Experimental Research Reproducibility and Experiment Workflow Management

Abstract

Research reproducibility is an important factor to support the full research life cycle; this is especially important for experimental research, where it is required to also reproduce the whole experiment environment and equipment setup. This paper presents the methodology and solution proposed in the SLICES Research Infrastructure to enable research reproducibility in modern digital technologies for complex and large scale experimentation. The paper provides a short overview of existing research and approaches for experimental research reproducibility, generally including git based experiments deployment and operation, Jupyter Notebook and Common Workflow Language (CWL) for workflow management. The paper describes the framework and approaches taken in the SLICES-RI that also address research environment provisioning on demand with the Platform Research Infrastructure as a Service (PRIaaS) and data management infrastructure to ensure data quality and support effective data sharing.