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Sustainable Data Governance of Government

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 4175

Special Issue Editors


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Guest Editor
Department of Library and Information Science, Chung-Ang University, Seoul, Korea
Interests: knowledge engineering; open data; data science
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Guest Editor
Department of Software Convergence Engineering, Kunsan National University, Gunsan 54150, Korea
Interests: knowledge graph; open data; data mining; patent analysis
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Guest Editor
Department of Convergence & Fusion System Engineering, Kyungpook National University, Sangju, Republic of Korea
Interests: data science; AI; machine learning; smart control; energy ICT
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Data are recognized as a key element for the realization of scientific administration and effective decision-making in government. Governments around the world are pushing data policies to enhance the country. The UK, for example, has established a National Data Strategy, which contains 1) unlocking the value of data across the economy, 2) securing a pro-growth and trusted data regime, 3) transforming the government’s use of data to drive efficiency and improve public services, 4) ensuring the security and resilience of the infrastructure on which data rely, and 5) championing the international flow of data as its main missions.

Data-driven governments should reflect the opportunities and challenges that data have. Data policy at the government level covers a wide range and is characterized by processing public data. At the same time, it can have a comprehensive impact on the daily life of citizens. Therefore, government-level data require an appropriate convergence of administrative sustainability, infrastructure, and the advanced and mature technologies. A data governance at the government level should be discussed to coordinate the promotion of data policies of different government agencies. From a technical point of view, it is necessary to investigate the method of constructing a data catalog and applying FAIRness to data that exist distributedly in public institutions.

This Special Issue discusses various theoretical and practical topics for the establishment and realization of sustainable data policies in the public sectors. It covers major issues related to data governance, such as technological elements and application plans necessary to realize a data-driven government such as artificial intelligence, big data, and data science, laws and systmes, open data and their disclosure, data-driven public services, and privacy issues.

Prof. Dr. Haklae Kim
Prof. Dr. Jangwon Gim
Prof. Dr. Dongjun Suh
Guest Editors

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Keywords

  • sustainable data governance
  • national data policy
  • data catalog across government agencies
  • advanced technology adoption in governments
  • knowledge management
  • open data
  • data governance
  • data interoperability
  • general aspects of data quality
  • data quality management
  • data quality assessment
  • roles and responsibilities for data quality
  • data refinement
  • data profiling
  • application domain data
  • standardization
  • machine-readable data
  • artificial intelligence
  • machine learning
  • big data analytics
  • data-driven technology
  • sustainable smart technology
  • AI- and ML-based applications

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Published Papers (1 paper)

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Research

31 pages, 8591 KiB  
Article
Analysis of OpenStreetMap Data Quality for Selected Counties in Poland in Terms of Sustainable Development
by Sylwia Borkowska and Krzysztof Pokonieczny
Sustainability 2022, 14(7), 3728; https://doi.org/10.3390/su14073728 - 22 Mar 2022
Cited by 15 | Viewed by 3343
Abstract
One potential source of geospatial open data for monitoring sustainable development goals (SDG) indicators is OpenStreetMap (OSM). The purpose of this paper is to provide a comprehensive evaluation of the spatial data quality elements of OSM against the national official data—the database of [...] Read more.
One potential source of geospatial open data for monitoring sustainable development goals (SDG) indicators is OpenStreetMap (OSM). The purpose of this paper is to provide a comprehensive evaluation of the spatial data quality elements of OSM against the national official data—the database of topographic objects at a scale of 1:10,000. Such spatial data quality elements as location accuracy, data completeness and attribute compatibility were analysed. In the conducted OpenStreetMap tests, basic land-cover classes such as roads, railroads, river network, buildings, surface waters and forests were analysed. The test area of the study consisted of five counties in Poland, which differ in terms of location, relief, surface area and degree of urbanization. The best results of the quality of OSM spatial data were obtained for highly urbanized areas with developed infrastructure and a high degree of affluence. The highest degree of completeness of OSM linear and area objects in the studied counties was acquired in Piaseczyński County (82%). The lowest degree of completeness of the line and area objects of OSM in the studied counties was obtained in the Ostrowski County (51%). The calculated correlation coefficient between the quality of OSM data and the income per capita in the county was 0.96. The study complements the previous research results in the field of quantitative analysis of the quality of OSM data, and the obtained results confirm their dependence on the geometric type of the analysed objects and characteristics of test areas, i.e., in this case counties in Poland. The obtained results of OSM data quality analysis indicate that OSM data may provide strong support for other spatial data, including official and state data. OSM stores significant amounts of geospatial data with relatively high data quality that can be a valuable source for monitoring some SDG indicators. Full article
(This article belongs to the Special Issue Sustainable Data Governance of Government)
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