• Proceedings of the Korean Nuclear Society Conference
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• 1998.10a
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• pp.89-89
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• 1998

• 한국지형공간정보학회:학술대회논문집
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• 2001.11a
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• pp.87-90
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• 2001

• Air Cleaning Technology
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• v.34 no.3
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• pp.17-27
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• 2021

• Journal of Korea Water Resources Association
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• v.45 no.1
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• pp.1-13
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• 2012

Various input data required for water quality modeling have considerable impacts on modeling results and relevant analysis due to the absence of data standardization and lack of data accuracy. With this in mind, this study mainly focused on the designing Korean Reach File for more effective water quality modeling through the supply of database composed with accurate hydraulic and hydrologic data. The Korean Reach File is the hydraulic database with the locational information of individual reaches, and each reach represents the stream reach of homogeneous hydraulic characteristics. In detail, it has reach code designating each stream reach, and topological information including catalog unit, segment, marker and index. It was also designed considering linkage of existing codes such as stream name and stream code. The devised reach code was implemented to Kyungan River at the City of Gwangju of Kyunggi Province and the results showed that the reach code could effectively support the input database integrating basic numerous data required for water quality modeling based on a criterion as well as easier linkage and utilization with existing database. In addition, more systematic water quality management was enabled through the linkage of existing data such as treatment facilities, pollutant data, and management institutes using the reach codes defined for each stream section. In the future, more efforts need to be made to adopt the reach code as the national standard data thereby enabling utilization of numerous relevant database through the assigning of reach code to individual stream reaches nationwide.

• 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.

• Journal of Korean Library and Information Science Society
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• v.43 no.2
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• pp.247-271
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• 2012

The institutional repository and linked data share a purpose, co-creation and joint usage of information resources. Therefore, a new approach linking these two concepts can be utilized for co-production and utilization of resources. This study hoped to configure the Korean dCollection repository as linked data. For this purpose, first, we analyzed the current data structure of dColleciton. Second, we investigated the resource types which dCollection is targeting. Third, we focused and analyzed a case study of resource types targeted by dCollection constructed as linked data. Fourth, this study examined in detail how to build the linked dCollection data and how to connect this linked data to the linked cloud. Finally, we discussed the problems that might oc cur in the process of building the linked data.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.23 no.2
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• pp.5-25
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• 2012

The purpose of this study is to develop linked data of authority data in national archives of Korea as a cornerstone for linked data cloud of Korea. The study analyzed data structure of authority data as well as a retrieval system. It finally developed linked data based on RDF/OWL, Dublin Core, and SKOS. The study also employed TopBraid ComposerTM as a tool for ontology construction. The visualization of the tool provides users with flexible search and browsing between data as well as access of detail authority data. It complements the search of a current system in terms of flexible linking between records and authority data. The study also suggests future work to publish linked data of archival data set itself and make rich relationships among data in museums, libraries, and other archives.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.6
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• pp.411-417
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• 2020

To utilize building information modeling (BIM) technology at the bridge maintenance stage, it is necessary to integrate large quantities of bridge inspection and model data for object-oriented information management. This research aims to establish the benefits of utilizing the extended industry foundation class (IFC)-BIM and ontology for bridge inspection information management. The IFC entities were extended to represent the bridge objects, and a method of generating the extended IFC-based information model was proposed. The bridge inspection ontology was also developed by extraction and classification of inspection concepts from the AASHTO standard. The classified concepts and their relationships were mapped to the ontology based on the semantic triples approach. Finally, the extended IFC-based BIM model was integrated with the ontology for bridge inspection data management. The effectiveness of the proposed framework for bridge inspection information management by integration of the extended IFC-BIM and ontology was tested and verified by extracting bridge inspection data via the SPARQL query.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.19-19
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• 2023

최근 기후변화에 의해 단기간에 많은 양의 집중호우가 발생하여 도시지역의 침수 피해가 증가하고 있다. 이에 도시지역의 홍수 피해 해결을 위해 도심지 홍수 발생 시 홍수정도 및 상황을 파악할 수 있는 장비가 개발되었으나, 실용화 단계까지는 진행이 미흡한 상황이다. 또한 기존 도시지역 홍수 현상 및 원인을 분석하기 위해 수치모형을 활용하고 있으나, 우수관망의 노후화 및 초기 강우패턴 적용에 대한 정확한 해석결과의 어려워 활용성이 낮다. 또한 홍수정도와 발생상황 인지를 위한 계측 장비의 개발 연구는 지속적으로 진행되고 있으나, 계측 장비의 높은 가격으로 전국적으로 설치 할 수 없는 상황으로 이를 대응하기 위한 별도의 방안 마련이 필요한 실정이다. 이를 위해 본 과제에서는 고성능·저비용 계측센서를 개발하여 실용화 가능성을 높이고, 전국에 산재되어있는 CCTV(교통상황, 방법용 등)의 영상을 활용한 침수상황 인지 기술 개발, 계측 데이터와 모니터링 데이터의 활용을 위한 빅데이터 개방 플랫폼을 구축하여, 상습 침수지역에 대해 실시간 감시가 가능한 계측 시스템의 정형 데이터와 CCTV 및 영상 등 모니터링 장비의 비정형 데이터의 분석 기술을 결합한 새로운 도심지 홍수 감시 기술의 개발을 목표로 한다. 이를 위해 본 연구 1차년도에 지표면 침수심 계측센서와 우수관망 월류심 계측센서를 개발하였으며, 2차년도에는개발된 계측센서의 현장실증을 통해 데이터를 수집한다. 수집된 계측센서 데이터와 비정형(CCTV 영상) 데이터의 AI학습을 통해 분석된 침수심, 침수범위, 침수면적 데이터는 도심지 홍수 정보 프로그램을 통해 표출되며, 최종적으로는 현장 상황을 쉽게 파악 가능한 3D 레이어의 형식으로 표출하고자 한다. 추후 도심지 홍수 정보 프로그램을 통해 표출되는 3D 레이어는 환경부가 추진하는 DT(Digital Twin) 연계 인공지능(AI) 홍수예보 사업과의 연계 시 도심지 홍수 지도 구축을 위한 자료로 활용될 수 있을 것으로 판단된다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.435-437
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• 2022

스마트 해상물류 통합 프로세스 설계 기술을 위한 데이터 처리 연구는 스마트 해상 물류 통합을 위한 메시지 관리 패턴 정의로 해운-항만-내륙물류의 다양한 서비스와의 연계 데이터 관리 패턴 설계, 디지털 문서의 수용 및 데이터 교환을 위한 상호운용성 보완 기술 설계 그리고 프로세스 기반 거래검증 알고리즘에 대한 연구 내용이다.