Key Points

Introduction

Reproducibility is central to research integrity and helps others check, build on, and reuse research
Reproducibility and open science overlap but are not the same thing: openness helps enable reproducibility but does not guarantee it
This lesson moves from concepts (reproducibility vs. replicability) and openness, to benefits and challenges, to tools, to the library’s role in supporting all of it

Reproducibility usually means obtaining the same results with the same data and the same analysis steps.
Across different disciplines and methodologies, the understanding of what reproducibility means can be very different.

Reproducible research is not the same as open research - it is important to share research outputs to be able to reproduce others’ studies, but research can be made fully reproducible even if it cannot be made fully open.
Naming a project’s materials (a script, a data file, a source excerpt) is not the same as documenting the connection between them and a specific claim - that connection is what makes a result checkable.
Recent studies point to many issues with reproducibility across different disciplines, something that has been termed “reproducibility crisis” (optional background, not required for this lesson’s practical outcomes)

Reproducibility improves research quality and benefits both science and individual researchers
It can be difficult due to time, skills, legal, and technical challenges
Support services like training, infrastructure, and guidance are key to helping researchers succeed

Research workflows include data collection, analysis, and reporting; each stage offers opportunities to improve reproducibility
Match a tool to what you’re actually checking: can someone understand the materials, repeat the analysis steps, or trace the reported findings
Use documentation (README, codebook) to explain what your data and steps mean, and version control (Git) to inspect and recover changes to your code over time
A named artifact (a script, a data file) only closes a gap once it’s specifically connected to the claim it’s meant to support - identifying that missing connection is as important as knowing the tool that could fix it

Libraries are natural partners in supporting open and reproducible research, because much of the required support already exists as library services under other names
Library support for reproducibility ranges from familiar entry points (awareness, documentation) to more specialized, technical services (version control, environment comparisons) - which level a given library offers depends on staffing and expertise, not a fixed rule about what librarians do or don’t do
Reproducibility support builds on existing library expertise in research data and scholarly communication