• Title/Summary/Keyword: 공간 빅 데이터

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Utilizing Spatial Big Data for Land and Housing Sector (토지주택분야 정보 현황과 빅데이터 연계활용 방안)

  • Jeong, Yeun-Woo;Yu, Jong-Hun
    • Land and Housing Review
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    • v.7 no.1
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    • pp.19-29
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    • 2016
  • This study proposes the big data policy and case studies in Korea and the application of land and housing of spatial big data to excavate the future business and to propose the spatial big data based application for the government policy in advance. As a result, at first, the policy and cases of big data in Korea were evaluated. Centered on the Government 3.0 Committee, the information from each department of government is being established with the big-data-based system, and the Ministry of Land, Infrastructure, and Transport is establishing the spatial big data system from 2013 to support application of big data through the platform of national spatial information and job creation. Second, based on the information system established and administrated by LH, the status of national territory information and the application of land and housing were evaluated. First of all, the information system is categorized mainly into the support of public ministration, statistical view, real estate information, on-line petition, and national policy support, and as a basic direction of major application, the national territory information (DB), demand of application (scope of work), and profit creation (business model) were regarded. After the settings of such basic direction, as a result of evaluating an approach in terms of work scope and work procedure, the four application fields were extracted: selection of candidate land for regional development business, administration and operation of rental house, settings of priority for land preservation, and settings of priority for urban generation. Third, to implement the application system of spatial big data in the four fields extracted, the required data and application and analytic procedures for each application field were proposed, and to implement the application solution of spatial big data, the improvement and future direction of evaluation required from LH were proposed.

Development and Application of Dynamic Visualization Model for Spatial Big Data (공간 빅데이터를 위한 동태적 시각화 모형의 개발과 적용)

  • KIM, Dong-han;KIM, David
    • Journal of the Korean Association of Geographic Information Studies
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    • v.21 no.1
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    • pp.57-70
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    • 2018
  • The advancement and the spread of information and communication technology (ICT) changes the way we live and act. Computer and ICT devices become smaller and invisible, and they are now virtually everywhere in the world. Many socio-economic activities are now subject to the use of computer and ICT devices although we don't really recognize it. Various socio economic activities supported by digital devices leave digital records, and a myriad of these records becomes what we call'big data'. Big data differ from conventional data we have collected and managed in that it holds more detailed information of socio-economic activities. Thus, they offer not only new insight for our society and but also new opportunity for policy analysis. However, the use of big data requires development of new methods and tools as well as consideration of institutional issues such as privacy. The goals of this research are twofold. Firstly, it aims to understand the opportunities and challenges of using big data for planning support. Big data indeed is a big sum of microscopic and dynamic data, and this challenges conventional analytical methods and planning support tools. Secondly, it seeks to suggest ways of visualizing such spatial big data for planning support. In this regards, this study attempts to develop a dynamic visualization model and conducts an experimental case study with mobile phone big data for the Jeju island. Since the off-the-shelf commercial software for the analysis of spatial big data is not yet commonly available, the roles of open source software and computer programming are important. This research presents a pilot model of dynamic visualization for spatial big data, as well as results from them. Then, the study concludes with future studies and implications to promote the use of spatial big data in urban planning field.

Resident Friendly River Management : Using the DT Technology (주민 친화적 하천관리 방향 : DT기술의 활용)

  • Lee, Sangeun;Lee, Jongso;Lee, Yookyung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.10-10
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    • 2020
  • 하천은 최근 주민에게 휴식과 레저의 기회를 제공하고 지역활기 창출의 자원으로 가치가 부상함에 따라 하천공간의 관리와 운영이 한층 더 중요해 졌다. 즉 하천공간의 개발과 보전은 지역의 문화관광과 복지 등의 지역 정책과 함께 하천이용의 수요를 고려하여 신중하게 운영해야 한다. 이에 본 연구에서는 하천공간의 체계적인 관리를 위해 통신 빅데이터를 활용하여 이용객 수를 추정하고 검증 한 뒤, 이용도 지표를 산정하였으며, 하천공간의 상세 유형화 방안을 마련하고 유형별 특성분석 등을 실시하고자 하였다. 현장표본조사를 통한 검증결과 통신 빅데이터는 하천공간에서의 이용객 수 추정에 활용 가능성을 보였으며, 이용도 지표 산정결과를 통해 친구지구를 이용객들이 어떻게 활용하는지 판단할 수 있었다. 또한 상세 유형화 방안을 마련하고 적용한 결과 이용객들이 하천공간을 근린의 성격과 거점의 성격으로 이용하고 있는지 판단할 수 있었다. 본 연구의 결과를 종합할 때, 친수지구 조성 및 관리를 위한 자료 활용방안을 제시할 수 있었으며, 국가하천 점용허가 시 통신 빅데이터 활용방안을 마련할 수 있었다. 통신 빅데이터는 친수지구 이용도 조사에 크게 유용한 방법을 제공하며, 하천계획, 유지·보수 등 관련 실무활용 및 정책수립에 큰 도움이 될 것으로 판단된다.

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빅데이터를 활용한 라이프케어 동향

  • Son, Jae-Gi;Sin, Sun-Ae;Han, Tae-Hwa
    • Information and Communications Magazine
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    • v.32 no.11
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    • pp.3-7
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    • 2015
  • 최근 활발히 연구되고 있는 빅데이터와 의료 영역이 융합되면서, 보건의료서비스 분야에서는 데이터 집약적이고 공간을 초월한 새로운 서비스패러다임의 움직임이 진행되고 있다. 본고에서는 이러한 빅데이터를 활용하여 건강증진 및 예방을 위하여 생활 속에서 제공되고 있는 생활환경 및 보건 데이터 기반의 라이프케어 서비스동향과 기술에 관하여 알아본다.

Development of the Guidelines for Expressing Big Data Visualization (공간빅데이터 시각화 가이드라인 연구)

  • Kim, So-Yeon;An, Se-Yun;Ju, Hannah
    • The Journal of the Korea Contents Association
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    • v.21 no.2
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    • pp.100-112
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    • 2021
  • With the recent growth of the big data technology market, interest in visualization technology has steadily increased over the past few years. Data visualization is currently used in a wide range of disciplines such as information science, computer science, human-computer interaction, statistics, data mining, cartography, and journalism, each with a slightly different meaning. Big data visualization in smart cities that require multidisciplinary research enables an objective and scientific approach to developing user-centered smart city services and related policies. In particular, spatial-based data visualization enables efficient collaboration of various stakeholders through visualization data in the process of establishing city policy. In this paper, a user-centered spatial big data visualization expression request method was derived by examining the spatial-based big data visualization expression process and principle from the viewpoint of effective information delivery, not just a visualization tool.

Design of Spatial Data Platform on Big Data (빅데이터 기반 공간정보 플랫폼 설계)

  • Lee, Sangwon;Kim, Jung Hee
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.05a
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    • pp.800-802
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    • 2016
  • In these days, the profitability of cadastral survey for national spatial information is getting worse. In order to reinforce the structure of the profitability, there exists the necessity to launch new and various businesses except the cadastral survey. In manipulating national spatial data effectively, it is necessary to design a platform for spatial information. Against this backdrop, we propose a platform for spatial data on the basis of Big Data in this paper.

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Business Innovation Through Spatial Data Analysis: A Multi-Case Analysis (공간 데이터 분석 기반의 비즈니스의 혁신: 해외 사례 분석을 중심으로)

  • Ham, YuKun
    • The Journal of Bigdata
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    • v.4 no.1
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    • pp.83-97
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    • 2019
  • With sensor and communication technology development, spatial data related to business activities is exploding. Spatial data is now evolving into atypical data about space over three dimensions, away from two-dimensional geographic data. In addition to the Fourth Industrial Revolution, which connects the virtual space with the real space, there is a great opportunity for companies to utilize it. The analysis of recent overseas cases shows that it is possible to analyze customized services by understanding the situation of customers and objects located in the space, to manage risk, and furthermore to innovate business processes by analyzing spatial data. In the future, business innovation that combines spatial data from various sources and real-time analysis of relationships and situations between people and objects in space is expected to expand in all business fields.

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A Method to Process Spatial Information in Parallel Spatial DBMS (병렬 공간데이터베이스 시스템에서 공간 정보 처리 방안)

  • Kim, JinDeog
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.05a
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    • pp.811-812
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    • 2016
  • 최근 공간 정보는 생산 되는 양과 데이터의 생성 빈도 및 다양성으로 인해 기존의 공간 데이터베이스 시스템에서 처리하기 어렵다. 그래서 공간 정보는 빅데이터와 연계에 관한 시도가 활발히 진행되고 있다. 그러나 효율적인 단일할당, 다중할당 색인기반 공간 연산에 대한 연구는 거의 없다. 이 논문에서는 공간 연산 중 비용이 매우 큰 공간 조인을 빅데이터 시스템에서 처리하기 위한 고려요소를 제시하고자 한다. 구체적으로 맵리듀스 시스템의 태스크 할당을 위한 단일 할당 공간 색인방안을 설명하고, 불균일 분포가 심한 공간 정보의 특성을 고려한 부하 균등화 시 고려 요소를 제시하고자 한다. 맵리듀스와 같은 병렬 공간 데이터베이스 시스템에서의 두 가지 문제인 데이터 불균일 분포 문제와 경계 겹침 색인의 문제와의 연관성을 기술한다.

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A Study on the Ferry Sewol Disaster Cause and Marine Disaster Prevention Informatization with Big Data : In terms of ICT Administrative Spatial Informatization and Maritime Disaster Prevention System development (세월호사고원인과 빅데이터 해양방재정보화연구 -ICT행정공간정보화와 해양방재시스템개발 측면에서-)

  • Lee, Sang-Yun;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.6
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    • pp.567-580
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    • 2016
  • In recent years, our society, because of the arrival of a new paradigm according to the rapid changes in ICT has entered into future smart society and the ubiquitous era. So it can be a notable turning point in the marine disaster prevention system with big data, aspects of the era change. Therefore, this study was to derive a desirable vision for the big data marine disaster prevention informatization in terms of ICT maritime disaster prevention system development as preparedness for the maritime disaster by applying 'scenario planning' as a foresight method. Soon this study derived a successful marine disaster prevention informatization strategy as preparedness for the maritime disaster like Ferry Sewol Disaster. It proposed the big data marine disaster prevention informatization system with the use of the administrative aspects of information with spatial informatization as big data information. Also this study explored the future leadership strategy of the big data marine disaster prevention informatization in smart society. Eventually in 2030 to around, In order to still remain our marine disaster prevention informatization as a leading ICT nation, this study suggested the following strategy. It is important to ready the advanced Big Data administrative spatial informatization system In terms of prevention of incidents like Ferry Sewol Disaster.

A study on trends and predictions through analysis of linkage analysis based on big data between autonomous driving and spatial information (자율주행과 공간정보의 빅데이터 기반 연계성 분석을 통한 동향 및 예측에 관한 연구)

  • Cho, Kuk;Lee, Jong-Min;Kim, Jong Seo;Min, Guy Sik
    • Journal of Cadastre & Land InformatiX
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    • v.50 no.2
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    • pp.101-115
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    • 2020
  • In this paper, big data analysis method was used to find out global trends in autonomous driving and to derive activate spatial information services. The applied big data was used in conjunction with news articles and patent document in order to analysis trend in news article and patents document data in spatial information. In this paper, big data was created and key words were extracted by using LDA (Latent Dirichlet Allocation) based on the topic model in major news on autonomous driving. In addition, Analysis of spatial information and connectivity, global technology trend analysis, and trend analysis and prediction in the spatial information field were conducted by using WordNet applied based on key words of patent information. This paper was proposed a big data analysis method for predicting a trend and future through the analysis of the connection between the autonomous driving field and spatial information. In future, as a global trend of spatial information in autonomous driving, platform alliances, business partnerships, mergers and acquisitions, joint venture establishment, standardization and technology development were derived through big data analysis.