Session

DescriptionIn this minisymposium, we discuss state-of-the-art solutions and ongoing developments to embed FAIR data principles into HPC research workflows. Indeed, despite the growing awareness of the importance of FAIR data principles, implementing them remains a challenge. This is especially true for HPC-powered research, due to the sheer amount of simulations, the lack of tools to simplify their management, and the rapidly evolving landscape of computational frameworks. The minisymposium focuses on best practices for reproducible workflows via modern state-of-the-art tools and approaches, concerning both workflow engines and the underlying simulation software running on current HPC architectures. We discuss applications from climate research and materials science, two domains with similar requirements in terms of workflows, access to HPC resources, and related data management needs. Nevertheless, these two domains have had until now limited interaction and cross-fertilization. Invited speakers are both developers and advanced users of widely adopted open-source workflow engines with a clear focus on reproducibility. They will showcase current efforts and future directions for addressing challenges on how the workflow engines can be expanded to facilitate adherence to FAIR requirements, by still keeping the user interface (for workflow developers and users) as simple as possible.