• 정보관리학회지
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• 제35권2호
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• pp.141-165
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• 2018

본 연구의 목적은 연구데이터 관리서비스 구현 시 성공적인 서비스를 위한 고려사항을 도출하는 것이다. 이를 위해 선행연구를 활용하여 연구데이터 관리서비스의 영역을 파악하였고, 미국, 독일, 호주에서 연구데이터 관리서비스를 시행중인 대학도서관 6곳과 1개의 기관에서 담당자 8명을 대상으로 연구데이터 서비스에 관한 질문의 답변을 이메일을 통해 수집하였다. 또 해외서비스를 대상으로 수집한 고려사항이 국내에 적용가능한지 국내 연구데이터 관리서비스 전문가와 검토하였다. 연구데이터 서비스 영역은 총 9개의 카테고리로 구분하여 분석하였는데, 연구서비스와 연구데이터 관리서비스 연계, 국가/대학/기관 차원의 협약, 메타데이터 입력주체 및 필수 요소, 직원의 전문화 방안, 이용자 요구분석을 통한 주요서비스 영역 선정, 연구데이터와 연구결과물의 효과적인 연결방안, 이용자와 유관기관과 긴밀한 공조 등의 연구데이터 관리서비스 구축 시 고려사항을 도출할 수 있었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 A
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• pp.238-240
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• 2002

This paper proposes an advanced digital kwh-meter, which records voltage management data, load management data as well as the existing kwh data. This meter supports the requests from DRMS (Distribution Remote Management System) which include kwh meter reading, voltage management data reading, and load management data reading request, it can enhance greatly the economics of the existing remote meter reading system. Also it can improve highly the quality of power supplied to the electric customer by minimizing the voltage management cost and by enhancing the efficiency of load management.

• 보건의료산업학회지
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• 제12권4호
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• pp.203-217
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• 2018

Objectives : This study aimed to investigate the clinical practice ability and satisfaction of clinical training of health-medical information management major students. Methods : The data were collected from 68 persons from students finished clinical training at medical record (information) team using self administered questionnaires. The data were analyzed using t-test, ANOVA and correlation with SPSS 22.0 version. Results: Performance of data collection, data management, and data analysis were analyzed in three areas of the job area. In terms of academic characteristics and correlation, they were not related to the level of satisfaction with the practical experience. Conclusions : Research on a virtuous cycle clinical practice program that analyzes the factors by assessing the satisfaction level of clinical practice in each area of health care information management will be conducted continuously.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2008년도 정기학술발표대회 논문집
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• pp.329-333
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• 2008

최근 건설공사가 대형화 및 복잡화됨에 따라 건설현장에서의 진행관리 중요성은 점점 더 증대되고 있다. 현재 건설 프로젝트 현장에서는 데이터, 정보 기록 및 분석을 현장관리자가 직접 수작업으로 수행하고 있어 상당한 노력과 시간이 소비되고 있으며, 이는 생산성 저하 등 문제점을 있어 야기하고 있다. 이를 개선하기 위한 방안중의 하나로 첨단 DAT(Data Acquisition Technology) 기술 적용이 시도되고 있으며, 본 연구에서는 이러한 DAT의 포괄적 적용 가능성을 분석함으로써 효율적인 프로젝트 진행관리의 방안을 검토하고자 한다.

• 자원환경지질
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• 제56권6호
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• pp.887-897
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• 2023

스웨덴, 스위스, 영국 등 폐기물 처분 선도국들은 고준위방사성폐기물 심층처분시설의 계획, 부지선정, 건설, 운영, 폐쇄, 그리고 폐쇄 후 관리 전 단계에서 안전성평가를 수행하고 있다. 안전성평가는 각 단계에서 반복적으로 이루어지며, 장기간에 걸쳐 다양하고 방대한 양의 데이터를 생성하므로, 안전성평가 자료를 위한 데이터베이스를 구축하고 효과적으로 관리하기 위한 자료관리체계를 구축하는 것이 필수적이다. 본 연구에서는 폐기물 처분 분야에서 선도적인 국가의 안전성평가 자료관리체계를 1) 안전성평가 입력 및 참조자료, 2) 자료관리 지침, 3) 자료관리 조직, 그리고 4) 자료관리 전산시스템으로 구분하여 분석하였다. 각 국가는 특정 부분에서는 차이를 보였지만, 안전성평가 입력자료를 처분 시스템 구성 요소를 기반으로 분류하고, 이를 제공, 사용, 관리하는 조직을 설립하며, 지침 및 매뉴얼에 따라 품질관리 체계를 구현하는 등 공통적인 특성을 보이고 있다. 이러한 사례들은 고준위방사성폐기물 처분시설의 안전성을 확보하고 신뢰성을 향상시키기 위해 효과적으로 데이터 관리 시스템과 문서 관리 시스템을 구축하는 것이 중요하다는 것을 시사한다. 이를 위해서는 유연하게 활용 가능한 입력자료의 분류, 입력자료의 일관성과 추적성 보장, 그리고 입력자료와 문서관리를 위한 품질관리 체계를 수립하는 것이 필요하다.

• 전기학회논문지
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• 제63권8호
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• pp.1111-1115
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• 2014

With the increasing interest of a demand side management using a Smart Grid infrastructure, the demand resources and energy usage data management becomes an important factor in energy industry. In addition, with the help of Advanced Measuring Infrastructure(AMI), energy usage data becomes a Big Data System. Therefore, it becomes difficult to store and manage the demand resources big data using a traditional relational database management system. Furthermore, not many researches have been done to analyze the big energy data collected using AMI. In this paper, we are proposing a Hadoop based Big Data system to manage the demand resources energy data and we will also show how the demand side management systems can be used to improve energy efficiency.

• 인터넷정보학회논문지
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• 제19권1호
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• pp.123-130
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• 2018

With the emergence of a new paradigm called Open Science and Big Data, the need for data sharing and collaboration is also emerging in the computational science field. This paper, we analyzed data-driven research cases for computational science by field; material design, bioinformatics, high energy physics. We also studied the characteristics of the computational science data and the data management issues. To manage computational science data effectively it is required to have data quality management, increased data reliability, flexibility to support a variety of data types, and tools for analysis and linkage to the computing infrastructure. In addition, we analyzed trends of platform technology for efficient sharing and management of computational science data. The main contribution of this paper is to review the various computational science data repositories and related platform technologies to analyze the characteristics of computational science data and the problems of data management, and to present design considerations for building a future computational science data platform.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1994년도 DB산업기술 활성화를 위한 학술대회 및 기술 심포지움
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• pp.105-129
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• 1994

The information system of corporations are facing a new environment expressed by miniaturization, decentralization and Open System. It is therefore of utmost importance for corporations to adapt flexibly th such new environment by providing for corresponding changes to their existing information systems. The objectives of this study are to identify this new environment faced by today′s information system and develop effective methods for data resource management under this new environment. In this study, it is assumed that the new environment faced by information systems can be specified as Distributed Computing Environment, and in order to achieve such system, presents Client/server architecture as its representative computing structure, This study defines Client/server architecture as a computing architecture which specialize the fuctionality of the client system and the server system in order to have an application distribute and perform cooperative processing at the best platform. Furthermore, from among the five structures utilized in Client/server architecture for distribution and cooperative processing of application between server and client this study presents two different data management methods under the Client/server environment; one is "Remote Data Management Method" which uses file server or database server and. the other is "Distributed Data Management Method" using distributed database management system. The result of this study leads to the conclusion that in the client/server environment although distributed application is assumed, the data could become centralized (in the case of file server or database server) or decentralized (in the case of distributed database system) and the data management method through a distributed database system where complete responsibility and powers with respect to control of data used by the user are given not only is it more adaptable to modern flexible corporate environment, but in terms of system operation, it presents a more efficient data management alternative compared to existing data management methods in terms of cutting costs.

• Smart Structures and Systems
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• 제17권4호
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• pp.669-690
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• 2016

Advances in sensor technologies have led to the instrumentation of sensor networks for bridge monitoring and management. For a dense sensor network, enormous amount of sensor data are collected. The data need to be managed, processed, and interpreted. Data management issues are of prime importance for a bridge management system. This paper describes a data management infrastructure for bridge monitoring applications. Specifically, NoSQL database systems such as MongoDB and Apache Cassandra are employed to handle time-series data as well the unstructured bridge information model data. Standard XML-based modeling languages such as OpenBrIM and SensorML are adopted to manage semantically meaningful data and to support interoperability. Data interoperability and integration among different components of a bridge monitoring system that includes on-site computers, a central server, local computing platforms, and mobile devices are illustrated. The data management framework is demonstrated using the data collected from the wireless sensor network installed on the Telegraph Road Bridge, Monroe, MI.

• 전기학회논문지
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• 제65권3호
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• pp.469-476
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• 2016

Relational Database Management Systems have become de facto database model among most developers and users since the inception of Data Science. From IoT devices, sensors, social media and other sources, data is generated in structured, semi-structured and unstructured formats, in huge volumes, thereby the difficulty of data management greatly increases. Organizations that collect large amounts of data are increasingly turning to non relational databases - NoSQL databases. In this paper, through experiments with real field data, we demonstrate that MongoDB, a document-based NoSQL database, is a better alternative for building a Telco Subscriber Data Management System which hitherto is mainly built with Relational Database Management Systems. We compare the existing system in various phases of data flow with our proposed system powered by MongoDB. We show how various workloads at some phases of the existing system were either completely removed or significantly simplified on the new system. Based on experiment results, using MongoDB for managing telco subscriber data turned out to offer performance better than the existing system built with MSSQL Server.