ENCORE: a practical implementation to improve reproducibility and transparency of computational research

Reproducibility of computational research is often challenging despite established guidelines and best practices. Translating these guidelines into practical applications remains difficult. Here, we present ENCORE, an approach to enhance transparency and reproducibility by guiding researchers in how to structure and document a computational project. ENCORE builds on previous efforts in computational reproducibility and integrates all project components into a standardized file system structure. It utilizes pre-defined files as documentation templates, leverages GitHub for software versioning, and includes an HTML-based navigator. ENCORE is designed to be agnostic to the type of computational project, data, programming language, and ICT infrastructure, and does not rely on specific software tools. We also share our group’s experience using ENCORE, highlighting that the most significant challenge to the routine adoption of approaches like ours is the lack of incentives to motivate researchers to dedicate sufficient time and effort to ensure reproducibility.

Antoine H. C. van Kampen, Utkarsh Mahamune, Aldo Jongejan, Barbera D. C. van Schaik, Daria Balashova, Danial Lashgari, Mia Pras-Raves, Eric J. M. Wever, Adrie D. Dane, Rodrigo García-Valiente, Perry D. Moerland