Re-running a series of published Jupyter notebooks

[Daniel Mietchen]

Dear list,

as part of an Open Data Day event this weekend, a small group of
participants with varying Jupyter expertise looked into Jupyter
notebooks in the context of research reproducibility.

The basic idea was to go through scholarly articles available as part
of the article corpus in PubMed Central, to re-run any Jupyter
notebooks that could be found in there, and to document the
observations, as described in
https://github.com/sparcopen/open-research-doathon/issues/25 .

We have looked at about 10 of these notebooks, none of which ran
through at the first attempt. So we documented the first problem that
occurred and moved on to the next notebook, except for the example
notebook mentioned in the first post in that thread, which we tried to
get to run by addressing any of the error messages.

If you have suggestions on how best to document such a systematic
re-run of a collection of Jupyter notebooks, or if you are aware of
past attempts in this direction, we would appreciate pointers.

You are also most welcome to join in directly - we'll continue
tomorrow (i.e. Sunday 5).

Thanks and cheers,

Daniel

[Daniel Mietchen]

Here is a write-up of our attempts to re-run these notebooks:
https://markwoodbridge.com/2017/03/05/jupyter-reproducible-science.html .

[Jason Grout]

Fascinating! Thanks for doing this! I think it was a very worth-while investigation.

Jason

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