Hi Greg,

I've written a Data Carpentry lesson on data provenance, which makes use of
a very simple package I've written called cmdline-provenance:

   - Lesson:
   https://data-lessons.github.io/python-aos-lesson/09-provenance/index.html
   - Package: http://cmdline-provenance.readthedocs.io/en/latest/


Cheers,
Damien

On Sun, Aug 12, 2018 at 9:13 AM, Greg Wilson <[email protected]> wrote:

> Hi,
>
> Back in the Stone Age, Software Carpentry's lessons spent a few minutes
> discussing data provenance:
>
> - Include the string '$Id:$' in every source code file - Subversion would
> automatically fill in the revision ID on every commit to turn it into
> something like '$Id: 12345'.
>
> - Print the script's name, the commit ID, and the date in the header of
> every output file (along with all the parameters used by the script).
>
> It wasn't much, and I don't know how many people ever actually implemented
> it, but it did allow you to keep track of which versions of which scripts
> had generated which output files in a systematic way.
>
> So here we are today in what I hope is research computing's Bronze Age,
> and I'm curious: what do you all actually do to keep track of data
> provenance?  What tools or methods do you use to record which programs
> produced which output files from which input files with which settings and
> parameters?  I was excited about the Open Provenance effort circa 2006-07 (
> https://openprovenance.org/opm/), but it never seemed to catch on.  What
> are people using instead?
>
> Thanks,
>
> Greg
>
> --
> If you cannot be brave – and it is often hard to be brave – be kind.
>
>
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