Training, Education and Outreach

The long term sustainability of the research software ecosystem is particularly important for HEP, given that the HL-LHC and other facilities of the 2020s will be relevant through at least the 2030s. The IRIS-HEP Software Sustainability Core (SSC) focuses on activities which promote the long term sustainability of the software. In the initial phase of the Institute, the SSC focuses primarily on Training, Education and Outreach. The dissemination of best practices for software to the HEP community, as well as engagement with the wider scientific, cyberinfrastructure and data science communities is also an integral part of our activities. After the initial phase of the Institute, the SSC activities will also include collaborative efforts within the HEP community to enable transitions to more sustainable software solutions.

Training: Training is central to building the community skills needed to address the computing challenges of the HL-LHC era. One key insight is the need to think of training not as a set of individual, disconnected activities, but as part of a larger framework which provides a training path from a researcher’s first steps through active contribution.

IRIS-HEP is working to implement this vision in collaboration with the FIRST-HEP project, HEP experiments and others. IRIS-HEP team members help organize events, develop training material and participate as lecturers at all levels of this training vision. We organize and run the annual Computational and Data Science for High Energy Physics (CoDaS-HEP) summer school at Princeton and provide additional professional development for the most advanced students and postdocs by supporting connections with mentors through the IRIS-HEP Fellows Program.

Best Practices: The Institute will document, disseminate, and work towards community adoption of the best practices (from HEP and beyond) in the areas of software sustainability, including topics in software engineering, data/software preservation, and reproducibility. Of particular importance are best practices surrounding the modernization of the software development process for scientists.