Maintenance and Support in Community-Driven Scientific Pipeline Ecosystems: A Cross-Platform Empirical Study of nf-core

2026-07-12

AI Summary

Community-driven scientific workflow ecosystems often struggle to sustain themselves due to ambiguous maintenance and user support mechanisms, particularly in cross-platform collaboration and heterogeneous execution environments. This study presents the first cross-platform empirical analysis of the nf-core ecosystem, systematically examining 15,760 GitHub issues, 35,411 pull requests, and 895 forum discussions. By integrating metadata and textual features into predictive models, the research uncovers significant disparities in maintenance and support activities across platforms and highlights weak explicit linkages among them. The findings reveal that issues, pull requests, and forum posts predominantly serve distinct roles—coordinating maintenance, facilitating code integration, and providing user support, respectively. Moreover, issue actionability, diagnostic evidence, and depth of interaction emerge as critical determinants of resolution efficiency.

Abstract

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.

Problem

• community-driven
• scientific pipeline
• maintenance
• user support
• heterogeneous execution environments

Innovation

• community-driven pipelines
• cross-platform empirical study
• maintenance and support
• nf-core
• scientific workflow ecosystems