[open-science] Open repositories

Tue Jul 6 22:57:00 UTC 2010

On Tue, Jul 6, 2010 at 11:15 PM, Jessy Cowan-Sharp <
jessy.cowansharp at gmail.com> wrote:

> didn't want to hijack the other thread so i changed the subject line, but
> i'm curious (and perhaps this is a naive question):
>
> You didn't actually change the subject so I have done so

> what open access repositories are there which people recommend, besides,
> say, arxiv.org? arxiv.org itself doesn't seem to have a strong (or at
> least not explicit) stance on licenses and such. and are there any OA
> archives where people can submit their code/data along with their paper (in
> such a way that it is formally associated with that paper?)
>
>
It's probably useful to differentiate between code/data/documents. The
current usage is:

open access - papers
open source - code
open data     - data

OpenSource is usually stored in specialist software repositories, which
should have  a powerful versioning system (SVN or better Mercurial or Git).
Typical repos are Sourceforge and bitbucket. These repos *could* be used for
otehr material (such as data or documentation but this is probably not a
good idea technically, as there is no good text search facility, etc)

OpenAccess material is usually stored in paper-oriented repos (DSPace,
Eprints, Fedora) and are commonly found in Universities and similar insts
and run by LIS staff. They are totally unsuited to software and data (go on,
someone, ask me why!)

OpenData is relatively new. The problems of storing it are considerable and
largely unsolved. Problems include versioning, dynamic updating, metadata,
formats, lack of specialist knowledge (there are (tens of) thousands of
common formats (e.g. several hundred alone in chemistry). This is my
speciality and I don't know the answer. I suspect it will be domain-specific
(e.g. biosequences, etc, are well supported at present, chemistry has
possiblle solutions but there are rabid anticommons interests in chemistry,
particle physics is huge, climate is hyperpolitical, etc.) OKF is as good a
place to start as any (though we can't store huge datasets and are more
likely to address metadata).

>

-- 
Peter Murray-Rust
Reader in Molecular Informatics
Unilever Centre, Dep. Of Chemistry
University of Cambridge
CB2 1EW, UK
+44-1223-763069
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