[R] Archive format
G.Maubach at gmx.de
G.Maubach at gmx.de
Sat Apr 8 09:04:00 CEST 2017
I have read your question with great interest. I am a little bit astonished to read about your project. There is a big national institute in Germany called GESIS (https://de.wikipedia.org/wiki/GESIS_%E2%80%93_Leibniz-Institut_f%C3%BCr_Sozialwissenschaften) which does the same job you are trying to set-up since 1986 now. You could try to exchange ideas with them.
Your subject is very complex with regard to reproducible research. You might want to have a look at
(2) Gandrud, Christopher: Reproducible Research with R and R Studio (https://www.amazon.com/Reproducible-Research-Studio-Second-Chapman/dp/1498715370)
> Gesendet: Mittwoch, 29. März 2017 um 10:44 Uhr
> Von: "Joe Gain" <joe.gain at uni-konstanz.de>
> An: R-help at r-project.org
> Cc: bwfdm-info at lists.kit.edu
> Betreff: [R] Archive format
> we are collecting information on the subject of research data management
> in German on the webplatform:
> One of the topics, which we are writing about, is how to *archive* data.
> Unfortunately, none of us in the project is an expert with respect to R
> and so I would like to ask the list, what they recommend? A related
> question is to do with the sharing of data. We have already asked some
> academics, who have basically replied that they don't really know other
> than to strongly recommend a plain text format.
> We would also like to know, if members of the list recommend converting
> formats from commercial software such as S-Plus, Terr, SPSS etc. to an
> R-compatible format for long term archivation? Are there any general
> rules and best practices, when it comes to archiving (and sharing)
> statistical data and statistical programs?
> Any comments would be much appreciated!
> B 1003
> Kommunikations-, Informations-, Medienzentrum (KIM)
> Universitaet Konstanz
> t: ++49-7531-883234
> e: joe.gain at uni-konstanz.de
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> and provide commented, minimal, self-contained, reproducible code.
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