Reproducible Research Workflows: Key Points

Introduction

Reproducibility usually means obtaining the same results with the same data.
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.
Recent studies point to many issues with reproducibility across different disciplines, something that has been termed “reproducibility crisis”

Making research more reproducible contributes to general research improvement, quality and rigor but also to higher efficiency and easier error correction for researchers
This does not come without specific challenges, such as time constraints, technical issues and the need of specific skills for making research outputs reproducible
To overcome the challenges, researchers are in need of proper tools, solutions, research support staff, infrastructure and training

Research workflows are sequences of processes that researchers have to go through to get to specific research outputs
Data acquisition, data analysis and manuscript writing are three phases of the research process that can be made more reproducible
There are many tools out there that can help make research workflows more reproducible

Academic libraries are uniquely positioned to provide help and support in the area of open and reproducible research
Academic librarians can build on their expertise in making research outputs shareable and reusable to also help make them reproducible
Academic libraries can offer training in reproducible research workflows in addition to open science trainings