Thank you all for your thoughts! Am linking to this thread in 
https://github.com/econ-ark/HARK/issues/188 which includes further discussion, 
and a link to a NumFOCUS mailing list thread.

On 08/03/2018 02:29 PM, Allen Lee wrote:
> Just dashing off a quick email but I would go with OSF if your primary aim
> is preserving the source code, datasets, documentation alongside the piles
> of necessary metadata and other digital context. If you'd like to make that
> Github repository citable then Zenodo is an easy way to generate a DOI for
> particular release changeset (http://about.zenodo.org/). For reference, the
> Force11 software citation principles are worth reviewing:
> https://www.force11.org/software-citation-principles
> 
> There are a few emerging platforms like http://wholetale.org/ and
> https://codeocean.com/ but as they are new it's hard to say if it's a safe
> bet for digtial preservation.
> 
> Shameful plug: we have also been providing computational model archival for
> agent based models since 2007 @ https://www.comses.net/codebases/ but this
> is more tailored towards computational models of social and ecological
> systems.
> 
> --
> Allen Lee
> Associate Research Professional
> Center for Behavior, Institutions, and the Environment <http://cbie.asu.edu>
> Network for Computational Modeling in the Social and Ecological Sciences
> <http://comses.net>
> Arizona State University
> Mail Code: 4804
> Tempe, AZ 85287
> *p: *480-727-4646
> *email: *[email protected]
> *web: *https://github.com/alee
> 
> 
> On Fri, Aug 3, 2018 at 9:24 AM Sumana Harihareswara <[email protected]>
> wrote:
> 
>> Friends and neighbors: what platforms for reproducible science (including 
>> scientific computing) do you recommend? As in, "in order for you to verify 
>> my results, you can go to this webpage/repository/etc. and download the data 
>> I used and the code I wrote, and run the same models/experiments to verify 
>> and reproduce my findings"? And is there an existing platform and site that 
>> economists in particular gravitate toward, and does it make a difference if 
>> the language in question is Python?
>>
>> I'm helping a client who wants to avoid reinventing the wheel. I include a 
>> note about them & their current approach at the bottom of this email.
>>
>> There seem to be many different software projects and archives I should 
>> explore, such as:
>>
>> * LabTrove http://www.labtrove.org/aboutus/ (example: 
>> http://malaria.ourexperiment.org/ )
>> * Dryad https://datadryad.org/
>> * Open Science Framework https://osf.io/
>> * figshare https://figshare.com/
>> * RunMyCode http://www.runmycode.org/
>> * DAT https://datproject.org/
>> * finding a particular existing Dataverse or VisTrails instance? 
>> https://dataverse.org/ https://nyu.reproduciblescience.org/vistrails/
>> * ScienceFair http://sciencefair-app.com/ maybe?
>> * Stencila https://stenci.la/ maybe?
>> * use GitHub plus Jupyter notebooks or something like ReproZip 
>> https://www.reprozip.org/
>>
>>
>> Sorry if I'm lumping together things that are quite different from each 
>> other! I'm at a bit of a loss here and may have missed a foundational 
>> explanation/directory.
>>
>> My client's currently got a standalone GitHub repository: 
>> https://github.com/econ-ark/REMARK . I'll excerpt from their README to 
>> explain:
>>
>>
>> This is the resting place for self-contained and complete projects written 
>> using [our tools].
>>
>> Each of these resides in its own subdirectory in the REMARKs directory
>>
>> Types of content include (see below for elaboration):
>>
>>     Explorations
>>         Use the Econ-ARK/HARK toolkit to demonstrate some set of modeling 
>> ideas
>>     Replications
>>         Attempts to replicate the results of published papers written using 
>> other tools
>>     Reproductions
>>         Code that reproduces the results of some paper that was originally 
>> written using the toolkit
>>
>> ...
>>
>> Code archives should contain:
>>
>>     All information required to get the replication code to run
>>     An indication of how long that takes on some particular machine
>>
>> Jupyter notebook(s) should:
>>
>>     Explain their own content ("This notebook uses the associated 
>> replication archive to demonstrate three central results from the paper of 
>> [original author]: The consumption function and the distribution of wealth")
>>     Be usable for someone wanting to explore the replication interactively 
>> (so, no cell should take more than a minute or two to execute on a laptop)
>>
>>
>> Much thanks. I would be happy to hear, for instance, "use this" or "it 
>> depends very heavily on your needs, but DON'T use these because they're 
>> vaporware/super-buggy".
>>
>> --
>> Sumana Harihareswara
>> Changeset Consultinghttps://changeset.nyc
>>
>>
>> P.S. Tried to send this earlier and it didn't seem to post, so, sorry if
>> this double-posts.
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>>

-- 
Sumana Harihareswara
Changeset Consulting
https://changeset.nyc

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