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. > *The Carpentries <https://carpentries.topicbox.com/latest>* / discuss / > see discussions <https://carpentries.topicbox.com/groups/discuss> + > participants <https://carpentries.topicbox.com/groups/discuss/members> + > delivery > options <https://carpentries.topicbox.com/groups/discuss/subscription> > Permalink > <https://carpentries.topicbox.com/groups/discuss/T45d1f9e935d7181b-Md42220083ebe1309e8614d9d> > ------------------------------------------ The Carpentries: discuss Permalink: https://carpentries.topicbox.com/groups/discuss/T45d1f9e935d7181b-M686f700f067dae91afd27f5f Delivery options: https://carpentries.topicbox.com/groups/discuss/subscription
