Ontological Analysis and Modularization of CIDOC-CRM

Sanfilippo, Emilio M.; Markhoff, Béatrice; Pittet, Perrine

doi:10.3233/faia200664

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…Using CIDOC-CRM also improves semantic integration and interoperability, as it is a standard and many datasets and research tools are using that representation. It already has many necessary concepts for archival descriptions, such as people, collections, events, and others [9].…”

Section: Introductionmentioning

confidence: 99%

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

Faraj¹,

Micsik

2021

Future Internet

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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.

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Section: Introductionmentioning

confidence: 99%

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

Faraj¹,

Micsik

2021

Future Internet

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A Joint Entity-Relation Detection and Generalization Method Based on Syntax and Semantics for Chinese Intangible Cultural Heritage Texts

Tan,

Wang,

Zhao

et al. 2024

J. Comput. Cult. Herit.

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[Purpose/Significance] The annotation of natural language corpus not only facilitates researchers to extract knowledge from it, but also helps to achieve deeper mining of the corpus. But the annotated corpus in the humanities knowledge domain is less. And the semantic annotation of humanities texts is difficult, because it requires a high domain background for researchers, even requires the participation of domain experts. Based on this, this study proposes a method for detecting entities and relations in domain which is lack of annotated corpus, and provides a referenceable idea for constructing conceptual models based on textual instances. [Method/Process] Based on syntactic and semantic features, this study proposes SPO triple recognition rules from the perspective of giving priority to predicates and generalization rules from the perspective of triple's content and the meaning of its predicate. The recognition rules are used to extract text-descriptive SPO triples centered on predicates. After clustering and adjusting triples, use the generalization rules proposed in this study to obtain coarse-grained entities and relations, and then form a conceptual model. [Results/Conclusions] This study recognizes SPO triples with high precision and summarization from descriptive texts, generalizes them and then forms a domain conceptual model. The method proposed in this paper provides a research idea for entity-relation detection in a domain with missing annotated corpus, and the formed domain conceptual model provides a reference for building a domain Linked Data Graph. The feasibility of the method is verified through practice on texts related to the four traditional Chinese festivals.

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Conceptualising Information Production in the Context of the SDHSS Ontology Ecosystem

Beretta

2024

methodos

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Dans cet article, nous mettons au défi le programme promu par le Projet « Semantic Data for Humanities and Social Sciences » (SDHSS) visant la création d'un graphe géant d’information à partir de données de recherche réutilisables en provenance de multiples projets et plateformes, graphe basé sur les technologies du Web sémantique et sur une conceptualisation collaborative en l’espèce d'un écosystème d'ontologies interopérables et réutilisables. Trois questions principales sont abordées : la difficulté de proposer une ontologie interdisciplinaire pour les sciences humaines et sociales, compte tenu des différents agendas de recherche et des différentes approches constructivistes. La difficulté de relier entre eux les objets dans les différents systèmes d'information, en raison des différentes notions d'identité. Le défi de traiter l'incertitude, les incohérences et les contradictions dans les sources d'information, lorsque l'objectif est de produire de l’information « factuelle ». Je propose d'abord une analyse épistémologique de l'information, distincte des données et des connaissances. Je développe ensuite une conceptualisation de l'information en sciences humaines et sociales, basée sur la méthodologie OntoClean et les ontologies fondationnelles DOLCE et Descriptions et Situations, en montrant comment elle peut fonder un écosystème d’ontologies transdisciplinaires basé sur le CRM CIDOC et son intégration SDHSS. Pour finir, j'applique ces principes à une analyse détaillée du processus de production de l'information et montre comment la conceptualisation proposée fournit des solutions aux trois défis en question.

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Ontological Analysis and Modularization of CIDOC-CRM

Cited by 3 publications

References 14 publications

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

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

A Joint Entity-Relation Detection and Generalization Method Based on Syntax and Semantics for Chinese Intangible Cultural Heritage Texts

Conceptualising Information Production in the Context of the SDHSS Ontology Ecosystem

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