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Construction and Reuse of Linked Agriculture Data: An Experience of Taiwan Government Open Data

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Semantic Technology (JIST 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11341))

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Abstract

This paper describes our experiences on dealing with the transformation from Traceable Agriculture Product (TAP) records to Linked Open Government Data. By using existing ontologies and vocabularies, TAP Ontology is developed for clarifying the semantics of TAP. To increase the reusability of TAP, the crops and operational processing details of TAP are mapped to Common Agricultural Vocabulary (CAVOC). There are four SPARQL endpoints developed for supporting queries to TAP. To demonstrate the reuse of Linked TAP, we develop a Chrome extension LinkedFood to offer TAP information via reading ingredients in recipe websites.

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Notes

  1. 1.

    http://www.e-stat.go.jp/SG1/estat/List.do?lid=000001155203.

  2. 2.

    https://github.com/trashmai/LinkedFood.

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Author information

Authors and Affiliations

  1. Industrial Technology Research Institute, Taipei, Taiwan

    Dongpo Deng

  2. Biodiversity Research Center, Academia Sinica, Taipei, Taiwan

    Guan-Shuo Mai

  3. National Center for High-Performance Computing, Taipei, Taiwan

    Steven Shiau

Authors
  1. Dongpo Deng
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  2. Guan-Shuo Mai
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  3. Steven Shiau
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Corresponding author

Correspondence to Dongpo Deng .

Editor information

Editors and Affiliations

  1. National Institute of Informatics, Tokyo, Japan

    Ryutaro Ichise

  2. Accenture Labs, Dublin, Ireland

    Freddy Lecue

  3. Japan Science and Technology Agency, Tokyo, Japan

    Takahiro Kawamura

  4. Peking University, Beijing, China

    Dongyan Zhao

  5. Imperial College London, London, UK

    Stephen Muggleton

  6. Osaka University, Osaka, Japan

    Kouji Kozaki

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Deng, D., Mai, GS., Shiau, S. (2018). Construction and Reuse of Linked Agriculture Data: An Experience of Taiwan Government Open Data. In: Ichise, R., Lecue, F., Kawamura, T., Zhao, D., Muggleton, S., Kozaki, K. (eds) Semantic Technology. JIST 2018. Lecture Notes in Computer Science(), vol 11341. Springer, Cham. https://doi.org/10.1007/978-3-030-04284-4_25

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  • DOI: https://doi.org/10.1007/978-3-030-04284-4_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04283-7

  • Online ISBN: 978-3-030-04284-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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