Heritage Science generates vast quantities of heterogeneous data; however, the absence of a shared semantic framework frequently results in fragmented knowledge and compromised reproducibility. This paper introduces CRMhs, an ontology developed as a formal extension of the CIDOC Conceptual Reference Model (CRM), designed to harmonise the documentation of scientific investigations within the cultural heritage domain. By defining specialised classes for scientific activities, study objects and analytical datasets, the model ensures a robust chain of provenance from initial physical sampling to final interpretative outcomes. The efficacy of CRMhs is evidenced in this paper through two archaeological case studies, illustrating how CRMhs enables the integration of diverse analytical data into a coherent and navigable knowledge graph. Broader applications, including the integration of environmental data and its use within Reactive Heritage Digital Twin frameworks, are outlined as ongoing developments. In this way, the model facilitates seamless data interoperability, and it bridges scientific evidence, art-historical and archaeological interpretation, supporting a more integrated approach to the preservation and understanding of cultural heritage.
Bridging “Nature” and “Spirit”: The CRMhs Ontology for the Integration of Heritage Science and Cultural Heritage Data / Felicetti, Achille; Murano, Francesca. - In: HERITAGE. - ISSN 2571-9408. - ELETTRONICO. - 9:(2026), pp. 186.1-186.22. [10.3390/heritage9050186]
Bridging “Nature” and “Spirit”: The CRMhs Ontology for the Integration of Heritage Science and Cultural Heritage Data
Murano, Francesca
2026
Abstract
Heritage Science generates vast quantities of heterogeneous data; however, the absence of a shared semantic framework frequently results in fragmented knowledge and compromised reproducibility. This paper introduces CRMhs, an ontology developed as a formal extension of the CIDOC Conceptual Reference Model (CRM), designed to harmonise the documentation of scientific investigations within the cultural heritage domain. By defining specialised classes for scientific activities, study objects and analytical datasets, the model ensures a robust chain of provenance from initial physical sampling to final interpretative outcomes. The efficacy of CRMhs is evidenced in this paper through two archaeological case studies, illustrating how CRMhs enables the integration of diverse analytical data into a coherent and navigable knowledge graph. Broader applications, including the integration of environmental data and its use within Reactive Heritage Digital Twin frameworks, are outlined as ongoing developments. In this way, the model facilitates seamless data interoperability, and it bridges scientific evidence, art-historical and archaeological interpretation, supporting a more integrated approach to the preservation and understanding of cultural heritage.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



