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Analysis of standard vocabulary use of the open government data: the case of the public data portal of Korea

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  • Haklae Kim

    (Korea Institute of Science and Technology Information)

Abstract

Open data is an important element in a variety of new industries, such as artificial intelligence and smart cities. While the South Korean government is continuously releasing new data on the public data portal, it is limited in the accomplishment of the goals such as job creation and the new economic leaps expected by the Korean government. From a data point of view, this limitation is due to a lack of data that users require and a lot of low-quality data to use. This paper analyses standard terms used in public data. The findings of this study reveals that standard vocabularies established by the government require updates to reflect the nature of public data, and the relevant laws and guidelines need to be revised.

Suggested Citation

  • Haklae Kim, 2019. "Analysis of standard vocabulary use of the open government data: the case of the public data portal of Korea," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(3), pages 1611-1622, May.
    • Handle: RePEc:spr:qualqt:v:53:y:2019:i:3:d:10.1007_s11135-018-0829-z
    DOI: 10.1007/s11135-018-0829-z
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    References listed on IDEAS

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    1. Donghun Yoon, 2017. "The information science policy for the public open data of the national research institute," Cogent Business & Management, Taylor & Francis Journals, vol. 4(1), pages 1406321-140, January.
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    Cited by:

    1. Jae-Geum Shim & Kyoung-Ho Ryu & Sung Hyun Lee & Eun-Ah Cho & Yoon Ju Lee & Jin Hee Ahn, 2021. "Text Mining Approaches to Analyze Public Sentiment Changes Regarding COVID-19 Vaccines on Social Media in Korea," IJERPH, MDPI, vol. 18(12), pages 1-9, June.
    2. Ibrahim Mutambik & Abdullah Almuqrin & John Lee & Justin Zuopeng Zhang & Abdulaziz Alomran & Taha Omar & Ahmad Floos & Abdullah Homadi, 2021. "Usability of the G7 Open Government Data Portals and Lessons Learned," Sustainability, MDPI, vol. 13(24), pages 1-17, December.

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