• ETRI Journal
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• 제28권2호
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• pp.191-204
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• 2006

Many previous studies of data quality have focused on the realization and evaluation of both data value quality and data service quality. These studies revealed that poor data value quality and poor data service quality were caused by poor data structure. In this study we focus on metadata management, namely, data structure quality and introduce the data quality management maturity model as a preferred maturity model. We empirically show that data quality improves as data management matures.

• 정보관리학회지
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• 제40권1호
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• pp.51-71
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• 2023

본 연구는 공공데이터 품질관리 모델, 빅데이터 품질관리 모델, 그리고 연구데이터 관리를 위한 데이터 생애주기 모델을 분석하여 각 품질관리 모델에서 공통적으로 나타나는 구성 요인을 분석하였다. 품질관리 모델은 품질관리를 수행하는 객체인 대상 데이터의 특성에 따라 생애주기에 맞추어 혹은 PDCA 모델을 바탕으로 구축되고 제안되는데 공통적으로 계획, 수집 및 구축, 운영 및 활용, 보존 및 폐기의 구성요소가 포함된다. 이를 바탕으로 본 연구는 연구데이터를 대상으로 한 품질관리 프로세스 모델을 제안하였는데, 특히 연구데이터를 대상 데이터로 하여 서비스를 제공하는 연구데이터 서비스 플랫폼에서 데이터를 수집하여 서비스하는 일련의 과정에서 수행해야하는 품질관리에 대해 계획, 구축 및 운영, 활용단계로 나누어 논의하였다. 본 연구는 연구데이터 품질관리 수행 방안을 위한 지식 기반을 제공하는데 의의를 갖는다.

• 환경영향평가
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• 제7권1호
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• pp.81-91
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• 1998

The objective of this study was to use remotely sensed data, combined with in situ data, for the assessment of trophic state for Daecheong reservoir. Three Landsat TM(Thematic Mapper) imagery data were processed to portray trophic state conditions. The remotely sensed data and the measured data were obtained on 20 June 1995. Regression models have been developed between the chlorophyll-a concentration and reflectance which was converted to Landsat TM digital data. The regression model was determined based on the correlation coefficient which was higher than 0.7 and was applied to the entire study area to generate a distribution map of chlorophyll-a and trophic state. The equation, providing estimates of chlorophyll-a concentration, represented the year-to-year spatial variation of trophic zones in the reservoir. Satellite remote sensing data derived from Landsat TM had been successfully used for trophic slate mapping in Daecheong reservoir.

• 한국환경과학회지
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• 제17권12호
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• pp.1353-1361
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• 2008

Quality control of Argo(Array for Real-time Geostrophic Oceanography) data is crucial by reason that salinity measurements are liable to experience some drift and offset due to biofouling, contamination of sensor and wash-out of biocide. The automated Argo real-time quality control has a limit of sorting data quality, so that WJO program is adopted as standardized method of Argo delayed mode quality control (DMQc) in the world that is a precise quality control method. We conducted DMQC on pressure, temperature and salinity measured by Argo floats in the Pacific Ocean including expert evaluation. Particularly, salinity data were corrected using WJO program. 4 salinity profiles of Argo delayed mode were compared with nearby in situ CTD data and other Argo data in deep layer where oceanographic conditions are stable in time and space. The differences of both salinities were lower than target accuracy of Argo. As compared with the difference of salinities before DMQC, those after DMQC decreased by 60-80 percent. Quality of delayed mode salinity data seemed to be improved correcting salinity data suggested by WJO program.

• The Journal of Asian Finance, Economics and Business
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• 제9권8호
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• pp.29-36
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• 2022

The objective of this research is to find out the effect of innovative culture and quality of work life on competitive advantage strategy with the mediation of individual performance. This research is the continuance of previous research conducted by Adya Hermawati with an originality aspect emphasizing a concept comprising innovative culture, quality of work life, and individual performance as factors that control competitive advantage strategy. The research subject is Tourism Industry SMEs. Explanatory research is a research method used in this study, by surveying respondents. The data sources in this research are primary and secondary. Primary data is collected from respondents directly through a questionnaire whereas secondary data are obtained from references that are relevant to research problems. In conformity with this explanation, the type of research data is quantitative data. The results of this research show that: innovative culture has an effect on individual performance, quality of work life affects individual performance, innovative culture has an effect on competitive advantage, quality of work life affects competitive advantage, individual performance has an effect on competitive advantage, innovative culture affects competitive advantage with the mediation of individual performance, and quality of work life affects competitive advantage with the mediation of individual performance.

• 한국물환경학회지
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• 제21권6호
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• pp.651-658
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• 2005

The Non-parametric Analysis is powerful in data test especially for the non- normality water quality data. The data at three monitoring stations of the Tam-Jin River were evaluated for their normality using Skewness, Q-Q plot and Shapiro-Willks tests. Various constituent of water quality data including temperature, pH, DO, SS, BOD, COD, TN and TP in the period of January 1994 to December 2004 were used as dataset. Shapiro-Willks normality test was carried out for a test 5% significance level. Most water quality data except DO at monitoring stations 1 and 2 showed that data does not normally distributed. It is indicating that non-parametric method must be used for a water quality data. Therefore, a homogeneity was conducted by Mann-Whitney U test (p<0.05). Two stations were paired in three pairs of such stations. Differences between stations 1, 2 and stations 1, 3 for pH, BOD, COD, TN and TP were meaningful, but Tam-Jin 2 and 3 stations did not meaningful. In addition, a narrow gap of the water quality ranges is not a difference. Categories in which all three pairs of stations (1 and 2, 2 and 3, 1 and 3) in the Tam-Jin River showed difference in water quality were analyzed on TN and TP. The results of in this research suggest a right analysis in the homogeneity test of water quality data and a reasonable management of pollutant sources.

• 한국빅데이터학회지
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• 제2권2호
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• pp.87-93
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• 2017

데이터 품질에 대한 연구는 오랜 기간 동안 수행되어 왔다. 하지만 이러한 데이터 품질관리 연구는 구조적 데이터를 대상으로 하였다. 최근에 디지털혁명 또는 4차산업혁명이 일어나면서 빅데이터에 대한 품질관리가 중요해 지고 있다. 본 논문에서는 기존 논문을 분석하여 빅데이터 품질 유형을 분류하고 비교 분석하였다. 요약하면, 빅데이터 품질 유형은 빅데이터 값, 빅데이터 구조, 빅데이터 품질 프로세스, 빅데이터 가치사슬 단계, 빅데이터 모형 성숙도 등으로 분류할 수 있다. 이러한 비교 연구를 바탕으로 본 논문에서는 새로운 기준을 제시하고자 한다.

• Agribusiness and Information Management
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• 제3권1호
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• pp.11-22
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• 2011

This study describes the development of a web-based system that collects all data generated in the research conducted to set pre-harvest residue limits (PHRLs) for agricultural product safety control. These data, including concentrations of pesticide residues, limit of detection, limit of quantitation, recoveries, weather charts, and growth rates, are incorporated into a database, a regression analysis of the data is performed using statistical techniques, and the PHRL for an agricultural product is automatically computed. The development and establishment of this system increased the efficiency and improved the reliability of the research in this area by standardizing the data and maintaining its accuracy without temporal or spatial limitations. The system permits automatic computation of the PHRL and a quick review of the goodness of fit of the regression model. By building and analyzing a database, it also allows data accumulated over the last 10 years to be utilized.

• Journal of the Korean Data and Information Science Society
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• 제16권4호
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• pp.781-790
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• 2005

Nowaday, statistical data with coherence, accuracy and timeliness are necessary to government, company and research center for decision making or research. In other words, the importance of statistical data quality is steadily increasing. Thus, in this paper, we suggest necessity of measuring customer satisfaction with NSO products for enhancing quality. And we construct measurement scale for measuring customer satisfaction based on the statistical quality indicators. Also we advise use of structural equation model in relation analysis for statistic quality elevation.

• 한국태양에너지학회 논문집
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• 제25권3호
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• pp.11-18
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• 2005

The Korea Institute of Energy Research(KIER) has begun collecting horizontal global insolation data since May, 1982 at different locations. Because of a poor reliability of existing data, KIER's new data will be extensively used by the solar system users as well as by research institutes. But the quality of solar insolation data is not always good. This reports on an attempt to identify systematic error in such data using clear-day analysis for data rehabilitation. Clear-day analysis is successful in uncovering solar insolation data of questionable quality. It is not proven that rehabilitation process can improve the quality of data for daily or monthly means, but it is suggested that the method can be used to improve the quality of data for monthly means of several years for use in many applications of solar energy planning. Earlier studies finding a maximum ETR of about 0.80 are confirmed.