A strategy for archives metadata representation on CIDOC-CRM and knowledge discovery

Melo, Dora; Rodrigues, Irene Pimenta; Varagnolo, Davide

doi:10.3233/sw-222798

Cited by 5 publications

(2 citation statements)

References 20 publications

(30 reference statements)

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“…The Baptismo and Passaportes datasets [13] were automatically represented in CIDOC CRM from their ISAD(G) description. The translation is based on rules that map the archival descriptive information to the CIDOC CRM representation semantically [12]. Additionally, the translated information was subject to some refinements to correspond to the same CIDOC CRM version used in ArchOnto.…”

Section: Linked Data Representationmentioning

confidence: 99%

From ISAD(G) to Linked Data Archival Descriptions

Koch,

Pires,

Teixeira Lopes

et al. 2023

Linking Theory and Practice of Digital Libraries

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Archives preserve materials that allow us to understand and interpret the past and think about the future. With the evolution of the information society, archives must take advantage of technological innovations and adapt to changes in the kind and volume of the information created. Semantic Web representations are appropriate for structuring archival data and linking them to external sources, allowing versatile access by multiple applications. ArchOnto is a new Linked Data Model based on CIDOC CRM to describe archival objects. ArchOnto combines specific aspects of archiving with the CIDOC CRM standard.In this work, we analyze the ArchOnto representation of a set of archival records from the Portuguese National Archives and compare it to their CIDOC CRM representation. As a result of ArchOnto's representation, we observe an increase in the number of classes used, from 20 in CIDOC CRM to 28 in ArchOnto, and in the number of properties, from 25 in CIDOC CRM to 28 in ArchOnto. This growth stems from the refinement of object types and their relationships, favouring the use of controlled vocabularies. ArchOnto provides higher readability for the information in archival records, keeping it in line with current standards.

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Section: Linked Data Representationmentioning

confidence: 99%

From ISAD(G) to Linked Data Archival Descriptions

Koch,

Pires,

Teixeira Lopes

et al. 2023

Linking Theory and Practice of Digital Libraries

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“…In [45], the authors proposed an approach for improving the Data Entry process by performing text classification, extraction and representation for Portuguese National Archives records. The target is the extracted information (from text) to be represented by using CIDOC-CRM ontology and then is visualized by using a Query Ontology Interface.…”

mentioning

confidence: 99%

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

et al. 2022

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The CIDOC Conceptual Reference Model (CIDOC-CRM) is an ISO Standard ontology for the cultural domain that is used for enabling semantic interoperability between museums, libraries, archives and other cultural institutions. For leveraging CIDOC-CRM, several processes and tasks have to be carried out. It is therefore important to investigate to what extent we can automate these processes in order to facilitate interoperability. For this reason, in this paper, we describe the related tasks, and we survey recent works that apply machine learning (ML) techniques for reducing the costs related to CIDOC-CRM-based compliance and interoperability. In particular, we (a) analyze the main processes and tasks, (b) identify tasks where the recent advances of ML (including Deep Learning) would be beneficial, (c) identify cases where ML has been applied (and the results are successful/promising) and (d) suggest tasks that can benefit from applying ML. Finally, since the approaches that leverage both CIDOC-CRM data and ML are few in number, (e) we introduce our vision for the given topic, and (f) we provide a list of open CIDOC-CRM datasets that can be potentially used for ML tasks.

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