[IPython-dev] Concise citations for the Scipy stack

Aron Ahmadia aron at ahmadia.net
Mon Feb 2 14:50:15 EST 2015


On Mon, Feb 2, 2015 at 2:11 PM, Mark Voorhies <mark.voorhies at ucsf.edu>
wrote:

> I'm putting together a set of "software tools" references for a paper that
> we are preparing to submit.
> I am trying to balance acknowledging as much of our infrastructure as
> possible, while minimizing the
> number of references that have no direct (i.e., unambiguously obvious to
> the reader) connection to the
> methods section of the paper (e.g., citing Tornado, git, h5py, or MySQL is
> probably going too far; likewise,
> I think it's reasonable to cite R but not rpy2).
>
> Based on http://www.scipy.org/citing.html, I think a good minimal set
> (for a paper with heavy use of
> IPython for matplotlib-based plotting, including KDEs from scipy.stats,
> and a lot of vanilla python
> sequence/expression analysis code) is:
>
> NumPy & SciPy
> Stéfan van der Walt, S. Chris Colbert and Gaël Varoquaux. The NumPy Array:
> A Structure for Efficient Numerical Computation, Computing in Science &
> Engineering, 13, 22-30 (2011), DOI:10.1109/MCSE.2011.37
>
> Matplotlib
> John D. Hunter. Matplotlib: A 2D Graphics Environment, Computing in
> Science & Engineering, 9, 90-95 (2007), DOI:10.1109/MCSE.2007.55
>
> IPython
> Fernando Pérez and Brian E. Granger. IPython: A System for Interactive
> Scientific Computing, Computing in Science & Engineering, 9, 21-29 (2007),
> DOI:10.1109/MCSE.2007.53
>
> Thoughts?
>
> --Mark
>

Hi Mark,

As I'm guessing you know, there are a number of reasons to cite academic
software.  I think first and foremost, you have a responsibility to
acknowledge contributions that were not your own.  Secondly, you also have
a responsibility to improve the credibility of your work by enabling others
to reproduce your analysis.  I agree that you should cite any software
package that implements algorithms you use for your work, as well as any
environments that are "transformational."  If you would like others to be
able to reuse or reproduce your work, it is also important to identify the
specific versions of software that you used.  In this case, I argue that
you should cite an identifier (such as release tag or git commit) as well
as a URL for obtaining that software.

The advantage of citing Git commits/tags in particular is that they also
contain complete records tracking authorship.

So my specific advice here would be to cite any papers that you found
helpful or were requested by the authors, but that you also provide a
description of the major components of the software environment (Python
libraries, sub-libraries such as HDF5) you used.

Regards,
Aron
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