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Managing data and code in open scientific research is complicated by two keyproblems: large datasets often cannot be stored alongside code in repositoryplatforms like GitHub, and iterative analysis can lead to unnoticed changes todata, increasing the risk that analyses are based on older versions of data.Here, I introduce SciDataFlow: a fast, concurrent command-line tool paired witha simple Data Manifest specification. SciDataFlow streamlines tracking datachanges, uploading data to remote repositories, and pulling in all datanecessary to reproduce a computational analysis.

SciDataFlow: A Tool for Improving the Flow of Data through Science