So what is the purpose of data citation? It is, as I see it, to give credit and make authors accountable, and to aid in the reproducibility of science. This is a way we could cite data:
Cline, D., R. Armstrong, R. Davis, K. Elder, and G. Liston. 2002, Updated July 2004. CLPX-Ground: ISA snow pit measurements. Edited by M. Parsons and M. J. Brodzik. Boulder, CO: National Snow and Ice Data Center. Data set accessed 2008-05-14 at http://www.nsidc.org/data/nsidc-0176.html.
In this example, we have a description of a dataset. It shows the proper citation of certain data out of the total number of entries, who is responsible for the dataset, who edited it, what was the location, and when it was last accessed online. The latter element may be important for some continuously changing datasets (e.g., time-series weather records); it is often much less important than a specific version number or revision date of the dataset. This, of course, assumes that the data “publisher” both maintains a clear history and can provide access to specific revisions of the dataset.
While it is not difficult to specify these elements for a data citation, even this fairly simple citation format received negative feedback from some researchers in my field. Some of my colleagues and students said: “We cannot possibility remember all those things. It is just too hard.” This suggests that, at least in some fields and disciplines, the cultural challenges may be greater than the technical ones.
Let me conclude with what I think is needed:
• Data collection coupled with quality control
• Quality assurance (a function of the data)
• Peer review ascertaining the authoritative source, assessed data
• Ease of publication
• Easily understood standards (especially metadata)
• Simple steps to place data in the public domain (e.g., the Polar Information Commons)
• Secure repository and long-term data curation
• Preferred use of this reliable source by data users
• Preservation of long-term data time series
• Repositories that adapt to evolving technology
• Collaboration with libraries and the publishing communities
• Ease of citation
• Credit given to data authors and proper recognition and citation by users
• Professional recognition (besides credit)
• Perhaps a change in academic mind-set.