AI 中文总结
研究社区驱动的科学管道生态系统nf-core中的维护与支持，通过分析大量GitHub问题、拉取请求及论坛讨论来研究相关问题、解决因素等，发现不同平台作用不同，解决结果与多种因素有关，跨平台分析揭示了内部可追溯性及联系有限的情况。
AI 中文摘要
社区驱动的科学管道生态系统对可重复的数据密集型研究愈发重要，其可持续性不仅取决于工作流引擎、模板和测试基础设施，还取决于社区如何维护管道、整合贡献以及在异构执行环境中支持用户。本文对nf-core这一标准化Nextflow管道的大型生态系统进行了跨平台实证研究。分析了15760个GitHub问题、35411个GitHub拉取请求和895条Seqera社区论坛讨论，以研究维护和支持方面的问题、不同工件类型的差异、与解决结果相关的因素以及问题和解决方案在以存储库为中心和以社区为中心的空间之间的流动情况。发现问题主要用于存储库级问题报告和维护协调；拉取请求用于实现、审查、测试、依赖和模板更新工作；论坛讨论用于围绕执行失败、容器、云与HPC环境、MultiQC报告和Nextflow使用的用户支持。解决结果与可操作性、协调性和诊断证据相关。问题关闭与分配者、评论、里程碑、错误标签、错误提及和版本信息有关。拉取请求集成因作者角色、自动化类型、草稿状态、检查清单、链接问题和审查路由而异。当讨论包含代码块持续交互和具体技术证据时，论坛接受答案的可能性更大，而云、HPC和工作流语义问题更难解决。跨平台分析揭示了GitHub内强大的存储库内部可追溯性，但论坛讨论与存储库工件之间的明确联系有限。
英文摘要
Community-driven scientific pipeline ecosystems are increasingly important for reproducible data-intensive research, but their sustainability depends on more than workflow engines, templates, and testing infrastructure. It also depends on how communities maintain pipelines, integrate contributions, and support users across heterogeneous execution environments. This paper presents a cross-platform empirical study of maintenance and support in nf-core, a large ecosystem of standardized Nextflow pipelines. We analyze 15,760 GitHub issues, 35,411 GitHub pull requests, and 895 Seqera Community Forum discussions to examine what maintenance and support concerns arise, how they differ across artifact types, which factors are associated with resolution outcomes, and how problems and solutions flow between repository-centered and community-centered spaces. We find that issues primarily capture repository-level problem reporting and maintenance coordination; pull requests capture implementation, review, testing, dependency, and template-update work; and forum discussions capture user-facing support around execution failures, containers, cloud and HPC environments, MultiQC reporting, and Nextflow usage. Resolution outcomes are associated with actionability, coordination, and diagnostic evidence. Issue closure is linked to assignees, comments, milestones, bug labels, error mentions, and version information. Pull request integration varies by author role, automation type, draft status, checklists, linked issues, and review routing. Forum accepted answers are more likely when discussions include code blocks, sustained interaction, and concrete technical evidence, while cloud, HPC, and workflow-semantics questions are harder to resolve. Cross-platform analysis reveals strong repository-internal traceability within GitHub, but limited explicit linkage between forum discussions and repository artifacts.
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