POSE: Phase II: MNE-Python Maintainer Training and Automation

Research on human neuroscience helps unlock knowledge of how healthy brains function as well as enabling greater understanding of brain disease mechanisms. The MNE-Python project, a software tool for analyzing human neuroscience data, has a focus on preparing new maintainers to contribute to the project. The project supports MNE-Python's thousands of clinical, industrial, and scientific users. The project also creates user-facing educational materials, a key development to nurture the growth of the next generation of maintainers. These actions ensure that neuroscience researchers, clinicians, and engineers have ongoing, sustainable support for the software tools they rely on. This project, funded by the Pathways to Enable Open-Source Ecosystems (POSE) program, addresses a common challenge in developing open-source software: how to recruit and retain enough skilled volunteers to keep a project vibrant. This challenge is especially difficult given high volunteer turnover rates and a dynamic hardware and software landscape. MNE-Python seeks to grow the maintainer team and create resources to support future growth. Developers learn how to triage incoming submissions and support requests, optimize code, test the software, and develop solutions. The project also automates some of the more repetitive tasks included in the developer role, such as triaging issues and reviewing submissions, by automatically monitoring and responding to new issues and submissions. This award helps current and future maintainers become more efficient thus ensuring the long-term sustainability of MNE-Python. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.