Computational basis and ReproIn/DataLad: Reference

A command line shell is a powerful tool and learning additional ‘tricks’ can help make its use more efficient, less error-prone, and thus more reproducible

Shell scripting is the most accessible tool to automate execution of an arbitrary set of commands. This avoids manual retyping of the same commands and in turn avoids typos and erroneous analyses

Distribution and version control systems allow for the efficient creation of tightly version-controlled computation environments

DataLad assists in creating a complete record of changes

Food is necessary for our survival

Food cannot be controled/distributed by Git, but recipes could/should

we can implement a complete imaging study using DataLad datasets to represent units of data processing

each unit comprehensively captures all inputs and data processing leading up to it

this comprehensive capture facilitates re-use of units, and enables computational reproducibility

carefully validated intermediate results (captured as a DataLad dataset) are a candidate for publication with minimal additional effort

the outcome of this demo is available as a demo DataLad dataset from GitHub