• Journal of Korean Medicine for Obesity Research
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• v.17 no.1
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• pp.46-53
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• 2017

Health care big data is thought to be a promising field of interest for disease prediction, providing the basis of medical treatment and comparing effectiveness of different treatments. Korean government has begun an effort on releasing public health big data to improve the quality and safety of medical care and to provide information to health care professionals. By studying population based big data, interesting outcomes are expected in many aspects. To initiate research using health care big data, it is crucial to understand the characteristics of the data. In this review, we analyzed cases from inside and outside the country using clinical data registry. Based on successful cases, we suggest research method for evidence-based Korean medicine. This will provide better understanding about health care big data and necessity of Korean medicine data registry network.

• Journal of Research and Publication Ethics
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• v.2 no.2
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• pp.5-10
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• 2021

Purpose: Ethical behaviors become more salient when researchers utilize face-to-face interviews and observation with vulnerable groups or communities, which may be unable to express their emotions during the sessions. The present research aims to investigate ethical behaviors while conducting research have resonance due to the deep nature of observation and interview data collection methods. Research design, data and methodology: The present research obtained non-numeric (Textual) data based on prior literature review to investigate Ethical Conducts in Qualitative Research. Non-numeric data differs from numeric data in how the data is collected, analyzed and presented. It is important to formulate written questions and adopt them what the method claims for the researcher to understand the studied phenomenon. Results: Our findings show that while conducting qualitative research, researchers must adhere to the following ethical conducts; upholding informed consent, confidentiality and privacy, adhering to beneficence's principle, practicing honesty and integrity. Each ethical conduct is discoursed in detail to realize more information on how it impacts the researcher and research participants. Conclusions: The current authors concludes that five ethical conducts are important for realizing extensive and rich information during qualitative research and may be exploited in implementing research policies for researchers utilizing observation and interviews methods of data collection.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.1
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• pp.115-137
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• 2023

The purpose of this study is to present a guide for the development of research data management education programs for researchers affiliated with domestic universities and research institutions. In order to present the relevant program guide, first, we investigated and analyzed educational programs for overseas research data management. The educational programs studied and analyzed are RDMRose, RDMLA, DataONE, Digital Research Alliance of Canada, NNLM, PARTHENOS and Coursera. In addition, in order to confirm the appropriateness of the education program, it was reviewed through the detailed competency of data literacy researched in Korea. As a result of the review, most of the detailed competencies for data literacy were satisfied. Finally, a program guide for researchers was presented by synthesizing the research data management education programs that were investigated and analyzed. The results of this study will help develop research data management education programs that can systematically support and activate researchers belonging to universities and institutions.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.245-248
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• 2004

In this paper, we propose a framework for synchronization of spatial data between mobile devices and a server by using SyncML(Synchronization Markup Language) that is standard specification for synchronization protocol. We used GML (Geographic Markup Language) to support interoperability of spatial data between various data sources. We also used metadata and catalog service to access and integrate distributed spatial data, considering relationships of spatial data and non-spatial data.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.73-77
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• 2021

As the big data analysis technologies has been developed worldwide, the importance of asset management for electric power facilities based data analysis is increasing. It is essential to secure quality of data that will determine the performance of the RISK evaluation algorithm for asset management. To improve reliability of asset management, asset data must be preprocessed. In particular, the process of cleaning dirty data is required, and it is also urgent to develop an algorithm to reduce time and improve accuracy for data treatment. In this paper, the result of the development of an automatic cleaning algorithm specialized in overhead transmission asset data is presented. A data cleaning algorithm was developed to enable data clean by analyzing quality and overall pattern of raw data.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.638-643
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• 2002

MODIS (MODerate-resolution Imaging Spectroradiometer) onboard the first Earth Observing System (EOS) satellite, Terra, was launched successfully at the end of 1999. The direct broadcast MODIS data has been received and utilized in Korea Meteorological Administration (KMA) since february 2001. This study introduces utilizations of this data, especially for the derivation of sea surface temperature (SST). To produce the MODIS SST operationally, we used a simple cloud mask algorithm and MCSST algorithm. By using a simple cloud mask algorithm and by assumption of NOAA daily SST as a true SST, a new set of MCSST coefficients was derived. And we tried to analyze the current NASA's PFSST and new MCSST algorithms by using the collocated buoy observation data. Although the number of collocated data was limited, both algorithms are highly correlated with the buoy SST, but somewhat bigger bias and RMS difference than we expected. And PFSST uniformly underestimated the SST. Through more analyzing the archived and future-received data, we plan to derive better MCSST coefficients and apply to MODIS data of Aqua that is the second EOS satellite. To use the MODIS standard cloud mask algorithm to get better SST coefficients is going to be prepared.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.4
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• pp.355-378
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• 2015

In recent years, countries such as USA, United Kingdom and Australia have begun to implement national policies in order to systematically manage and share research data produced through publicly funded research. However, Korea as of yet does not have a coordinated research data policy. The lack of infrastructure that supports the sharing and preserving research data results in the poor management and loss of valuable data produced from significant national R&D investments. The need for research data collection, management and sharing goes beyond the outcome assessment of national research: it facilitates the diffusion of research impact and economic development. There is a growing recognition that data sharing is an essential element of research ethics. This research investigates the relevant research data policies and methods of governance at the national level using a case study analysis. United Kingdom was selected as a case study target as it shows a wide variety of policy examples and instruments. In particular, this research focuses on the UK's national legal framework for research data sharing, analyzes the RCUK (Research Councils UK)'s data policies, activities at the seven research councils under RCUK as well as several supporting institutions. Based on the analyses, this research offers a national roadmap for better managing and sharing of research data in Korea.

• Journal of Korean Society of Archives and Records Management
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• v.12 no.3
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• pp.93-115
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• 2012

This study aims to propose improvement plans of the Humanities and Social Sciences research data archives in Korea. For this purpose, literature reviews were conducted to prove the importance of the Humanities and Social Sciences research data and establish a theoretical basis for the concept and requirements of data archives. In addition, analysis of the Korean Research Memory (KRM), case surveys for a total of 9 domestic and international archives, and in-depth interviews with a total of 10 researchers in the field of the Humanities and Social Sciences were conducted as well. As for the improvement of the Humanities and Social Sciences research data archives in Korea, establishing a cooperative system between the National Research Foundation of Korea (NRF) and the field of the Humanities and Social Sciences was proposed first for data archives of each project. Secondly, a conceptual model of research data archives was designed in such a way that the archives would perform according to a life cycle of research data in the cooperative system, all based on data curation.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.79-84
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• 2021

The fundamental element to be kept for big data analysis, artificial intelligence technologies and asset management system is a data quality, which could directly affect the entire system reliability. For this reason, the momentum of data cleaning works is recently increased and data cleaning methods have been investigating around the world. In the field of electric power, however, asset data cleaning methods have not been fully determined therefore, automatic cleaning algorithm of asset data for transmission cables has been studied in this paper. Cleaning algorithm is composed of missing data treatment and outlier data one. Rule-based and expert opinion based cleaning methods are converged and utilized for these dirty data.

• Journal of the Korean Solar Energy Society
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• v.31 no.1
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• pp.51-58
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• 2011

The energy makes the basic element which improves the quality of life with motive power of industry and life. However, using the fossil fuel resources was restricted through it's abuse and exhaustion, and that cause a global warming resultingly. According to the reason, the world increased the interest that are stability and use of new and renewable energy which is clean energy with environment. Therefore, the property data of new and renewable is needed for developing and supplying the energy. In other words, the data of new and renewable energy becomes the standards for supply and evaluation of new and renewable energy with development of industry and technology. Also, the necessity came to the fore as the reference and standards of new and renewable energy data. Therefore, in this study, we evaluate and collect the solar radiation data as the new and renewable data and process the collected data through the standards for valuation. We evaluate uncertainty with standards which are NREL, WMO, and GUM. Whereby the data becomes reference standards data and gains the credibility. For the reliability data, we correct the measuring instrument with correction period. Using the DQMS and SERI QC, we efficiently manage and evaluate the solar radiation data. As a result, we evaluate uncertainty as 1,120 case about 16 area. we achieve credibility of data from evaluated solar radiation data and provide an accurate information to user. The annual average of horizontal radiation presents between 1,484 and 4,577, then the uncertainty evaluates from 163 to 453. The error of uncertainty presents smaller than the measurement values. So, we judge a credibility of data by expression of reliability quantitatively. In additional, the reference standards data which is possible to approach anywhere will be used for the supporting related industry and policy making.