In his paper, Reproducible Research and Cloud Computing, Bill Howe asks:
What happens if you do all your work on a virtual machine hosted
in the cloud? When it came time to publish, you might make a
snapshot of the VM, make it public, and cite it in your
paper. Those who wish to reproduce your experiments would launch
the virtual machine (on their dime) and have access to your entire
experimental environment --- the code, the data, the environment,
log files, notes, etc. There would be no need to install a network
of complex, version-sensitive inter-dependent prerequisites.
Indeed, what a
idea! But not, I think, sufficient.
This idea -- that posting a VM is sufficient for reproducibility --
has hit my Twitter feed a couple of times now, and each time I feel
compelled to make the point that this isn't useful reproducibility.
Mick Watson put it best when he said you can't install an image for
every pipeline you want.
To put it another way, it is certainly true that posting a virtual
machine is a way to make your research reproducible. It's just not a
very useful way, in the sense that it effectively blocks remixing
or mashing up the code. In my post on the diginorm paper I made this point
in response to some poo-pooing of replicability:
Fifth, and probably most significant from a practical perspective,
Graham misses the point of reuse. In bioinformatics, it behooves us
to reuse proven (aka published) tools -- at least we know they
worked for someone, at least once, which is not usually the case
for newly written software.
In essence, providing a gigantic black box of custom installed code
that was installed, set up, and executed by experts just isn't
very useful to many people.
I think the ENCODE effort
did it about 3/4 right --
As part of the supplementary material for this paper, we have
established a virtual machine instance of the software, using the
code bundles from
each analysis program has been tested and run.
I could have wished that each bit of code was in a separate git or hg
repository, for example, or that there were small test data sets; this
would have maximized my ability to dive into the code and play with
it. But this is a giant step forward all on its own, compared to
what pretty much everyone else does! And it's
really fantastic to see it being done by a massive genomics
Bill Howe commented that I'm conflating the publication of "one off"
experiments (which require reproducibility) with the dissemination
of reusable software, and that we should enable the first via whatever
mechanisms we can, given the poor status quo. I disagree, mainly
because it's not capacity building: releasing shoddy VMs is easy to
do, but it doesn't help you learn how to do a better job of reproducibility
along the way. Releasing software pipelines, however crappy, is
on the path towards better reproducibility.
A related topic that also comes up occasionally is distributing
software via VM. Scott Cain gave a great talk at BOSC 2012 on Tripal, a Web interface for Chado, and
mentioned that there's a VM available.
During the Q&A I apparently confused him by recommending that instead
of, or in addition to, a VM, he provide a source code repository along
with an install script pinned to a particular Linux install --
something that's really easy to do these days, what with the clouds
and open sourciness. His response was "why would you need anything
more than the VM?" Again, the reason comes back to Mick's observation
above: you can't (or at least shouldn't need to) install a VM for
every software package or pipeline you need to execute!
If you think about the dependency chain here, it's easy to build a
VM if you automate the install process, and providing that install
script for even one OS can demystify the install process for others;
conversely, just because you provide a VM doesn't mean that anyone
other than you can install your software. So why not make life
easy for everyone?
There is a deeper principle at work here: the distinction between a
user and a maker. A user merely wants to take your software and
run with it; a maker wants to probe, remix, and mash up your
software. To maximize the benefit of our scientific software, we
should be enabling makers, not users. To do anything else limits
the use of our software to our own imagination, rather than enabling
serendipity. And wouldn't that be a shame?
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