PubMed 2026 MeSH-Incidence Corpus: a sparse-binary dataset (30 M articles × 30 k descriptors) for self-organizing-map and clustering benchmarks

A MeSH-descriptor incidence matrix derived from the PubMed 2026 annual baseline. Each row is one indexed article and each column is one Medical Subject Headings (MeSH) descriptor; an entry marks that the article was indexed with that descriptor. The result is a large, genuinely sparse binary matrix (~11 descriptors per article) intended for benchmarking self-organizing maps, clustering, and sparse-matrix kernels at scale. Scale. 29,903,261 articles × 30,766 MeSH descriptors, 332,436,043 non-zeros (mean 11.1 descriptors/article), after dropping articles with fewer than 5 descriptors. Provided pre-split for held-out evaluation: a deterministic 98% / 2% train/test partition (random seed 0) — train 29,304,386 articles, test 598,875. Contents. - corpus.train.sbcsr, corpus.test.sbcsr — the incidence matrices (CSR binary; see format below) - vocab.json — the column→MeSH map: an ordered list of MeSH descriptor UI codes (e.g. "D000123") - summary.json — provenance: counts, the ≥5-descriptor filter, source filenames, timestamps - README.md — this record, the format spec, and regeneration instructions What it deliberately does not contain. No abstracts, no titles, no author or journal data, and no PMIDs — rows are anonymous and cannot be traced back to individual articles. Only NLM's controlled-vocabulary descriptor codes are stored (not even the descriptor strings). The bundle is therefore composed solely of public-domain, U.S.-government-produced content. Format (.sbcsr, little-endian). A 24-byte header — magic "SBCSR1\0\0", then uint32 n_samples, n_features, n_nonzeros, reserved — followed by uint32 row_ptr[n_samples+1] and uint16 col_idx[n_nonzeros]. Column id c maps to MeSH UI vocab.json[c]. License. Released CC0 1.0 (public-domain dedication) on these derived structures. Attribution (required). Courtesy of the U.S. National Library of Medicine. This product uses publicly available data from NLM but is not endorsed or certified by NLM. Currency. This is a static snapshot of the PubMed 2026 annual baseline and does not reflect the most current or accurate data available from NLM. For live data, ingest directly from https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/. Integrity. medline-mesh-pubmed26-ge5.tar.gz — SHA-256 dc79fc5f81c80e3d99b30f41c179cc7f90d5e7be4f2e9cf20c9d0ba756da0bfd.