A Realistic Guide to Making Data Available Alongside Code to Improve Reproducibility

TL;DR

This paper offers practical guidance on how researchers can effectively share data alongside code to enhance reproducibility, transparency, and trust in scientific research.

Contribution

It provides a realistic, step-by-step approach to sharing data with minimal barriers, emphasizing practical considerations often overlooked in existing advice.

Findings

Sharing data increases research visibility and trust.

Minimal barriers facilitate more widespread data sharing.

Practical steps can improve reproducibility significantly.

Abstract

Data makes science possible. Sharing data improves visibility, and makes the research process transparent. This increases trust in the work, and allows for independent reproduction of results. However, a large proportion of data from published research is often only available to the original authors. Despite the obvious benefits of sharing data, and scientists' advocating for the importance of sharing data, most advice on sharing data discusses its broader benefits, rather than the practical considerations of sharing. This paper provides practical, actionable advice on how to actually share data alongside research. The key message is sharing data falls on a continuum, and entering it should come with minimal barriers.