• 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.

• 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.

• The Journal of Industrial Distribution & Business
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• v.13 no.11
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• pp.1-10
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• 2022

Purpose: This study measures the influence of facilitating conditions on employees' attitudes towards the adoption of big data analytics by selected medical aid organizations in Durban. In the health care sector, there are various sources of big data such as patients' medical records, medical examination results, and pharmacy prescriptions. Several organizations take the benefits of big data to improve their performance and productivity. Research design, data, and methodology: A survey research strategy was conducted on some selected medical aid organizations. A non-probability sampling and the purposive sampling technique were adopted in this study. The collected data was analysed using version 23 of Statistical Package for Social Science (SPSS) Results: the results show that the "facilitating conditions" have a positive influence on employees' attitudes in the adoption of big data analytics Conclusions: The findings of this study provide empirical and scientific contributions of the facilitating conditions issues regarding employee attitudes toward big data analytics adoption. The findings of this study will add to the body of knowledge in this field and raise awareness, which will spur further research, particularly in developing countries.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.87-96
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• 2021

Data-driven markets depend on access to data as a resource for products and services. Since the quality of information that can be drawn from data increases with the available amount and quality of the data, businesses involved in the data economy have a great interest in accessing data from other market players and sharing data with other stakeholders. Despite the growing need for access to data and evidence of the economic and social benefits, data access and sharing remains below its potential. Individuals, businesses, and governments often face barriers to data access, which may be compounded by the reluctance to share, including within and across sectors. To address these challenges, this paper focuses on finding possible solutions for a better data-sharing economy. This paper 1) Discusses opportunities and challenges of open data and the data-sharing economy, limitations of private sector data, and issues with open government data. 2) Introduces open government data initiatives and open governance networks initiatives. 3) Suggests possible solutions, including the governance and management, the legal and policy frameworks, and the technical standards for open data with proposing an open data governance model for the data-sharing economy.

• 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.

• Journal of Information Technology Services
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• v.21 no.5
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• pp.15-28
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• 2022

Recently, government agencies are actively adopting the platform model as a means of public policy. However, existing studies on the public platform are minimal and have focused on user experiences or the possibility of public usage of the platform model. Now the research concerning building governance structure and utilizing network effects of the platform after adopting the platform model in the public sector is keenly required. This study intended to ignite academic dialogue on the governance of public platforms in the context of digital transformation. This study focused on a case of the 'Special delivery,' a public delivery app established by Gyeonggi-do. In order to analyze the characteristics of the public platform and its governance structure, data were collected from press releases, policy reports, and news articles. Data was analyzed using the frame of Hagui's platform design factors and Ansell & Gash's collaborative governance model. The results of the public platform analyses showed 1) incompleteness in the value trade-off accounting, which was designed for platform business based on general cost-benefit analysis, and 2) a closed governance structure that limits direct participation of diverse user groups(i.e., service provider, customer) in order to enhance providers' utility by preventing customers' excessive online activities. The results of this study provided theoretical and policy implications regarding designing the strategy for accounting for value trade-offs and functioning governance structure for public platforms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.218-220
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• 2014

Data economy era is rapidly approaching where big data plays the pivotal role of creating new values and solving various problems. This paper aims at designing Korea's new strategic direction of informatization in the big data age. For this purpose, paradigm shift of our society and the new role of IT together with the discussion on open platform and big data focused on its potentials and new possibilities are analyzed, which leads to the conclusion that big data will be a main engine for creating new values. Based on the results of the analysis, three kinds of strategic direction is designed. The first direction is on national vision making and 'data analysis-based creative nation' is suggested. The second direction is on catalyst making and 'smart government utilizing the power of big data' is proposed in details. The third direction is on sustainable leading mechanism and 'collaborative governance between stakeholders' is suggested.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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• pp.281-282
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• 2015

Data, by itself, will not reveal the optimal policy choice. Nor will data alone tell us what problems to focus on or how to direct resources. It should be recognized upfront that data-driven policy making cannot provide all the answers to the challenges of good governance. Policy decisions always depend on a combination of facts, analysis, judgment, and values. In this paper, we research on factors to design an organizational policy making for Big Data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.579-589
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• 2016

This research focuses on accomplishing analysis problems and issues by examining the policies and systems related to geo-spatial big data which have recently arisen, and suggests political and systemic improvement plan for service activation. To do this, problems and probable issues concerning geo-spatial big data service activation should be analyzed through the examination of precedent studies, policies and planning, pilot projects, the current legislative situation regarding geo-spatial big data, both domestic and abroad. Therefore, eight political and systematical improvement plan proposals are suggested for geo-spatial big data service activation: legislative-related issues regarding geo-spatial big data, establishing an exclusive organization in charge of geospatial big data, setting up systems for cooperative governance, establishing subsequent systems, preparing non-identifying standards for personal information, providing measures for activating civil information, data standardization on geo-spatial big data analysis, developing analysis techniques for geo-spatial big data, etc. Consistent governmental problem-solving approaches should be required to make these suggestions effectively proceed.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.245-256
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• 2021

The Fourth Industrial Revolution brought the quantitative value of data across the industry and entered the era of 'Big Data'. This is due to both the rapid development of information & communication technology and the diversity & complexity of customer purchasing tendencies. An enterprise's core competence in the Big Data Era is to analyze and utilize the data to make strategic decisions for enterprise. However, most of traditional studies on Big Data have focused on technical issues and future potential values. In addition, these studies lacked interest in managing the quality and utilization levels of internal & external customer Big Data held by the entity. To overcome these shortages, this study attempted to derive influential factors by recognizing the quality management information systems and quality management of the internal & external Big Data. First of all, we conducted a survey of 204 executives & employees to determine whether Big Data quality management, Big Data utilization, and level management have a significant impact on corporate work efficiency & corporate management performance. For the study for this purpose, hypotheses were established, and their verifications were carried out. As a result of these studies, we found that the reasons that significantly affect corporate management performance are support from the management class, individual innovation, changes in the management environment, Big Data quality utilization metrics, and Big Data governance system.