Study on Government Data Governance Framework: Based on the National Data Strategy in the US, the UK, Australia, and Japan

Jeong Eun Seo, Hun Yeong Kwon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Most government agencies today have a perception that data is essential. However, creating a culture that encourages public servants to perceive data as an asset and make data-driven decisions is challenging. Data governance helps reduce the cost of data management and create value from the data. However, data is often dispersed across many organizations with different data policies in place, stored, and utilized. It can lead to accountability issues and poor data quality, and economic decline based on data utilization. The government data governance framework is one of the solutions to this problem, but there is a lack of discussion of a national data governance framework. Therefore, this paper analyzes the NDS of the US, the UK, Australia, and Japan based on the DGF of the DGI to derive the essential considerations in formulating national data strategies. And then, we suggest the components of the Government Data Governance Framework. These components are essential elements to be discussed in the establishment of NDS. This paper's results can help establish a new NDS or modify the established NDS.

Original languageEnglish
Title of host publicationBig Data, Cloud Computing, and Data Science Engineering
EditorsRoger Lee
PublisherSpringer Science and Business Media Deutschland GmbH
Pages133-144
Number of pages12
ISBN (Print)9783031196072
DOIs
Publication statusPublished - 2023
Event7th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science Engineering, BCD 2022 - Danang, Viet Nam
Duration: 2022 Aug 42022 Aug 6

Publication series

NameStudies in Computational Intelligence
Volume1075
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503

Conference

Conference7th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science Engineering, BCD 2022
Country/TerritoryViet Nam
CityDanang
Period22/8/422/8/6

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • DGI
  • Data governance
  • Data governance framework
  • Government data governance framework
  • National Data Strategy

ASJC Scopus subject areas

  • Artificial Intelligence

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