Scientific workflows have become integral tools in broad scientific computing use cases.
Science discovery is increasingly dependent on workflows to orchestrate large and complex …

Research process automation–the reliable, efficient, and reproducible execution of linked
sets of actions on scientific instruments, computers, data stores, and other resources–has …

The Workflows Community Summit gathered 111 participants from 18 countries to discuss
emerging trends and challenges in scientific workflows, focusing on six key areas: time …

We address the increasing complexity of scientific workflows in the context of high-
performance computing (HPC) and their associated need for robust, adaptable, and flexible …

Modern large-scale scientific discovery requires multidisciplinary collaboration across
diverse computing facilities, including High Performance Computing (HPC) machines and …

The Julia programming language has evolved into a modern alternative to fill existing gaps
in scientific computing and data science applications. Julia leverages a unified and …

We observe the emergence of a new generation of scientific workflows that process data
produced at a sustained rate by scientific instruments and large scale numerical simulations …

X‐ray scattering experiments using free electron lasers (XFELs) are a powerful tool to
determine the molecular structure and function of unknown samples (such as COVID‐19 …

The Superfacility model is designed to leverage HPC for experimental science. It is more
than simply a model of connected experiment, network, and HPC facilities; it encompasses …

Abstract The Dagstuhl Seminar 23352, titled" Integrating HPC, AI, and Workflows for
Scientific Data Analysis," held from August 27 to September 1, 2023, was a significant event …