The Pegasus Workflow Management System maps abstract, resource-independent workflow
descriptions onto distributed computing resources. As a result of this planning process …

It is commonly agreed that in silico scientific experiments should be executable and
repeatable processes. Most of the current approaches for computational experiment …

In the past decades, one of the most common forms of addressing reproducibility in scientific
workflow-based computational science has consisted of tracking the provenance of the …

We present an end-to-end solution for automation of scientific workflow deployment and
execution on distributed computing infrastructures. The solution integrates de-facto standard …

We present Asterism, an open source data-intensive framework, which combines the
strengths of traditional workflow management systems with new parallel stream-based …

Cloud computing has become a major approach to help reproduce computational
experiments. Yet there are still two main difficulties in reproducing batch based Big Data …

We propose a comprehensive solution for reproducibility of scientific workflows. We focus
particularly on Kubernetes-managed container clouds, increasingly important in scientific …

Reproducible research in scientific workflows is often addressed by tracking the provenance
of the produced results. While this approach allows inspecting intermediate and final results …

The emergence of Cloud computing provides a new computing paradigm for scientific
workflow execution. It provides dynamic, on-demand and scalable resources that enable the …

Reproducibility is a crucial requirement in scientific research. When results of research
studies and scientific papers have been found difficult or impossible to reproduce, we face a …