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.