• Title, Summary, Keyword: Bigdata

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Educational Policy Proposals through Analysis of the Perception of Bigdata for University Students (학부생의 빅데이터 인식 분석을 통한 교육정책 제언)

  • Noh, Kyoo-Sung
    • Journal of Digital Convergence
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    • v.13 no.11
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    • pp.25-33
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    • 2015
  • In Korea, despite the increase in demand for Bigdata manpower, institutions and universities to educate and train Bigdata manpower are not yet much. Therefore, this study investigated the status regarding the recognition on Bigdata of universities students and presented a direction for educating Bigdata manpower at the university. In order to accomplish this purpose, this study surveyed and analyzed the students' understanding of Bigdata, the awareness of the students about the social impact of Bigdata, the learning intention of the students on Bigdata and presented Implications for Bigdata workforce development. As a result, despite of the somewhat difference in understanding for the Bigdata, it was found that their awareness about the impact of Bigdata is very positive. And this study showed the need of universities' and government' political effort for Bigdata workforce development, because it was investigated that students' intentions of learning for Bigdata is proportional to students' understanding levels and learning experience for Bigdata.

The Necessity and Case Analysis of Bigdata Quality Control in Medical Institution (의료기관 빅데이터 품질관리의 필요성과 사례 분석)

  • Choi, Hye Rin;Lee, Seung Won;Kim, YoungAh;Lee, Jong Ho;Koh, Hong;Kim, Hyeon Chang
    • The Journal of Bigdata
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    • v.2 no.2
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    • pp.67-74
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    • 2017
  • The use of Bigdata plays an important role in all areas of society. Especially in the health care field, the role of Bigdata is very considerable because it deals with people's life and health. However, the interest and awareness of quality control of medical data is markedly low. Because the low-quality medical Bigdata leads to national loss and public health impairment, quality control of medical Bigdata is needed. The purpose of this research is to present the direction of medical Bigdata quality management by examining literature and cases of domestic and foreign medical Bigdata quality management practices. In addition, as a case of medical Bigdata quality control in the Y medical institution in Korea, activities of a Bigdata quality management TFT and results of a survey conducted for major data users in the hospital were presented.

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A Study on Analysis of the Differences for Perception of Big Data in Era of Convergence (융합시대 빅데이터 인식 차이 분석에 관한 연구)

  • Noh, Kyoo-Sung;Lee, Joo-Yeoun
    • Journal of Digital Convergence
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    • v.13 no.10
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    • pp.305-312
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    • 2015
  • In Korea, institutions and universities to educate and train Bigdata manpower are not yet much. There are various causes, but major cause among them is lack of understanding and perception on Bigdata. Therefore, this study investigated the situation regarding the recognition on Bigdata of universities' faculties and presented a direction for educating Bigdata manpower at the university. As a result, it was investigated that their awareness about the impact of Bigdata is not so great, despite of the somewhat understanding for the Bigdata. In particular, it was investigated that their intentions of research and education for Bigdata are not high. So, for a while, it was identified that Bigdata specialist training will not be easy. In conclusion, this study suggested that the government should pay its attention more on policy for Bigdata manpower training policy of the universities according to direction of the government 3.0 policy that considers the Bigdata to the axis of the major policy.

Methodological Implications of Employing Social Bigdata Analysis for Policy-Making : A Case of Social Media Buzz on the Startup Business (빅데이터를 활용한 정책분석의 방법론적 함의 : 기회형 창업 관련 소셜 빅데이터 분석 사례를 중심으로)

  • Lee, Young-Joo;Kim, Dhohoon
    • Journal of Information Technology Services
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    • v.15 no.1
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    • pp.97-111
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    • 2016
  • In the creative economy paradigm, motivation of the opportunity based startup is a continuous concern to policy-makers. Recently, bigdata anlalytics challenge traditional methods by providing efficient ways to identify social trend and hidden issues in the public sector. In this study the authors introduce a case study using social bigdata analytics for conducting policy analysis. A semantic network analysis was employed using textual data from social media including online news, blog, and private bulletin board which create buzz on the startup business. Results indicates that each media has been forming different discourses regarding government's policy on the startup business. Furthermore, semantic network structures from private bulletin board reveal unexpected social burden that hiders opening a startup, which has not been found in the traditional survey nor experts interview. Based on these results, the authors found the feasibility of using social bigdata analysis for policy-making. Methodological and practical implications are discussed.

The Bigdata Processing Environment Building for the Learning System (학습 시스템을 위한 빅데이터 처리 환경 구축)

  • Kim, Young-Geun;Kim, Seung-Hyun;Jo, Min-Hui;Kim, Won-Jung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.9 no.7
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    • pp.791-797
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    • 2014
  • In order to create an environment for Apache Hadoop for parallel distributed processing system of Bigdata, by connecting a plurality of computers, or to configure the node, using the configuration of the virtual nodes on a single computer it is necessary to build a cloud fading environment. However, be constructed in practice for education in these systems, there are many constraints in terms of cost and complex system configuration. Therefore, it is possible to be used as training for educational institutions and beginners in the field of Bigdata processing, development of learning systems and inexpensive practical is urgent. Based on the Raspberry Pi board, training and analysis of Big data processing, such as Hadoop and NoSQL is now the design and implementation of a learning system of parallel distributed processing of possible Bigdata in this study. It is expected that Bigdata parallel distributed processing system that has been implemented, and be a useful system for beginners who want to start a Bigdata and education.

Strategy Design to Protect Personal Information on Fake News based on Bigdata and Artificial Intelligence

  • Kang, Jangmook;Lee, Sangwon
    • International Journal of Internet, Broadcasting and Communication
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    • v.11 no.2
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    • pp.59-66
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    • 2019
  • The emergence of new IT technologies and convergence industries, such as artificial intelligence, bigdata and the Internet of Things, is another chance for South Korea, which has established itself as one of the world's top IT powerhouses. On the other hand, however, privacy concerns that may arise in the process of using such technologies raise the task of harmonizing the development of new industries and the protection of personal information at the same time. In response, the government clearly presented the criteria for deidentifiable measures of personal information and the scope of use of deidentifiable information needed to ensure that bigdata can be safely utilized within the framework of the current Personal Information Protection Act. It strives to promote corporate investment and industrial development by removing them and to ensure that the protection of the people's personal information and human rights is not neglected. This study discusses the strategy of deidentifying personal information protection based on the analysis of fake news. Using the strategies derived from this study, it is assumed that deidentification information that is appropriate for deidentification measures is not personal information and can therefore be used for analysis of big data. By doing so, deidentification information can be safely utilized and managed through administrative and technical safeguards to prevent re-identification, considering the possibility of re-identification due to technology development and data growth.