Connecting Data Science and Project Governance: How Automated Risk Analytics Reshape Mitigation in Digital Projects

This record contains the research data and analysis code accompanying the study “Connecting Data Science and Project Governance: How Automated Risk Analytics Reshape Mitigation in Digital Projects.” The study examines how automated vulnerability signals move from actionable exposure identification through governed organisational response to verified and durable mitigation in public open-source repositories. The release includes pseudonymised derived repository- and episode-level records, activation and linkage audit decisions, data dictionaries, exclusion records, privacy-preserving lineage receipts, machine-readable results, vector figures, and Python-based reproduction and testing scripts. The analysis covers 960 public repositories and 11,520 repository–vulnerability candidates, with 9,911 actionable episodes retained within common support. The code environment is specified in analysis_code/environment.lock. No private communications, authentication credentials, demographic attributes, or person-level performance rankings are included. The files are intended to support research reproduction, audit, and methodological reuse.