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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Câmara, A., Almeida, A. de. & Oliveira, J. (2024). Transforming the CIDOC-CRM model into a megalithic monument property graph. Journal of Computer Applications in Archaeology. 7 (1), 213-224
Exportar Referência (IEEE) 
A. Câmara et al.,  "Transforming the CIDOC-CRM model into a megalithic monument property graph", in Journal of Computer Applications in Archaeology, vol. 7, no. 1, pp. 213-224, 2024
Exportar BibTeX 
@article{câmara2024_1730780197702,
	author = "Câmara, A. and Almeida, A. de. and Oliveira, J.",
	title = "Transforming the CIDOC-CRM model into a megalithic monument property graph",
	journal = "Journal of Computer Applications in Archaeology",
	year = "2024",
	volume = "7",
	number = "1",
	doi = "10.5334/jcaa.151",
	pages = "213-224",
	url = "https://journal.caa-international.org/"
}
Exportar RIS 
TY  - JOUR
TI  - Transforming the CIDOC-CRM model into a megalithic monument property graph
T2  - Journal of Computer Applications in Archaeology
VL  - 7
IS  - 1
AU  - Câmara, A.
AU  - Almeida, A. de.
AU  - Oliveira, J.
PY  - 2024
SP  - 213-224
SN  - 2514-8362
DO  - 10.5334/jcaa.151
UR  - https://journal.caa-international.org/
AB  - This paper presents a method to store information about megalithic monument-building components as graph nodes in a knowledge graph (KG). As a case study, we analyse the dolmens from the region of Pavia (Portugal). To build the KG, information has been extracted from unstructured data to populate a schema model based on the International Committee for Documentation – Conceptual Reference Model (CIDOC-CRM). In order to prepare the archaeological monument’s information for bulk loading, it was transformed into semi-structured data. While the semi-structured file was used to populate the classes with their respective properties and instances, the KG labels and types were defined using some of the entities and relations defined by the CIDOC-CRM. The knowledge-driven model was built to represent dolmens in a formal and structured manner using Neo4j, a property-graph database. Modelling a labelled property graph based on predefined labels as a KG enables to transform textual semantic data into instances and properties. Thus, we show that it is possible to represent at a granular level all the information about the structural components of monuments since heterogeneities, granularities, and large amounts of data can be handled by a KG. Therefore, a KG implemented using a native graph database can improve data storage and processing, making it interoperable between humans, humans and machines and machine to machine.
ER  -