Hi Joe,

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

(1) https://cran.r-project.org/web/views/ReproducibleResearch.html
(2) Gandrud, Christopher: Reproducible Research with R and R Studio 
(https://www.amazon.com/Reproducible-Research-Studio-Second-Chapman/dp/1498715370)

Kind regards

Georg

> Gesendet: Mittwoch, 29. März 2017 um 10:44 Uhr
> Von: "Joe Gain" <joe.g...@uni-konstanz.de>
> An: R-help@r-project.org
> Cc: bwfdm-i...@lists.kit.edu
> Betreff: [R] Archive format
>
> Hello,
> 
> we are collecting information on the subject of research data management 
> in German on the webplatform:
> 
> www.forschungsdaten.info
> 
> 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!
> Joe
> 
> -- 
> B 1003
> Kommunikations-, Informations-, Medienzentrum (KIM)
> Universitaet Konstanz
> 
> t: ++49-7531-883234
> e: joe.g...@uni-konstanz.de
> 
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