Documentation

Introduction

Scientists in many disciplines are working with large and complex datasets that are challenging to store, manage, analyse, preserve, and share. Furthermore, corresponding analytical workflows for the interpretation of data and generation of publishable results are also increasing in complexity. As a result, the reusability of data and (computational) reproducibility of results becomes a major challenge, if the full analytical pathway from data to the final result is not documented in detail and or only partially available. This includes not only the analysis code but also information on the computational environment in which analyses are executed, because a single missing library or an updated package can break a published workflow in the future.

The Reproducible Research Platform (RRP) has been developed to address this challenge. RRP builds on established open-source tools and aims for a seamless and user-friendly connection between the data and metadata management (with openBIS) and tools for code management (Git), management of computational environments (repo2docker) and interactive computational notebooks (Jupyterlab). Furthermore, researchers from a research group can use RRP to easily share computational projects with each other, for example, to build upon previous work or share it between student and supervisor. In summary, the RRP platform enables researchers to achieve full reproducibility of their computational work with minimal additional effort.

RRP Documentation

The RRP documentation is organized in the following sections: