TADA! Simple guidelines to improve code sharing

Code sharing is important for transparency and facilitates computational reproducibility of published research. However, even as the number of journals that encourage or mandate code sharing continues to increase, the prevalence of open code remains low. Furthermore, even when shared, code is often non-functional, which hinders computational reproducibility. One reason for low levels of code sharing is uncertainty around how to prepare functional (i.e., the ability to run code without error) and reproducible (i.e., the ability to reproduce the analysis and results using the same data, code, and computational conditions) code as existing principles for best coding practices are both complex and primarily developed for software. To improve code sharing, there is an urgent need for clear and simple guidance on how to prepare functional and reproducible code for sharing. To address this, we provide simple code sharing guidelines: TADA (Transferable, Accessible, Documented and Annotated). TADA details the minimum requirements necessary for a researcher to produce functional and reproducible code for sharing that directly supports open science best practices and the FAIR (Findable, Accessible, Interoperable, Reusable) principles for code. TADA aims to streamline the process of depositing and sharing functional code for researchers with all levels of coding experience, with the ultimate goal of increasing the transparency, reproducibility, and reliability of research results across ecology and evolution, and more broadly.