Representing and Validating Cultural Heritage Knowledge Graphs in CIDOC-CRM Ontology

Abstract

In order to unify access to multiple heterogeneous sources of cultural heritage data, many datasets were mapped to the CIDOC-CRM ontology. CIDOC-CRM provides a formal structure and definitions for most cultural heritage concepts and their relationships. The COURAGE project includes historic data concerning people, organizations, cultural heritage collections, and collection items covering the period between 1950 and 1990. Therefore, CIDOC-CRM seemed the optimal choice for describing COURAGE entities, improving knowledge sharing, and facilitating the COURAGE dataset unification with other datasets. This paper introduces the results of translating the COURAGE dataset to CIDOC-CRM semantically. This mapping was implemented automatically according to predefined mapping rules. Several SPARQL queries were applied to validate the migration process manually. In addition, multiple SHACL shapes were conducted to validate the data and mapping models.

CIDOC-CRM and Machine Learning: A Survey and Future Research

“…For instance, [24] performs entity matching for finding existing person instances between the different datasets, which are described by using the CIDOC-CRM model, while [13] supports both automated (rule-based) and manual instance matching processes as well as manual vocabulary curation before data are transformed based on CIDOC-CRM. The authors of [25] evaluate the quality of mappings between COURAGE and CIDOC-CRM ontologies by using mainly SPARQL queries and reasoners. The author of [26] describes a process for relating paintings with events.…”