Implementing Reproducible Fisheries Research: A Decade of Experience With the Kahawai Reporting System

Area of Science:

• Scientific publishing
• Research methodology
• Data analysis

Background:

• Scientific publishing is perceived to be in crisis, partly due to low reproducibility rates.
• Insufficient methodological details in studies complicate the assessment of result reliability.
• Low reproducibility challenges the trustworthiness of scientific publications.

Purpose of the Study:

• To present a framework for achieving fully reproducible analyses of fisheries data.
• To demonstrate the transferability of this framework to other scientific disciplines.
• To advocate for the adoption of reproducible analyses to address the scientific publishing crisis.

Main Methods:

• Utilizing a framework where analyses are fully defined in code.
• Running analyses within a consistent computing environment.
• Applying the framework to fisheries data analysis over a decade.

Main Results:

• The framework enables full reproduction of analysis results.
• The approach has been successfully adopted in various disciplines beyond fisheries.
• The benefits of openness, transparency, and efficiency outweigh the initial overhead.

Conclusions:

• Fully reproducible analyses are crucial for re-establishing trust in scientific publications.
• Adopting reproducible methods strengthens peer review and helps identify questionable research practices.
• The framework offers a viable solution to the "reproducibility crisis" in science.