Reproducible eScience: The Data Containerization Challenge

Computational reproducibility is the cornerstone of the scientific method. We are witnessing a surge of reproducible practices emerging in scientific disciplines. Use of containers is a common theme across several of these practices. Containers isolate applications and make it simple to share code, data, and experiment settings. This paper presents current eScience infrastructures that use containers for reproducible research. We then present our view of the important research issues in data containerization for reproducible eScience. Containerization requires considering packaging, sharing, security, and language choices to ensure reproducibility and preservation. Despite its benefits, containerization can be inefficient and impact experiment reproducibility when users stop using it or transition the experiment to different environments. We describe reproducible containers that in addition to containerization include services to ensure and maintain long-term reproducibility and lay forward a vision based on reproducible containers.