• Journal of Digital Convergence
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• v.20 no.4
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• pp.133-145
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• 2022

As a result of the study, the poorest keywords were information, big data, management, policy, government, law, and smart. In addition, as a result of network analysis, related research was being conducted on topics such as data industry policy, data governance performance, defense, governance, and data public. The four topics derived through topic modeling were "DG policy," "DG platform," "DG in laws," and "DG implementation," of which research related to "DG platform" showed an increasing trend, and "DG implementation" tended to shrink. This study comprehensively summarized data governance-related studies. Data governance needs to expand research areas from various perspectives and related fields such as data management and data integration policies at the organizational level, and related technologies. In the future, we can expand the analysis targets for overseas data governance and expect follow-up studies on research directions and policy directions in industries that require data-based future industries such as Industry 4.0, artificial intelligence, and Metaverse.

• Informatization Policy
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• v.30 no.3
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• pp.29-48
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• 2023

This study aims to investigate empirically the structural relationships among the components of data governance and their impacts on data integration and data-based administration. Through literature review, various definitions, typologies, and case studies of data governance were examined, with the definition of data governance from a public policy perspective developed and applied. The study then analyzed the data from a survey conducted by the Korea Institute of Public Administration on the use of public data policies and confirmed that organizational factors play a mediating role between institutional and technical factors, and that institutional and technical factors have statistically significant positive relationships with data fusion and data-driven administration. Based on these results, interest and investment in the improvement and development of the legal system in data governance from the institutional, technical, and organizational perspective, clarification of means and purposes of data technology, interest in data organizations and human resources, and practical operation can be achieved. Policy implications such as the development of an effective mechanism were presented.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.2
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• pp.57-66
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• 2017

The academic research on data governance is still in its infancy and focused on the definition of concept and components. However, we need to study of evaluation on data governance to help make decision of establishment. The purpose of this paper is to develop of attribute index in data governance framework. Therefore, in this paper, we used RGT (repertory grid technique) and Laddering techniques for experts interview and survey for validation of disinterested third party experts and analysis statistically. We completed data governance attribute index which is composed of data compliance area including 8 components, data quality area including 16 components and data organization area including 7 components. Moreover, the evaluation attributes is prioritized and ranked using the AHP. As a result of the study, this paper can be used for the base line data in introducing and operating data governance in an IT company.

• Digital Contents
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• no.10 s.161
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• pp.46-47
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• 2006

한국데이터베이스진흥센터가 주관하는 '2006 데이터베이스 그랜드 컨퍼런스'가 최근 부각되고 있는 데이터 거버넌스를 주제로 지난달 20일 코엑스 인터컨티넨탈 호텔에서 개최됐다. 이번 행사는 기업들이 당면하고 있는 데이터 품질 확보를 위한 해법으로 데이터 거버넌스를 제안, 관련 분야의 해외 전문가들을 초청하여 선진 기술동향을 파악할 수 있는 계기가 됐다는 평가다.

• The Journal of Bigdata
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• v.3 no.2
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• pp.1-10
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• 2018

In the field of smart water management, there is an increasing demand for strengthening competitiveness through big data analysis. As a result, systematic management (Governance) of big data is becoming an important issue. Big data governance is a systematic approach to evaluating, directing and monitoring data management, such as data quality assurance, privacy protection, data lifetime management, data ownership and clarification of management rights. Failure to establish big data governance can lead to serious problems by using low quality data for critical decisions. In addition, personal privacy data can make Big Brother worry come true, and IT costs can skyrocket due to the neglect of data age management. Even if these technical problems are fixed, the big data effects will not be sustained unless there are organizations and personnel who are dedicated and responsible for data-related issues. In this paper, we propose a method of building data governance for smart water data management based on big data.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.69-78
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• 2013

This paper introduces the alignment background, analyzes some alignment issues. a practical the model of Data Governance for business and IT alignment is describes to implement the alignment so as to improve organizations innovation competency. Business and Information Technology alignment plays an important role in the business operation. Data Governance is an emerging approach which has been proven in some organizations to meet alignment demand. This paper proposes the model of Data Governance and proves the effective through implementation. This could be a good model of benchmarking for the best data quality management of all organizations.

• The Journal of Bigdata
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• v.4 no.1
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• pp.39-51
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• 2019

With the advent of the fourth industrial revolution characterized by hyperconnectivity and superintelligence and the emerging cyber physical systems, enormous volumes of data are being generated in the cyberspace every day ranging from the records about human life and activities to the communication records of computers, information and communication devices, and the Internet of things. Big data represented by 3Vs (volume, velocity, and variety) are actively used in the defence field as well. This paper proposes a big data governance model to support effective military operations in the cyberspace. Cyberspace operation missions and big data types that can be collected in the cyberspace are classified and integrated with big data governance issues to build a big data governance framework model. Then the effectiveness of the constructed model is verified through examples. The result of this study will be able to assist big data utilization planning in the defence sector.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.83-90
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• 2019

In addition to the proliferation of intelligent information technology, the field of disaster management is being approached from a multifaceted perspective. In particular, as the interest in establishing a disaster safety management system using data increases, there is an increasing need for a large amount of big data distribution generated in real time and a systematic management. Furthermore, efforts are being made to improve the quality of data in order to increase the prevention effect of disasters through data analysis and to make a system that can respond effectively and to predict the overall situation caused by the disasters. Disaster management should seek both precautionary measures and quick responses in the event of a disaster as well as a technical approach to establishing governance and safety. This study explores the policy implications of the significance and structure of disaster safety management governance using data.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1402-1405
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• 2012

데이터 품질의 패러다임 변화에 따라 기업에서는 효과적인 의사결정지원을 위한 정보서비스의 품질 관리가 중요하다. 본 연구에서는 설문조사를 통해 데이터 거버넌스 관점에서 행정기관 간 정보연계를 통해 민본 녹색 행정을 위한 '행정정보공동이용시스템'의 데이터 품질관련 현황을 분석하였다. 이와 관련하여 향후 정확하고 안전한 행정정보의 공동이용을 위한 정보서비스 품질관리체계 구축을 위한 대안으로서 데이터 거버넌스 관점의 행정정보 공유 데이터 품질관리체계 구축을 제시하는 바이다.

• Informatization Policy
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• v.28 no.2
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• pp.98-113
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• 2021

This study presents implications of the Global Data Law & Policy by comparing national data strategies, data regulations and policies, and governance in South Korea, the United States, the United Kingdom, and the European Union. According to the result of the comparative analysis, the biggest difference is in data governance, in other words, the management and coordination of policies at the pan-government level and data ethics. Therefore, this study proposes the establishment of a presidential special committee on data policy or the creation of a 'National Digital Innovation Office' at the Presidential Secretariat as a national CDO for the governance of data policies. Furthermore, this paper suggests a) to enact 'the Framework Act on the Development of Data Industry' that can regulate data practices in the private sector, b) to institutionalize the data-centric security and data protection, c) to settle the public ethics and personnel management based on data expertise and professional ethics, including explainability and responsibility, and d) the education and training systems.