• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.125-138
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• 2016

Currently, there is increasing demand for weather information, however, providing meteorology and climate information is limited. In order to improve them, supporting the meteorology and climate big data platform use and training the meteorology and climate big data specialist who meet the needs of government, public agencies and corporate, are required. Meteorology and climate big data requires high-value usable service in variety fields, and it should be provided personalized service of industry-specific type for the service extension and new content development. To provide personalized service, it is essential to build the collaboration ecosystem at the national level. Building the collaboration ecosystem environment, convergence of marine policy and climate policy, convergence of oceanography and meteorology and convergence of R&D basic research and applied research are required. Since then, demand analysis, production sharing information, unification are able to build the collaboration ecosystem.

• Electronics and Telecommunications Trends
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• v.31 no.2
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• pp.51-62
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• 2016

인공지능(Artificial Intelligence: AI)이 사물인터넷, 빅데이터, 엄청나게 빠른 컴퓨팅 파워와 결합하고 있다. 이에 따라 인공지능이 인간과 같은 수준의 인지능력을 갖추게 되어 가까운 장래에 개인비서 기능뿐만 아니라 기업의 의사결정이나 고객관리를 비롯한 모든 비즈니스 부문에서 큰 역할을 할 것으로 기대된다. 해외의 주요 기술업체들은 AI를 핵심 R&D 분야로 삼고 각기 Application Programming Interface(APIs) 및 클라우드 서비스를 통한 인공지능 기술의 대중화에 힘쓰고 있으며, 개발자들은 이들 도구를 각자의 애플리케이션에 통합함으로써 수익기회를 창출하고 있다. 국내에서도 대기업 및 공공 R&D를 중심으로 인공지능 기술개발이 추진되고 있으나 관련 시장참여자 전체를 견인할 수 있는 기본 생태계 조성을 위한 정부의 지원이 필요한 상황이다. 본 연구는 인공지능 시장동향과 IBM 인공지능 생태계에 대해 개관하였으며, AI 산업체 의견을 반영한 국내 인공지능 산업 활성화 생태계 조성을 위한 제언으로 AI 플랫폼 지원, 인력문제 해결 그리고 공유의 장 마련이 필요하다는 점을 제시하였다.

• 한국벤처창업학회:학술대회논문집
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• 2019.11a
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• pp.153-155
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• 2019

최근 국내 외를 불문하고 IT기술의 비약적인 발전에 따라 금융분야에서도 금융과 기술이 결합된 새로운 형태의 금융서비스가 다양하게 개발되고 있다. 그러나, 개인금융시장의 비약적 발전에도 불구하고, 기업금융시장에서의 핀테크 활용은 아직까지 미미한 실정이다. 기업 신용평가는 재무제표 위주의 정태적(static) 과거 정보 위주로 이루어지고 있어 업력이 짧고 규모가 영세한 중소기업의 금융접근에 제약이 존재한다. 또한, 중소기업의 인력이 부족한 상황에서 모든 거래를 일일이 금융기관을 방문하여 처리해야 하는 불편함도 애로사항으로 파악되었다. 이러한 한계를 해소하기 위해 신용보증기금은 빅데이터 활용과 비대면 채널에 주목하였다. 본 보고서는 신용보증기금이 빅데이터와 비대면 채널을 활용하여 중소기업의 금융접근성을 향상시킨 사례에 대하여 소개하고자 한다. 첫 번째로, 신보는 기존에 활용되지 못한 동태적(dynamic) 빅데이터를 활용하여 기업의 현재 새로운 신용평가모형을 개발하였다. 두 번째로, 신보는 중소기업의 금융거래 편의성 향상을 위해 비대면 금융업무 플랫폼을 도입하였다. 신보는 이를, 데이터 수집이 체계적이고 정교해야 하며, 중소기업 관련 데이터가 공유되어야 한다는 정책적 시사점을 발견하였다. 이러한 정책적 시사점을 바탕으로 신보는 이제 기업 데이터 뱅크(Data Bank)로서의 역할을 도모하고 있으며, 더 나은 기업정보 생태계를 구현하고자 한다. 이를 통해 신보의 신기술을 활용한 중소기업 금융접근성 제고 사례가 핀테크를 활용한 공공기관의 금융정책 수립에 유용한 사례가 될 수 있을 것으로 기대한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.433-434
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• 2014

Big Data services is composed of Big Data user, Big Data service provider, and Big Data application provider. And it is possible to extend the service to interplay-reciprocal actions among three subjects such as providing, being provided, connecting, being connected, and so on. In this paper, we propose an ecosystems of Big Data and a framework of its service.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.103-106
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• 2020

• The Journal of Bigdata
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• v.3 no.1
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• pp.73-82
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• 2018

At the core of future medicine is the realization of Precision Medicine centered on individuals. For this, we need to have an open ecosystem that can view, manage and distribute healthcare data anytime, anywhere. However, since healthcare data deals with sensitive personal information, a significant level of reliability and security are required at the same time. In order to solve this problem, the healthcare industry is paying attention to the blockchain technology. Unlike the existing information communication infrastructure, which stores and manages transaction information in a central server, the block chain technology is a distributed operating network in which a data is distributed and managed by all users participating in the network. In this study, we not only discuss the technical and legal aspects necessary for demonstration of healthcare data distribution using blockchain technology but also introduce KOREN SDI Network-based Healthcare Big Data Distribution Demonstration Study. In addition, we discuss policy strategies for activating blockchain technology in healthcare.

• Journal of Fashion Business
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• v.27 no.1
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• pp.1-15
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• 2023

This study divided articles into two time periods, from 2012 to 2022, with the aim of using big data analysis to look at patterns in the ecosystem of fashion start-ups. The research method extracted top keywords based on TF(Term Frequency) and TF-IDF(Term Frequency-Inverse Document Frequency), analyzed the network, and derived centrality values. As a result of comparing the first and second fashion startup ecosystems, elements of policy, support, market, finance, and human capital were derived in the first period. In addition, in the second period, elements of policy, support, market, finance, and culture were derived. In the first period, the fashion startup ecosystem focused on fostering new designer startups by emphasizing support, finance, and human capital factors and focusing on policies. Meanwhile, in the second period, online-based fashion platform startups and fashion tech startups appeared with the support of digital transformation and fulfillment services triggered by COVID-19(Corona Virus Disease 19), private finances were emphasized, and cultural factors were derived along with success stories of fashion startups. This study is meaningful in that it helps in developing strategies for fashion startups to grow into sustainable companies.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.143-153
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• 2013

Big data is expected to bring forth enormous public good as well as economic opportunity. However there is ongoing concern about privacy not only from public authorities but also from private enterprises. Big data is suspected to aggravate the existing privacy battle ground by introducing new types of privacy risks such as privacy risk of behavioral pattern. On the other hand, big data is asserted to become a new way to by-pass tradition behavioral tracking such as cookies, DPIs, finger printing${\cdots}$ and etc. For it is not based on a targeted person. This paper is to find out if big data could contribute to catching out behavioral patterns of consumers without threatening or damaging their privacy. The difference between traditional behavioral tracking and big data analysis from the perspective of privacy will be discerned.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.31-36
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• 2018

The tourism industry has a great influence on national economy activation. The development of IT technology has enabled the collection and analysis of personal profile information, location information and activity information based on the characteristics, behavior, purchase propensity and interest of tourists. In order to realize this, the implementation of convergence smart tourism information service platform is completed by developing business model, IoT & Big Data integration management system, big data algorithm development and analysis platform in three stages. The underlying technology of the platform and algorithm needs a process of adopting open source, expanding the service element on the basis of it, and then complementing the problem through the test-bed demonstration test that connects the area. Using this platform, it is possible to develop a smart tourism environment that can provide customized services for each tourist by analyzing various information in an integrated manner. Also, it will be possible to improve the life of tourist destination residents and contribute to regional revitalization and job creation through the creation of smart tourism ecosystem focused on the region.

• The Journal of Bigdata
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• v.5 no.2
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• pp.121-133
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• 2020

This study was carried out to set the direction of the new industry policy of Busan city by analyzing the changing trend of artificial intelligence technology that has recently developed rapidly and predicting the direction of future development. The company wanted to draw up support measures to utilize artificial intelligence technology, which has been rapidly emerging in the market, in the region's specialized industry. Artificial intelligence is a key keyword in the fourth industrial revolution and artificial intelligence-based data utilization technology can be used in various fields from manufacturing processes to services, and is entering an era of super-fusion in which barriers between technologies and industries will be broken down. In this study, the direction of promotion for fostering Busan as an artificial intelligence city was derived based on the comparison and analysis of artificial intelligence-related ecosystems among major local governments. In this study, we wanted to present a plan to create an artificial intelligence industrial ecosystem that can be called a key policy to foster Busan as an 'AI City'. Busan's plan to foster the AI industry ecosystem is aimed at establishing a policy direction to ultimately nurture the artificial intelligence industry as Busan's future food source.