MHKG: An Ontology-Guided, Evidence-Linked Knowledge Graph for Metal Exposure and Health

Preventing metal exposure and related diseases is an important public health issue. However, related research involves various types of information and the relevant evidence is scattered across a large number of documents. The same concepts often appear in abbreviated forms, aliases, or different granular terms, which limits cross-study retrieval and evidence integration. We bulid a Metal-Health Knowledge Graph (MHKG) dataset, which organizes the literature extraction results into a queryable and auditable structured resource. MHKG links exposure factors with biological responses, health outcomes, and intervention measures, and the relationships retain links to the original articles and supporting paragraphs. We construct the dataset using a unified schema to organize heterogeneous entities and relationships. Meanwhile, cross-document entity standardization and evidence verification make the graph more coherent and the content more accessible for auditing. MHKG provides a structured and auditable resource for studying occupational metal exposure, supporting evidence-oriented retrieval, knowledge exploration, as well as future knowledge-enhanced applications.