• 한국CDE학회논문집
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• 제20권3호
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• pp.254-262
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• 2015

This study proposes an approach to Product Data Management (PDM) education for collaborative product data management, which can support collaborative product development process. This approach introduces social media and a PDM system into a framework for PDM education supported by consistent product development process and product data model. It has been applied to two PDM classes and the result shows that the social media in PDM education can support not only experiences of the collaborative product data management but also interactive and informal communications among instructors and participants using integrated social media with product data during courses.

• 한국빅데이터학회지
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• 제3권2호
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• pp.1-10
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• 2018

스마트 물관리 분야에서도 빅데이터 분석을 통해 경쟁력을 강화하려는 요구가 급증하면서 빅데이터에 대한 체계적인 관리(거버넌스)가 중요한 이슈로 부각되고 있다. 빅데이터 거버넌스는 데이터의 품질보장, 프라이버시 보호, 데이터 수명관리, 데이터 전담조직을 통한 데이터 소유 및 관리권의 명확화 등의 데이터 관리를 평가하고(Evaluation), 지시하며(Direction), 모니터링(Monitoring) 하는 체계적인 관리활동을 의미한다. 빅데이터 거버넌스가 확립되지 못하면 중요한 의사결정에 품질이 낮은 데이터를 사용함으로써 심각한 문제를 야기할 수 있으며, 개인 프라이버시 관련 데이터로 인해 빅브라더의 우려가 현실화될 수 있고, 폭증하는 데이터의 수명관리 소홀로 인해 IT 비용이 급증하기도 한다. 이러한 기술적인 문제가 완비되더라도 데이터 관련 문제를 전담하고 책임지는 조직과 인력이 없다면 빅데이터 효과는 지속되지 못할 것이다. 본 연구에서는 빅데이터 기반의 스마트 물관리를 위한 데이터 거버넌스 구축모델을 제시하고, 실제 물관리 업무에 적용한 사례를 소개한다.

• 한국IT서비스학회지
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• 제18권1호
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• pp.91-112
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• 2019

The IoT environment has led to explosive growth of existing enterprise data, and how to utilize such big data is becoming an important issue in the management field. In this paper, major factors affecting the decisions of companies to utilize big data have been studied. And also, the effect of big data utilization on the management quality is studied empirically. During this process, we have studied the difference according to the award of Korean national quality award. As a result of the study, we confirmed that the five factors such as cost from technology, organization and environment perspective, compatibility, company size, chief officer support, and competitor pressure are key factors influencing big data utilization. Also, it was confirmed that the use of big data for management activities has an important influence on the six management quality factors based on MBNQA, and that the management quality level of Korean national quality award companies is relatively high. This paper provides practical implications for companies' use of big data because it demonstrates for the first time that big data utilization has an impact on management quality improvement.

• 한국문헌정보학회지
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• 제47권3호
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• pp.251-274
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• 2013

본 연구는 미국, 영국, 캐나다, 호주의 15개 정부연구비지원기관에서 제공하는 데이터관리 정책을 분석하여 국내 데이터 정책 개발을 위한 참고사항을 제시하는 것을 목적으로 하였다. 데이터 정책의 내용 분석을 위해 선행연구를 바탕으로 1) 데이터의 정의, 2) 데이터관리 원칙, 3) 데이터관리 계획, 4) 데이터관리 실행, 5) 법적 윤리적 측면의 5가지 기준을 제시하였다. 분석결과 이러한 내용들을 모두 포함하고 있는 데이터정책은 존재하지 않았지만 다수의 기관들이 분석기준으로 제시된 내용들을 정책에서 공통적으로 다루고 있음을 확인할 수 있었다. 분석결과를 바탕으로 제시된 데이터 정책 개발을 위한 제언은 다음과 같다. 첫째, 연구비를 지원하는 학문 분야의 데이터 생성에 대한 이해를 바탕으로 데이터의 정의와 유형을 제시하여 관리대상을 명확히 한다. 둘째, 국내 연구데이터 관리에 적용할 수 있는 데이터관리 원칙을 수립하고 이를 정책에 제시한다. 셋째, 연구자들의 데이터관리에 대한 책임을 강화할 수 있는 데이터관리계획 도입을 검토한다. 넷째, 연구자들의 데이터 공유를 촉진하고 지원할 수 있는 데이터관리 실행 내용을 정책에 명시한다. 다섯째, 데이터 공유의 근거가 되는 법제도의 적용 및 개선방안을 검토하여 데이터 공유와 관련된 법적 윤리적 문제를 최소화하는 정책을 마련한다.

• Journal of Information Technology Applications and Management
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• 제10권4호
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• pp.103-118
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• 2003

This study presents a database quality evaluation framework. As a way to build a framework, this study expands data quality management to include data transformation processes as well as data. Further, an information structure graph is applied to represent data transformations processes. An information structure graph is absed on a relational database scheme. Thus, data transformation processes may be stored in a relational database. This kind of integration of data transformation metadata with technical metadata eases evaluation of database qualities and their causes.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.231-234
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• 2013

According to the recent development of USN technology, it has been applied in various fields of construction management. In particular, the concrete curing management using the wireless measurement system is actively being conducted. However, the existing method has limitations such as the reinstallation of temperature sensors and repositioning of repeaters. It is also not easy to acquire the measured data. Thus, this study focuses on the concrete curing management. This study proposes data acquisition method using the smartphone on construction site and tests applicability of the data measuring device and the smartphone. The test allows us to suggest the actual communication distance on construction site and to determine the correction value that is applied to the measured temperature. The data acquisition method proposed in this study is intended to enable appropriate management on construction site and will be able to be applied effectively to a variable construction site. It can also be used in all fields of construction management.

• 대한전기학회논문지:전력기술부문A
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• 제53권6호
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• pp.316-323
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• 2004

This paper develops an ADWHM(Advanced Digital Watt-Hour Meter) which integrates and implements the voltage management data record function and the load management data record function in the electronic watt-hour meter. ADWHM is developed based on PIC16F874 which is 8bit micro-controller of RISK type for the easy of programing and maintenance, and electronic power signal processing module is located at front of it to reduce the computing load of processor. Also, a 16kbyte EEPROM is used to record the voltage management data and load management data for a week as well as watt-hour data and USART communication mode is used to transfer data from ADWHM to PC. The accuracy of the voltage and unt measuring for ADWHM is verified by identifying the LCD display values of the ADWHM after the voltage signals of id levels from digital function generator is applied to PT(Potential Transformer) and CT(Current Transformer) output under state which it is separated from real power line. On the its basic functions such as watt-hour data recording function, voltage management data recording function and load management data recording function was verified by showing data for three days among the collected data to PC by RS232C communication from ADWHM which was connected to real power lines for a week.

• 디지털산업정보학회논문지
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• 제12권3호
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• pp.1-9
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• 2016

The current meaning of "Big Data" refers to all the techniques for value eduction and actionable analytics as well management tools. Particularly, with the advances of wireless sensor networks, they yield diverse patterns of digital records. The records are mostly semi-structured and unstructured data which are usually beyond of capabilities of the management tools. Such data are rapidly growing due to their complex data structures. The complex type effectively supports data exchangeability and heterogeneity and that is the main reason their volumes are getting bigger in the sensor networks. However, there are many errors and problems in applications because the managing solutions for the complex data model are rarely presented in current big data environments. To solve such problems and show our differentiation, we aim to provide the solution of actionable analytics and semantic reusability in the sensor web based streaming big data with new data structure, and to empower the competitiveness.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.433-436
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• 2008

A demand on the spatial data management has been rapidly increased with the introduction and diffusion process of ITS, Telematics, and Wireless Sensor Network, and many different people use the digital map that offers various thematic spatial data. Spatial data for digital map can manage to tile-based and feature-based data. The existing tile-based digital map management systems have difficult problems of data construction, history management, and updating based on a spatial object. In order to solve these problems, this paper proposed the data model for the feature-based digital map management system that is designed for feature-based seamless map, history management, real-time updating of spatial data, and analyzed the validity and utility of the proposed model.

• Journal of information and communication convergence engineering
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• 제7권2호
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• pp.199-202
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• 2009

Adaptive memory management is a serious issue in data stream management. Data stream differ from the traditional stored relational model in several aspect such as the stream arrives online, high volume in size, skewed data distributions. Data skew is a common property of massive data streams. We propose the predicted allocation strategy, which uses predictive processing to cope with time varying data skew. This processing includes memory usage estimation and indexing with timestamp. Our experimental study shows that the predictive strategy reduces both required memory space and latency time for skewed data over varying time.