Problem
Research questions and friction points this paper is trying to address.
maintenance
community-driven
ecosystem
traceability
support
Understanding Maintenance and Support in a Community-Driven Scientific Workflow Ecosystem: A Cross-Space Study of Galaxy
🤖 AI Summary
研究通过分析Galaxy的GitHub和社区论坛数据，使用BERTopic模型识别维护和支持主题，揭示了维护生态系统的分布特点，并提出改善诊断报告、生命周期意识分类及跨空间追溯性的建议。
📝 Abstract
Galaxy is a widely used, community-driven scientific workflow system whose sustainability depends on continuous maintenance across its software, tools, workflows, infrastructure, documentation, and user-support ecosystem. However, maintenance knowledge in Galaxy is distributed across development and community-support spaces, making it difficult to understand what is maintained, how maintenance artifacts are resolved, and how user-facing concerns connect to repository-level development. We conduct a large-scale empirical study of Galaxy using 11,762 GitHub issues, 52,203 pull requests, and 6,235 Community Forum discussions. We characterize maintenance and support concerns, examine factors associated with resolution outcomes and resolution time, and investigate explicit and candidate connections among maintenance artifacts across these spaces.
Using BERTopic modeling, we identify nine issue topics, 14 pull-request topics, and 14 forum topics, revealing a maintenance landscape spanning workflow execution, data management, tools and dependencies, infrastructure, testing, scientific resources, documentation, and user support. Resolution analyses show that coordination, diagnostic, contributor, automation, and engagement characteristics exhibit different associations with whether artifacts are resolved and how quickly resolution occurs. We further find limited explicit traceability between development and support spaces: 97.77\% of 16,426 resolved explicit relationships occur within GitHub, while only 294 connect GitHub artifacts with Community Forum discussions, despite additional semantic and technical relatedness across these spaces. Together, these findings characterize Galaxy maintenance as a distributed ecosystem-level process and identify opportunities to improve diagnostic reporting, lifecycle-aware triage, cross-space traceability, and the reuse of community-support knowledge.
Innovation
Methods, ideas, or system contributions that make the work stand out.
BERTopic modeling
cross-space traceability
maintenance landscape
resolution analysis
community-support knowledge
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