On Thu, 2008-07-24 at 00:57 -0500, [EMAIL PROTECTED] wrote:
> The Ecole Polytechnique Federale De Lausanne has introduced 
> an online journal for reproducible research at:
>   <http://rr.epfl.ch/17/>
> 
> The introductory headline reads:
> 
>   Have you ever tried to reproduce the results presented in a research
>   paper? For many of our current publications, this would unfortunately
>   be a challenging task. For a computational algorithm, details such as
>   the exact dataset, initialization or termination procedures and precise
>   parameter values are often omitted in the publication for various
>   reasons. This makes it difficult, if not impossible, for someone else
>   to obtain the same results. To address the problem, we have started
>   making our research reproducible. Instead of only describing the 
>   developed algorithms to 'sufficient' precision in an article, we give
>   readers access to all the information (code, data, schemes, etc) that
>   was used to produce the presented results as first advocated by Knuth
>   and Claerbout. We are convinced that making research reproducible is
>   not only a matter of good practice, but also increases the impact of
>   our publications and makes it easier to build upon each other's work.
>   It is a clear win-win situation for our community: we will have access
>   to more and more algorithms and can spend time inventing new things
>   rather than recreating existing ones.

I have a number of links to "reproducible research" from the R langauge
- it's a big deal in the R community. R has its own literate programming
tool set -- it's patterned after "noweb" but has no external
dependencies. In addition, there is an excellent LyX front-end to all of
it.
-- 
M. Edward (Ed) Borasky
ruby-perspectives.blogspot.com

"A mathematician is a machine for turning coffee into theorems." --
Alfréd Rényi via Paul Erdős



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