The Universal Decimal Classification (UDC) in the semantic web

analysis of UDC Summary Linked Data

Authors

  • Kazumi Tomoyose Federal University of São Carlos
  • Ana Carolina Simionato Arakaki Federal University of São Carlos

DOI:

https://doi.org/10.11606/issn.2178-2075.v10i2p138-157

Keywords:

Classification, Universal Decimal Classification (UDC), UDC Summary Linked Data, Linked data, Semantic Web

Abstract

As the classification process is one of the main activities of Information Science in relation to the organization of information, the present work deals with the concepts of the discipline of Classification applied to the Semantic Web, focusing on the Linked Data principles, as a way of providing order and standardization to the terms used in data interconnection, through the UDC Summary Linked Data initiative. Through an exploratory, theoretical and applied research it is sought to verify the presence of the initiative in the search tools of information centers’ catalogs, as well as the benefits that it provides to the institutions. To this end, 26 Online Public Access Catalogs (OPACs) were investigated to identify the adoption of UDC Summary Linked Data. It was possible to verify that none of the catalogs investigated adheres to the UDC Summary Linked Data, besides the scarcity of productions in the literature that discuss the initiative. As a possible propeller to the visibility of the summary in Linked Data, it is suggested its insertion in the Linked Data Open Cloud diagram. However, the restriction on the number of notations that incorporate the UDC Summary Linked Data limits its adoption, reducing the flexibility of use by information centers. It is considered that the implementation of the initiative promotes a more semantic thematic representation of information, also benefiting the discovery and visibility of different sources of information.

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Author Biographies

  • Kazumi Tomoyose, Federal University of São Carlos

    Master student in Information Science at the Federal University of São Carlos (PPGCI/UFSCar), with assistance from the Foundation for Research Support of the State of São Paulo (FAPESP). Graduated in Librarianship and Information Science at the Federal University of São Carlos - UFSCar (2018), where she undertook Scientific Initiation with the help of the Foundation for Research Support of the State of São Paulo (FAPESP). Participates in the Data and Metadata Research Group (GPDM), at UFSCar. Has experience working in libraries and other information centers, having done an internship at the Centro Universitário Central Paulista's library - Unicep (2015) and at the Data Management sector of the Health School Unit - USE/UFSCar. Has experience in the area of ​​Information Science, with emphasis in Librarianship, with interest in the following topics: information representation, metadata and Linked Data.

  • Ana Carolina Simionato Arakaki, Federal University of São Carlos

    Graduated in Library Science from Paulista State University "Júlio de Mesquita Filho" - UNESP (2010), Master's degree (2012) and PhD (2015) in Information Science (Research Line 'Information and Technology') from Paulista State University "Júlio de Son Mosque "- UNESP. Since 2015, she is an Associate Professor at the Department of Information Science, Federal University of São Carlos - UFSCar, acting in the graduate Program in Information Science - PPCGI / UFSCar and undergraduate Library and Information Science - BCI / UFSCar. She is leader of the research group "Data and Metadata" and collaborates with the research groups "Organization and Representation of Information and Knowledge of Imaging Resources" and "New Technologies in Information". She is currently the Coordinator of the Coordination of the Scientific and Technological Initiation Programs (CoPICT) of the UFSCar's Rectory of Research (ProPq). Has experience in metadata, cataloging and archival and museum description, conceptual and audiovisual modeling. Her preferred themes are: Data and Metadata, Linked Data, Conceptual Model, Data Model, Digital Curation, Cultural Heritage, Image and Audiovisual.

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Published

2019-01-22

Issue

Vol. 10 No. 2 (2019)

Section

Articles

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How to Cite

TOMOYOSE, Kazumi; ARAKAKI, Ana Carolina Simionato. The Universal Decimal Classification (UDC) in the semantic web: analysis of UDC Summary Linked Data. InCID: Revista de Ciência da Informação e Documentação, Ribeirão Preto, Brasil, v. 10, n. 2, p. 138–157, 2019. DOI: 10.11606/issn.2178-2075.v10i2p138-157. Disponível em: https://www.periodicos.usp.br/incid/article/view/161278.. Acesso em: 18 may. 2024.