
D-Lib Magazine, 13.

Abstract
An essential aspect of science is a community of scholars cooperating and competing in the pursuit of common goals. A critical component of this 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 propose 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 data sets, 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.
See Also
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- [Paper] Education and Scholarship by Video (2021)
- [Paper] Ensuring the Data Rich Future of the Social Sciences (2011)
- [Paper] How Human Subjects Research Rules Mislead You and Your University, and What to Do About It (2016)
- [Paper] How Social Science Research Can Improve Teaching (2013)
- [Patent] Instructional Support Platform for Interactive Learning Platforms (2019)
- [Patent] Instructional Support Platform for Interactive Learning Platforms (2nd) (2020)
- [Patent] Management of Off-Task Time in a Participatory Environment (2018)