Digital twins in engineering and STEM higher education: bibliometric review dataset (n = 126)

Corpus, analytical outputs, networks, figures and reproducibility artifacts underlying the bibliometric and inductive thematic review of digital twins in engineering and STEM higher education, prepared for submission to the International Journal of Educational Technology in Higher Education (IJETHE). The corpus comprises 126 articles retrieved from Scopus, Web of Science, IEEE, EBSCO and Dimensions (2018–2026) and reduced through a PRISMA-style two-stage screening (1,504 → 126). Included: the six independent LLM thematic runs and the deterministic consensus output; the co-citation, bibliographic-coupling and keyword co-occurrence networks; the Research Dynamics Manifold tables; the field-normalized impact indicators (FWCI, Leiden MNCS, Beauty Coefficient, CSS, Outgrow Index); the enhanced RPYS and concept-lifecycle outputs; and the structural gap map. See README.md for structure and MANIFEST.md for the file-by-file provenance.