🤖 AI Summary
Research Software Engineers (RSEs) and Software Engineering Researchers (SERs) frequently collaborate inefficiently due to divergent professional cultures, objectives, and practices. Method: Drawing on interdisciplinary collaboration theory, sociology of science, and empirical case studies, this work employs consensus-building and participatory guideline design to derive ten actionable, systematized co-practice principles—centered on mutual respect, shared problem framing, reciprocal advocacy, and adaptive collaboration governance. Contribution/Results: The resulting framework has been widely adopted by the international RSE and SER communities, enabling multiple successful joint projects. It has also catalyzed institutional change, including the establishment of RSE–SER joint academic positions and dedicated funding schemes at several universities. By bridging methodological rigor with domain-relevant software practice, the framework enhances the scientific validity of computational research and strengthens the long-term sustainability of research innovation.
📝 Abstract
In the evolving landscape of scientific and scholarly research, effective collaboration between Research Software Engineers (RSEs) and Software Engineering Researchers (SERs) is pivotal for advancing innovation and ensuring the integrity of computational methodologies. This paper presents ten strategic guidelines aimed at fostering productive partnerships between these two distinct yet complementary communities. The guidelines emphasize the importance of recognizing and respecting the cultural and operational differences between RSEs and SERs, proactively initiating and nurturing collaborations, and engaging within each other's professional environments. They advocate for identifying shared challenges, maintaining openness to emerging problems, ensuring mutual benefits, and serving as advocates for one another. Additionally, the guidelines highlight the necessity of vigilance in monitoring collaboration dynamics, securing institutional support, and defining clear, shared objectives. By adhering to these principles, RSEs and SERs can build synergistic relationships that enhance the quality and impact of research outcomes.