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YAMAML: An Application Profile Based Lightweight RDF Mapping Language

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Book cover From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries (ICADL 2022)

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Abstract

YAMA Mapping Language (YAMAML) is a lightweight mapping language for generating RDF. YAMAML is based on Yet Another Metadata Application Profiles (YAMA). YAMA is an extensible intermediary application profile authoring format for generating application profile expressions. Application profiles are a combination of vocabularies, which are mixed and matched from different namespaces and optimized for a particular local application. YAMA is based on Description Set Profiles (DSP), a Dublin Core Application Profiles constraint language. YAMA is implemented on YAML, one of the most human-readable data serialization formats. As a superset of JSON, YAML is highly interoperable and has parsers and emitters in all major programming languages. It adapts the basic application profile elements from YAMA and is designed as a simplified markup language to map non-RDF data structures to RDF and generate corresponding RDF based on the application profile. It is proposed as an intermediary format for generating RDF, but not as an RDF representation syntax. The authors demonstrate the capability of YAMAML by developing a basic specification and proof of concept implementations.

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Notes

  1. 1.

    https://www.w3.org/DesignIssues/LinkedData.

  2. 2.

    https://metabridge.jp/.

  3. 3.

    https://yaml.org/spec/1.2.2/.

  4. 4.

    https://github.com/dcmi/dctap.

  5. 5.

    http://tarql.github.io.

  6. 6.

    https://linkml.io.

  7. 7.

    https://rml.io/yarrrml/.

  8. 8.

    https://github.com/AtesComp/rdf-transform.

  9. 9.

    https://openrefine.org.

  10. 10.

    https://shex.io.

References

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Acknowledgements

This work was supported by JSPS KAKENHI Grant Number 21K12579.

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Authors and Affiliations

  1. Graduate School of Library, Information and Media Studies, Tsukuba, Japan

    Nishad Thalhath

  2. Faculty of Library, Information and Media Studies, University of Tsukuba, Tsukuba, Japan

    Mitsuharu Nagamori & Tetsuo Sakaguchi

Authors
  1. Nishad Thalhath
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  2. Mitsuharu Nagamori
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  3. Tetsuo Sakaguchi
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Corresponding author

Correspondence to Nishad Thalhath .

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Editors and Affiliations

  1. National Taiwan Normal University, Taipei, Taiwan

    Yuen-Hsien Tseng

  2. Doshisha University, Kyoto, Japan

    Marie Katsurai

  3. VNU University of Engineering and Technology, Hanoi, Vietnam

    Hoa N. Nguyen

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Thalhath, N., Nagamori, M., Sakaguchi, T. (2022). YAMAML: An Application Profile Based Lightweight RDF Mapping Language. In: Tseng, YH., Katsurai, M., Nguyen, H.N. (eds) From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries. ICADL 2022. Lecture Notes in Computer Science, vol 13636. Springer, Cham. https://doi.org/10.1007/978-3-031-21756-2_32

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  • DOI: https://doi.org/10.1007/978-3-031-21756-2_32

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-21756-2

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