A Principled Bayesian Workflow for Structural Model Updating: Review and Demonstration — review corpus dataset

This dataset is the analytical corpus underlying the systematic literature review in "A Principled Bayesian Workflow for Structural Model Updating: Review and Demonstration" (Shaker and Caprani). It contains 207 peer-reviewed journal articles that apply Bayesian inference to finite element model updating (FEMU) of structural systems, together with their extracted, per-paper methodological classifications. The corpus was assembled following a PRISMA-style identification, screening, and inclusion workflow. Scopus and Web of Science were queried on 2026-05-12 over the range 1900–2024, returning 1,325 records (785 Scopus, 540 Web of Science). After de-duplication (847 unique records), title/abstract screening (410 included), a peer-reviewed-journal quality filter (246), full-text retrieval (235), and full-text eligibility assessment, a final analytical corpus of 207 papers was reached. The single file bayesian_femu_corpus_207.csv (207 rows × 27 columns) provides, for each paper: identifiers (key, DOI, title, year); the headline classifications used in the review (updated/uncertain parameters, prior distribution family, data type, sampling method); finer codings (objects updated, prior per object, prior-bound style, error-model treatment, hierarchical structure); and the workflow safeguards reported (prior and posterior predictive checks, convergence diagnostics, multiple chains, prior-sensitivity analysis, identifiability analysis, model comparison, software, reproducible code); plus the inclusion decision and reason. These columns reproduce the statistics, tables, and Sankey diagram reported in the paper. Bibliographic database abstracts and vendor records are not redistributed; papers are identified by DOI. Search/analysis pipeline code is not included in this deposit.