  We present DataDeps.jl: a julia package for the reproducible handling of
static datasets to enhance the repeatability of scripts used in the data and
computational sciences. It is used to automate the data setup part of running
software which accompanies a paper to replicate a result. This step is commonly
done manually, which expends time and allows for confusion. This functionality
is also useful for other packages which require data to function (e.g. a
trained machine learning based model). DataDeps.jl simplifies extending
research software by automatically managing the dependencies and makes it
easier to run another author's code, thus enhancing the reproducibility of data
science research.
