The notion of capturing each execution of a script and workflow and its associated metadata is enormously appealing and should be at the heart of any attempt to make scientific simulations repeatable and reproducible.

Most of the work in the literature focus in the terminology and the approaches to acquire those metadata. Those are critical but not enough. Since one of the purposes of capturing an execution is to be able to recreate the same execution environment as in the original run, there is a great need to investigate ways to recreate a similar environment from those metadata and also to be able to make them accessible to the community for collaboration. The so popular social collaborative pull request mechanism in Github is a great example of how cloud infrastructures can bring another layer of public collaboration. We think reproducibility could benefit from a cloud social collaborative presence because capturing the metadata about a simulation is far from being the end game of making it reproducible, repeatable or of any use to another scientist that has difficulties to easily get them.

In this paper we define a reproducibility record atom and the cloud infrastructure to support it. We also provide a use case example with the event based simulation management tool Sumatra and the container system Docker.