
This talk introduces the CodeRefinery project, its workshops, and its community, and explore how you can engage, contribute, and benefit from our resources as a researcher or Research Software Engineer. CodeRefinery is a community-driven, publicly funded project dedicated to improving research code by providing hands-on training and open learning materials for researchers across disciplines. Our workshops focus on practical tools and “good enough” research software engineering practices that are often missing from traditional academic education—such as version control, reproducible research, collaborative development, and efficient coding techniques fostering Open Science and FAIR software development. In addition to workshops and learning materials, CodeRefinery fosters a supportive and inclusive community where Research Software Engineers and enthusiasts can share knowledge, exchange experiences, and find opportunities for collaboration. This community-driven approach has enabled the joint organization of specialized workshops, such as high-performance computing (HPC) kick-off and “Tools and Techniques for HPC”, addressing a wide range of computational research needs. There are many ways to get involved with/support/ benefit from CodeRefinery: Join a workshop as a learner Bring your team and learn together Host a local classroom to follow the workshop with colleagues Teach with us—become a co-instructor Contribute to lesson materials Provide feedback to help us improve Use our materials for your own training events The presentation recording is available on the HiRSE YouTube Channel: https://www.youtube.com/@Helmholtz_Platform_for_RSE/videos?view=0&sort=dd&shelf_id=3https://www.youtube.com/watch?v=kY7aP3tgG6E Learn more about the HiRSE Seminar Series: https://www.helmholtz-hirse.de/series.html
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
