Data-Driven Community Standards for Interdisciplinary Heterogeneous Information Networks
Year: 2025
Type: article
Abstract: Integrating diverse datasets into a unified, interoperable representation is a key challenge in interdisciplinary research. Heterogeneous information networks provide a graph-based framework for linking datasets while preserving their semantic structure. This work explores the use of ontologies to ensure semantic interoperability in cultural heritage knowledge graphs. Using the CIDOC Conceptual Reference Model (CIDOC-CRM) alongside other commonly used or domain-specific ontologies, this study develops a hybrid ontology for archaeo-natural research data (ArNO) based on the experience gained in NFDI4Objects Task Area 3. The integration follows Linked Open Data principles, ensuring schema-level consistency through ontology-based modelling and enforcing data-level consistency with terminologies. By establishing schema- and data-level standards, this work contributes to FAIR-compliant research infrastructures, enhancing data reuse across humanities and natural sciences. The approach is demonstrated through the integration of ancient DNA datasets from the Poseidon framework. This enables cross-dataset analysis by linking biological, archaeological, and contextual data. The study also addresses challenges in CIDOC-CRM-based modelling, e.g., its event-centric nature.
Language: English
Topic: Semantic Web and Ontologies
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6930884583
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