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From: "Ludovic Courtès" <ludovic.courtes@inria.fr>
To: zimoun <zimon.toutoune@gmail.com>
Cc: guix-devel <guix-devel@gnu.org>, guix-hpc@gnu.org
Subject: Re: “Reproducible research articles, from source code to PDF”
Date: Thu, 18 Jun 2020 09:31:16 +0200	[thread overview]
Message-ID: <87k104omnv.fsf@inria.fr> (raw)
In-Reply-To: <864kraxjau.fsf@gmail.com> (zimoun's message of "Wed, 17 Jun 2020 09:06:49 +0200")

Hi Simon!

zimoun <zimon.toutoune@gmail.com> skribis:

> For example, they are future bridges to think: connect the Guix archive
> somehow with zenodo DOI and/or Software Heritage identifier.
>
> When I read this comment in the review [1]:
>
>         As  a final  note,  I  wonder if,  and  how  much, the  author's
>         approach to reproducible computation/automated report generation
>         is  feasible  for  the  average scientist,  in  particular  when
>         compared to tools with a smoother learning curve, such as Docker
>         containers,  Jupyter notebooks,  R  Markdown  documents and  the
>         like. A brief  analysis of this topic with  a clear presentation
>         of the  advantages of  the author's  approach in  the Discussion
>         session would be worthwhile.
>
> and then the Konrad's answer [2], I asked myself what pieces are
> missing.  And what could be the articulation of "guix pack -f docker",
> Guix-Jupyter or other notebooks (RMarkdown, Org)?  And what could be a
> practical workflow? (Keeping in mind that the average scientist is not a
> Linux guru but often run MacOS or Windows.)
>
> 1: https://github.com/ReScience/submissions/issues/32#issuecomment-633739558
> 2: https://github.com/ReScience/submissions/issues/32#issuecomment-634149030

I don’t like the phrase “average scientist”, and we’re talking about
people with a PhD who definitely know how to learn.

Apart from that, I agree with the comments above: putting it in the
hands of scientists will be the real challenge.  I think providing
modules and ready-to-use “templates” for people who use R+RMarkdown, or
LaTeX, or Jupyter, etc. is a necessary step.

> Half-related to the blog post.  You mention elsewhere this baby channel
> [3], maybe it could be worth to link it somewhere in the blog post.
> Moreover, totally unrelated, I feel it lacks a list of "Scientific"
> channels, as [4] or [5], maybe on hpc.guix.info
>
> 3: https://gitlab.inria.fr/guix-hpc/guix-past
> 4: https://github.com/BIMSBbioinfo/guix-bimsb
> 5: https://gitlab.inria.fr/guix-hpc/guix-hpc

<https://hpc.guix.info/about/> has a list of channels.  I’ve added Guix
Past now.

Thanks for your feedback!

Ludo’.


  reply	other threads:[~2020-06-18  7:33 UTC|newest]

Thread overview: 15+ messages / expand[flat|nested]  mbox.gz  Atom feed  top
2020-06-16 12:25 “Reproducible research articles, from source code to PDF” Ludovic Courtès
2020-06-17  7:06 ` zimoun
2020-06-18  7:31   ` Ludovic Courtès [this message]
2020-06-18  9:37     ` Konrad Hinsen
2020-06-18 11:42       ` Ludovic Courtès
2020-06-18 12:56         ` zimoun
2020-06-18 13:05           ` Ludovic Courtès
2020-06-18 16:28             ` Konrad Hinsen
2020-06-19 12:04               ` Ludovic Courtès
2020-06-19 12:14                 ` zimoun
2020-06-19 13:21                   ` Ludovic Courtès
2020-06-21 14:50               ` Konrad Hinsen
2020-06-22  7:38                 ` Ludovic Courtès
2020-06-18 16:39             ` Pjotr Prins
2020-06-18  2:33 ` Maxim Cournoyer

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