Natural heritage digitization has evolved beyond simple 3D representation. Contemporary approaches require transparent documentation integrating biological, heritage, and digitization standards, yet existing frameworks operate in isolated domains without semantic interoperability. Current digitization frameworks fail to integrate biological standards (Darwin Core, ABCD), heritage standards (CIDOC-CRM), and digitization standards (CRMdig, PROV-O) into a unified semantic architecture, limiting transparent documentation of natural heritage data across its entire lifecycle—from physical observation through digital reconstruction to knowledge reasoning. This study proposes an integrated semantic framework comprising three components: (1) the E-DNH ontology, which adopts a triple-layer architecture (data–metadata–paradata) and a triple-module structure (nature–heritage–digital), bridging Darwin Core, CIDOC-CRM, CRMdig, and PROV-O; (2) the HR3D workflow, which establishes a standardized high-precision 3D data acquisition protocol that systematically documents paradata; and (3) the C-EDNH platform, which implements a Neo4j-based knowledge graph with semantic search capabilities, AI-driven quality assessment, and persistent identifiers (NSId/DOI). The framework was validated through digitization of 197 natural heritage specimens (68.5% avian, 24.9% insects, 5.1% mammals, 1.5% reptiles), demonstrating high geometric accuracy (RMS 0.18 ± 0.09 mm), visual fidelity (SSIM 0.92 ± 0.03), and color accuracy (ΔE00 2.1 ± 0.7). The resulting knowledge graph comprises 15,000+ nodes and 45,000+ semantic relationships, enabling cross-domain federated queries and reasoning. Unlike conventional approaches that treat digitization as mere data preservation, this framework positions digitization as an interpretive reconstruction process. By systematically documenting paradata, it establishes a foundation for knowledge discovery, reproducibility, and critical reassessment of digital natural heritage.
Songie Seol (Thu,) studied this question.