Replication Data for: Uncertainty-Aware Learning in Agile Requirements Engineering

This replication package contains the anonymized operational dataset and supporting artifacts for the paper 'Uncertainty-Aware Learning in Agile Requirements Engineering: A VOUL-Guided Protocol for Requirements-Level Inspect-and-Adapt'. The dataset includes 110 unique product backlog items (PBIs) from three industrial teams, tracking variables such as BaselinePullIn, BelScore, PlScore, and sprint review decisions (GO/PIVOT/KILL). Also included are the Python scripts for data anonymization and ICC(2,k) reliability calculation, the data dictionary, Jira field mapping templates, and the integrated calibration rubric.