[Numpy-discussion] SciPy Journal

Alexander Michael lxander.m at gmail.com
Mon Jun 4 16:17:16 EDT 2007


On 5/31/07, Travis Oliphant <oliphant.travis at ieee.org> wrote:
> Hi everybody,
>
> I'm sorry for the cross posting, but I wanted to reach a wide audience
> and I know not everybody subscribes to all the lists.
>
> I've been thinking more about the "SciPy Journal" that we discussed
> before and I have some thoughts.
>
> 1) I'd like to get it going so that we can push out an electronic issue
> after the SciPy conference (in September)
>
> 2) I think it's scope should be limited to papers that describe
> algorithms and code that are in NumPy / SciPy / SciKits.   Perhaps we
> could also accept papers that describe code that depends on NumPy /
> SciPy that is also easily available.
>
> 3) I'd like to make a requirement for inclusion of new code in SciPy
> that it have an associated journal article describing the algorithms,
> design approach, etc.  I don't see this journal article as being
> user-interface documentation for the code.  I see this is as a place to
> describe why the code is organized as it is and to detail any algorithms
> that are used.
>
> 4) The purpose of the journal as I see it is to
>
>     a) provide someplace to document what is actually done in SciPy and
> related software.
>     b) provide a teaching tool of numerical methods with actual "people
> use-it" code that would be
>        useful to researchers, students, and professionals.
>     c) hopefully clever new algorithms will be developed for SciPy by
> people using Python
>        that could be show-cased here
>     d) provide a peer-review publication opportunity for people who
> contribute to open-source
>        software
>
> 5) We obviously need associate editors and people willing to review
> submitted articles as well as people willing to submit articles.   I
> have two articles that can be submitted within the next two months.
> What do other people have?
>
>
> As an example of the kind of thing a SciPy Journal would be useful for.
> I have recently over-hauled the interpolation.py file for SciPy by
> incorporating the B-spline stuff that is partly in fitpack.  In the
> process I noticed two things:
>
> 1) I have (what seems to me) a different recursive algorithm for
> calculating derivatives of B-splines than I could find in fitpack.
> 2) I have developed a different way to determine the K-1 extra degrees
> of freedom for Kth-order spline fitting than I have seen before.
>
> The SciPy Journal would be a great place to document both of these
> things while describing the spline interpolation design of scipy.interpolate
>
> It is true that I could submit this stuff to other journals, but it
> seems like that doing that makes the information harder to find in the
> future and not easier.  I'm also dissatisfied with how information
> exclusionary academic journals seem to be.  They are catching up, but
> they are still not as accessible as other things available on the internet.
>
> Given the open nature of most scientific research, it is remarkable that
> getting access to the information is not as easy as it should be with
> modern search engines (if your internet domain does not subscribe to the
> e-journal).
>
> Comments and feedback is welcome.

 An implementation oriented journal/newsletter in the vain of RNews
(<http://cran.r-project.org/doc/Rnews/>) would be great. [Note: I
remember seeing some mentions of the R project in various comments,
but I am not sure anyone brought RNews as a model. Please excuse me if
it was already brought up.]

About R News
R News is the newsletter of the R project for statistical computing
and features short to medium length articles covering topics that
might be of interest to users or developers of R, including

    * Changes in R: new features of the latest release
    * Changes on CRAN: new add-on packages, manuals, binary
distributions, mirrors,...
    * Add-on packages: short introductions to or reviews of R extension packages
    * Programmer's Niche: nifty hints for programming in R (or S)
    * Hints for newcomers: Explaining sides of R that might not be so
obvious from reading the manuals and FAQs.
    * Applications: Examples of analyzing data with R

Of course, any write-up of library code should also be distributed
with/in the code (doc strings) as well. Such a publication would
provide a great outlet for people to write about how they implemented
their research and would make a great companion to the publication of
the analysis and results. Additionally, the development of a good
document template and commendable examples from other contributors
would likely encourage better communication as with leading journals.
A lot of the material could be culled from the mailing lists and
should be written up in a way (and in a format) that would allow it to
be dropped into the wiki (e.g. the cookbook page) as well as included
in the publication.



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