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Câmara, A., Almeida, A. de. & Oliveira, J. (2024). Transforming the CIDOC-CRM model into a megalithic monument property graph. In Waagen, J., Verhagen, P., Hacigüzeller, P., Visser, R., Taelman, D., and Brandsen, A. (Ed.), CAA2023 Conference Proceedings. Amsterdam

A. Câmara et al.,  "Transforming the CIDOC-CRM model into a megalithic monument property graph", in CAA2023 Conf. Proc., Waagen, J., Verhagen, P., Hacigüzeller, P., Visser, R., Taelman, D., and Brandsen, A., Ed., Amsterdam, 2024

@inproceedings{câmara2024_1730780455895,
	author = "Câmara, A. and Almeida, A. de. and Oliveira, J.",
	title = "Transforming the CIDOC-CRM model into a megalithic monument property graph",
	booktitle = "CAA2023 Conference Proceedings",
	year = "2024",
	editor = "Waagen, J., Verhagen, P., Hacigüzeller, P., Visser, R., Taelman, D., and Brandsen, A.",
	volume = "",
	number = "",
	series = "",
	doi = "10.5281/zenodo.7981230",
	publisher = "",
	address = "Amsterdam",
	organization = "",
	url = "https://2023.caaconference.org/proceedings/"
}

TY  - CPAPER
TI  - Transforming the CIDOC-CRM model into a megalithic monument property graph
T2  - CAA2023 Conference Proceedings
AU  - Câmara, A.
AU  - Almeida, A. de.
AU  - Oliveira, J.
PY  - 2024
DO  - 10.5281/zenodo.7981230
CY  - Amsterdam
UR  - https://2023.caaconference.org/proceedings/
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. Modeling a labeled
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,
between humans and machines and machine to machine.
ER  -