Background

Reproducibility of research requires that research data and code be made available so that others can reach the results published in scientific outputs. Improving reproducibility leads to increased rigour and quality of scientific outputs, and thus to greater trust in science. There has been a growing need and willingness to expose research workflows lifecycle from initiation of a project and data collection right through to the interpretation and reporting of results. These developments have come with their own sets of challenges, including designing integrated research workflows that can be adopted by collaborators while maintaining high standards of integrity.