The rise of data-centric research practices has uncovered shortcomings in the traditional scholarly communication system. The foundation of that system, the peer-reviewed publication—”[the] selective distribution of ink on paper, or… electronic facsimiles of the same,” according to Bourne, et al. (2011)—does not adequately support what has become an essential element of scholarship: the reproducibility of research results.

This refers to duplicating a reported result with the data, tools, techniques, etc., used in previous research. The notion of reproducible research is appealing for a number of reasons, including facilitating novel research that “builds on the shoulders of giants,” allowing the testing of veracity of existing research, and educating new scholars in common research practices.

Reproducibility depends on disaggregating and exposing the multiple components of the research—data, software, workflows, and provenance—to other researchers and providing adequate metadata to make these components usable.

The belief in the importance of reproducibility is shared by a large number of scientists, in many disciplines, who have pushed ever stronger for a modernization of the current system of scholarly communication, including support for reproducibility. In particular, we refer to the set of recommendations articulated by Stodden, et al. (2016), and which they call “Reproducibility Enhancement Principles” (REP).

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