Cervical Cancer Dataset Catalog (CCDCAT-U_v1.0; Release v0.1): A Machine-Readable, Reproducible Catalog of Discoverable Human Cervical Cancer and Pre-Cancer Datasets Across Modalities

Human cervical cancer and pre-cancer research relies on datasets scattered across modality-specific archives, imaging repositories, benchmark platforms, trial registries, and controlled-access catalogs. This fragmentation—combined with heterogeneous metadata, ambiguous use of “cervical” terminology, and inconsistent indexing of pre-cancer and screening/triage resources—limits reproducible discovery, access planning, and cross-modal benchmarking. We present the Cervical Cancer Dataset Catalog (CCDCAT), a machine-readable, versioned dataset of datasets that enumerates host-specific dataset-instance records anchored to stable identifiers and resolvable landing records within an explicitly declared discoverable source universe (U_v1.0) and a frozen discovery/labeling lexicon (Q_v1.0). The CCDCAT spans invasive cervical cancer, pre-cancer/dysplasia, and cervix-focused screening and triage phenotypes, and it covers molecular omics, imaging and microscopy (including cervix photography, cytology, and digital pathology), trial registry records, benchmark resources, and controlled-access catalogs represented as metadata with explicit access pathways. Eligibility and labels are assigned conservatively from source-provided metadata; when evidence is insufficient, the CCDCAT abstains rather than infers. In the initial release (CCDCAT-U_v1.0; v0.1), we enumerate 14 eligible dataset instances across 11 host systems within a declared universe of 21 sources. Releases include manuscript-ready tables and interoperable artifacts (schema, controlled vocabularies, provenance logs, abstention ledgers, and a queryable database), enabling reproducible filtering, linkage, and auditable reuse planning.