[Esip-citationguidelines] scooped in 1979

[Matthew Mayernik]

Hi Mark,
Good pointer. There was definitely a fair amount of activity around that
time regarding citation of social science data. Another article by Howard
White from 1982 (citation below) started with this sentence: "An argument
by no means new is that social scientists who work with machine‐readable
data files (MRDF) should cite them in their writings, with formal
references set apart from main text, just as they now do books, papers and
reports".
White, H.D. (1982). Citation analysis of data file use. Library Trends, 31(3),
467–477. http://hdl.handle.net/2142/7222

I am always struck by the "by no means new" in that quote. I think it
demonstrates how this is a recurring problem that has to be dealt with anew
for each generation of researchers and technologies - how/why to cite data.

Matt

On Tue, Oct 27, 2020 at 4:31 PM Mark Parsons via Esip-citationguidelines <
esip-citationguidelines at lists.esipfed.org> wrote:

> Dodd, S. A. (1979). Bibliographic references for numeric social science
> data files: Suggested guidelines. Journal of the American Society for
> Information Science, 30(2), 77–82. https://doi.org/10.1002/asi.4630300203
>
> If you are paywalled, try: sci-hub.do/10.1002/asi.4630300203
>
> A few observations:
> - it grapples with many of the same issues we do - the vagueness of how
> data are currently referenced, the inadequacy of current standards, the
> challenge of defining the citable object, the notion of machine
> readability, the confusion around terms and roles…
> - the elements it defines aren’t that much different than ours. I love
> “General material designator” sorta like type but also akin to identifier.
> They also pay good attention to versioning and author roles. Sound familiar?
> - it might have worked if the internet and then the web hadn’t followed so
> soon after.
> - the conclusion about uptake is charmingly naive (see note about internet
> above)
> - it notes the need to be able to cite data even before it is archived!
> - more evidence that social science data, especially census data, tend to
> be pioneers in data science
>
> cheers,
>
> -m.
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