2018 ESIP Summer Meeting

Reproducible science is critical to both researchers and society. Exposing the provenance of research products enables researchers to fully understand computational workflows that led to a result, and is key for computational reproducibility that builds trust in science. Provenance information includes metadata about the structure of scientific workflows, input data and parameters, output data and products like figures and graphs, and software that was executed in the workflow. With provenance, researchers can understand an analysis, guide interpretation of scientific results, propose alternative analysis, and re-execute workflows. Recording all of this in practical systems that are easy to use and available to the research community remains a challenge. During this workshop we will highlight existing and emerging solutions to provenance tracking and explore advances and best practice representing, capturing, and using provenance. Demonstrations of tools and methods supporting provenance capture, editing, and use of provenance for reproducible science will be highlighted.