Artifact of the paper "What Do Users Discuss in nf-core Modules? Insights from GitHub Issues and Pull Requests"

The study analyzes 8,115 GitHub issues and pull requests to investigate practitioner challenges, repository maintenance practices, and factors associated with artifact resolution in modular scientific workflow infrastructure. The package contains raw datasets collected from the GitHub REST API, processed datasets used for analysis, and Jupyter notebooks implementing the data collection, preprocessing, and statistical analysis pipeline. These scripts allow researchers to reproduce the steps used to construct the dataset, identify linked pull requests, and perform the analyses corresponding to the research questions reported in the paper. The Dataset folder contains the data collected from the GitHub REST API for the nf-core/modules repository, including issues, pull requests, and metadata related to their resolution. It also includes filtered and processed datasets that were used in the analysis after removing redundant artifacts, such as pull requests explicitly linked to issues. These processed datasets form the final dataset used to conduct the empirical analyses reported in the paper. The Scripts folder contains Jupyter notebooks implementing the data collection, preprocessing, and analysis pipeline. These notebooks reproduce the steps used to retrieve data from GitHub, detect linked pull requests, prepare the final dataset, and perform the analyses corresponding to the research questions. Together, the provided datasets and scripts enable researchers to reproduce the results reported in the paper and support further research on collaboration, governance, and maintenance in modular scientific workflow ecosystems. The Results folder contains the categorization outcomes.本研究共分析了8115个GitHub议题（GitHub issues）与拉取请求（pull requests），旨在探究模块化科学工作流基础设施中的从业者实践挑战、仓库维护规范，以及与工件（artifact）解析相关的影响因素。 本数据集包包含从GitHub REST API（GitHub REST应用程序编程接口）采集的原始数据集、用于分析的预处理后数据集，以及实现数据采集、预处理与统计分析流程的Jupyter笔记本（Jupyter notebooks）。本配套脚本可支持研究人员复现数据集构建、关联拉取请求识别，以及针对论文中研究问题开展分析的全部步骤。 数据集文件夹包含从GitHub REST API采集的针对nf-core/modules仓库的相关数据，涵盖议题、拉取请求及其解析相关的元数据。该文件夹同时包含经筛选与预处理后的分析用数据集，已剔除冗余工件——例如显式关联议题的拉取请求。上述预处理后数据集即为支撑论文中实证分析的最终数据集。 脚本文件夹包含实现数据采集、预处理与分析流程的Jupyter笔记本。本配套笔记本可复现从GitHub获取数据、识别关联拉取请求、构建最终数据集，以及针对研究问题开展分析的全部步骤。综上，本次提供的数据集与脚本可支持研究人员复现论文中报告的研究结果，同时为模块化科学工作流生态系统中的协作、治理与维护相关的后续研究提供支撑。 结果文件夹包含分类结果。