[Numpy-discussion] SciPy Journal

[Travis Oliphant]

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.  

-Travis