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Aggregation and Utilization of Metadata for Intangible Folk Cultural Properties Using Linked Open Data

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Diversity, Divergence, Dialogue (iConference 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12645))

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Abstract

Intangible Folk Cultural Properties (IFCP) represent cultural customs or events related to transition in people’s lives, and need to be protected and passed on to future generations. The Japanese government adopted the revised Act on Protection of Cultural Properties in 2018, which aims to ensure comprehensive protection and utilization of cultural properties. IFCP are required to make it available and accessible to the public considering these features. This study proposes an IFCP data model using Linked Open Data (LOD). This model is based on the CIDOC Conceptual Reference Model (CRM) and other vocabularies. We constructed a dataset based on this model and published it on the web. The dataset contains 5,106 triples from 103 IFCP focusing on religious faiths festivals (RF) and annual observances (AO). To evaluate our data model, we defined functional requirements for the IFCP and implemented a prototype system to verify utilization feasibility of the IFCP. The prototype system shows the IFCP lists based on retrieval feature using the SPARQL query language.

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Authors and Affiliations

  1. University of Tsukuba, Tsukuba, Ibaraki, Japan

    Itsumi Sato & Masao Takaku

Authors
  1. Itsumi Sato
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  2. Masao Takaku
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Corresponding author

Correspondence to Itsumi Sato .

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Editors and Affiliations

  1. Humboldt University of Berlin, Berlin, Germany

    Katharina Toeppe

  2. Renmin University of China, Beijing, China

    Hui Yan

  3. The University of Hong Kong, Hong Kong, Hong Kong

    Samuel Kai Wah Chu

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Sato, I., Takaku, M. (2021). Aggregation and Utilization of Metadata for Intangible Folk Cultural Properties Using Linked Open Data. In: Toeppe, K., Yan, H., Chu, S.K.W. (eds) Diversity, Divergence, Dialogue. iConference 2021. Lecture Notes in Computer Science(), vol 12645. Springer, Cham. https://doi.org/10.1007/978-3-030-71292-1_14

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  • DOI: https://doi.org/10.1007/978-3-030-71292-1_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-71291-4

  • Online ISBN: 978-3-030-71292-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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