Session

DescriptionThe role of research software in scientific computing has grown tremendously over the last few decades. In addition to traditional research areas, data-intensive science has seen a rapid rise in prominence. This has been accompanied by disrupting changes in computer architectures and increasing complexity in the system software stack. At the same time, software development teams are growing in size and disciplinary diversity. While we focus on the scientific discoveries enabled by modern computational and data science, we also understand that the science is only as credible as the software that underlies it. The changing hardware environment, growing demand for solutions from modeling, simulation, and data analytics, growing emphasis on transparency and reproducibility, as well as the social challenges of larger/diverse teams needing to collaborate effectively, poses serious challenges for the scientific computing community. This minisymposium will explore the current state and future prospects for sustainability of software and data, spanning multiple scientific areas, and computational and human scales -- from individuals and small teams to broader communities. We hope to bring a variety of experience and perspectives to understand the challenges being faced and to explore insights that can be spread to other areas of computational and data science.