Evidence-Aware Software–Data Compatibility in Administrative Disaster Analytics: A Reproducible OpenFEMA Case Study

Administrative disaster data may be technically usable even when available fields do not support every substantive interpretation associated with a workflow. We present an evidence-aware software–data compatibility framework using an archived OpenFEMA Disaster Declarations Summaries snapshot and the R package DisasterAlert 1.0.0. The archive comprises 5074 declaration-area records, 356 FEMA declaration numbers, and 54 observed jurisdictions. Analytical-unit choice changes geographic summaries: declaration-area rankings have only moderate agreement with declaration-number counts (Spearman ρ=0.528), and Gini concentration falls from 0.653 to 0.432. Declaration-type stratification explains this pooled result: rank agreement is 0.751 for major-disaster, 0.962 for emergency, and 0.989 for fire-management declarations; median rows per declaration number are 8, 47, and 1, respectively. Complete-month and 2024–2025 calendar checks show that the principal rankings are not boundary-month artifacts. Nine exported functions are mapped to documented input and evidence requirements through an audit of argument compatibility, source-field availability, upstream prerequisites, and construct support. Spatial outputs are restricted to jurisdiction-level administrative summaries, with clustered-bootstrap uncertainty reported for compositional entropy. This single, developer-affiliated data–software demonstration does not externally validate general applicability; independent evaluation across other packages and datasets is required.