• Title/Summary/Keyword: research data management

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Developing a Web-based System for Computing Pre-Harvest Residue Limits (PHRLs)

  • Chang, Han Sub;Bae, Hey Ree;Son, Young Bae;Song, In Ho;Lee, Cheol Ho;Choi, Nam Geun;Cho, Kyoung Kyu;Lee, Young Gu
    • Agribusiness and Information Management
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    • v.3 no.1
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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.

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AUTOMATED PROGRESS MEASUREHEMT FOR CONTRUCTION PROJECT

  • Seunghee Kang;Youngsoo Jung
    • International conference on construction engineering and project management
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    • 2009.05a
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    • pp.1068-1074
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    • 2009
  • The progress is widely used as a critical index for successful construction project management. In spite of the importance of progress measurement, the excessive management effort to collect and maintain detailed data has been highlighted as a major barrier to measurement of highly accurate progress. In order to reduce the required workload and to enhance accuracy, several researches have been conducted. These researches can be categorized into two groups. First group focuses on automated data collection utilizing advanced technologies only for limited construction tasks. The second group is a research area where the standard progress measurement methodologies encompassing entire construction tasks are investigated. Topics include the adjusting the level of details, standardizing work processes, and applying flexible WBS. However, the techniques for automated data collection are not fully investigated yet in the second group. Combining these two research areas can provide a solution for more effective progress management in terms of enhancing accuracy and optimizing workload. However, there has been no comprehensive research addressing these two research groups in an integrated manner. In this context, the purpose of this paper is to propose a methodology that identifies the most suitable measurement method and data acquisition technology (e.g., GPS, RFID, etc.) for entire construction tasks of a project. The proposed methodology in this paper will be able to facilitate the selection process of data acquisition technologies for entire construction tasks of a project and to support the overall enhancement of automated progress management.

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A Study on the Construction of RDM in an Organization Using Big Data and Block Chain (빅데이터와 블록체인을 활용한 조직내 RDM 구축방안)

  • Lee, Kyung-Hee;Choi, Youngjin;Cho, Wan-Sup
    • The Journal of Bigdata
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    • v.4 no.2
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    • pp.127-139
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    • 2019
  • Research Data Management (RDM) is a system that encompasses people, policies, resources and technologies that provide and support directions in producing, collecting, using, and preserving research data. RDMs consist of a wide range of activities, including supporting the creation of data management plans (DMPs), building data collections and repositories, and digital preservation and distribution. In advanced countries, systems for RDMs and related organizations are well organized and functioning, but in Korea, the management system is insufficient due to low level of data awareness. In this paper, we propose a plan to establish a research data management system suitable for the reality. In particular, it is important to reflect in RDM that the construction of big data platforms for the collection and management of big data in each field and organization is increasing rapidly. Also, we will discuss how to provide data provision and researchers' data sovereignty using blockchain technology, and propose a P2P-based decentralized RDM scheme.

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Assessment of Needs and Accessibility Towards Health Insurance Claims Data (연구를 위한 건강보험 청구자료 요구 및 이용 요인분석)

  • Lee, Jung-A;Oh, Ju-Hwan;Moon, Sang-Jun;Lim, Jun-Tae;Lee, Jin-Seok;Lee, Jin-Yong;Kim, Yoon
    • Health Policy and Management
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    • v.21 no.1
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    • pp.77-92
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    • 2011
  • Objectives : This study examined the health policy researchers' needs and their accessibility towards health insurance claim datasets according to their academic capacity. Methods : An online questionnaire to capture relevant proxy variables for academic needs, accessibility, and research capacity was constructed based on previous studies. The survey was delivered to active health policy researchers through three major scholarly associations in South Korea. Seven-hundred and one scholars responded while the survey as open for 12 days (starting on December 20th, 2010). Descriptive statistics and logistic regression analysis were carried out. Results : Regardless of the definition for operational needs, the prevalent needs of survey respondents were not met with the current provision of claim data. Greater research capacity was shown to be correlated with increased demand for claim data along with a positive correlation between attempts to obtain claim datasets and research capacity. A greater research capacity, however, was not necessarily correlated with better accessibility to the claim data. Conclusions : The substantial unmet need for claim data among the healthcare policy research community calls for establishing proactive institutions which could systematically prepare and make available public datasets and provide call-in services to facilitate proper handling of data.

A Study on the Development of Research Data Management Service in a Domestic University Library: Focused on the Analysis on the Needs of Researchers Affiliated in Seoul National University (국내 대학도서관의 연구데이터관리서비스 개발 방안에 관한 연구: 서울대학교 소속 연구자들의 요구 분석을 중심으로)

  • Shim, Yunhee;Kim, Jihyun
    • Journal of the Korean Society for information Management
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    • v.36 no.3
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    • pp.61-80
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    • 2019
  • This study aimed to develop Research Data Management (RDM) Services in a domestic university library of Korea. In this study, elements and levels of RDM services are examined and in-depth interview was conducted with university researchers affiliated in Seoul National University, which has the largest amount of research fund among universities in Korea. Interview was conducted to analyze their data management practices and needs of RDM services. Interview results show researchers' lack of awareness toward Data Management Policy and data sharing obligations of funding agencies and academic journal publishers. Also, they had trouble managing research data systematically. However, many of the researchers understand the necessary of research data management and education of data management. Based on the interview result, service elements and contents are suggested for RDM services which is consisted of education services, professional consulting services, curation technical services. This study result will help to guide for the planning the future RDM service in university library of Korea.

Strategy to Improve the Management Efficiency of Meta Data Mining System (메타데이터 마이닝 시스템의 관리효율성의 제고전략)

  • Yun, Yong-Un
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.05a
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    • pp.276-279
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    • 2005
  • Many large organizations that have allocated resources to Data Administration(DA) have DA-context meta data mining. Also meta data is an interesting topic in the data warehouse world. This conceptual view gradually cleared up, and recently we have been talking more confidently about the back-room and front-room meta data. We describe the processes and problems that characterize the general architecture of s meta data mining system to do improve management efficiency that require further research and development.

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Web-based Knowledge Management Model for Mid-Term and Long- Term Nuclear R&D Using Web Knowledge DataBase (웹 지식 데이터베이스를 활용한 원자력 중장기 연구개발 웹 기반 지식관리 모델)

  • 정관성;한도희
    • The Journal of Society for e-Business Studies
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    • v.5 no.2
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    • pp.143-150
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    • 2000
  • This paper presents a methodology how to utilize management of research scheduling plan, processing, and results using Web Knowledge Database System, which integrates research knowledge management model under the Research & Development Environment. The content of this paper consists of description on utilization of the Web Knowledge Database System, sharing of the Research Knowledge through design data review, communications, and management of research knowledge flow during the Research & Development Period.

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FEATURE-BASED SPATIAL DATA MODELING FOR SEAMLESS MAP, HISTORY MANAGEMENT AND REAL-TIME UPDATING

  • Kim, Hyeong-Soo;Kim, Sang-Yeob;Seo, Sung-Bo;Kim, Hi-Seok;Ryu, Keun-Ho
    • Proceedings of the KSRS Conference
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    • 2008.10a
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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.

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Ecoinformatics: A Review of Approach and Applications in Ecological Research

  • Lin, Chau Chin
    • Proceedings of the National Institute of Ecology of the Republic of Korea
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    • v.1 no.1
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    • pp.9-21
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    • 2020
  • Ecological communities adapt the concept of informatics in the late 20 century and develop rapidly in the early 21 century to form Ecoinformatics as the new approach of ecological research. The new approach takes into account the data-intensive nature of ecology, the precious information content of ecological data, and the growing capacity of computational technology to leverage complex data as well as the critical need for informing sustainable management of complex ecosystems. It comprehends techniques for data management, data analysis, synthesis, and forecasting on ecological research. The present paper attempts to review the development history, studies and application cases of ecoinformatics in ecological research especially on Long Term Ecological Research (LTER). From the applications show that the ecoinformatics approach and management system have formed a new paradigm in ecological research.

Pattern Analysis of Nonconforming Farmers in Residual Pesticides using Exploratory Data Analysis and Association Rule Analysis (탐색적 자료 분석 및 연관규칙 분석을 활용한 잔류농약 부적합 농업인 유형 분석)

  • Kim, Sangung;Park, Eunsoo;Cho, Hyunjeong;Hong, Sunghie;Sohn, Byungchul;Hong, Jeehwa
    • Journal of Korean Society for Quality Management
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    • v.49 no.1
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    • pp.81-95
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    • 2021
  • Purpose: The purpose of this study was to analysis pattern of nonconforming farmers who is one of the factors of unconformity in residual pesticides. Methods: Pattern analysis of nonconforming farmers were analyzed through convergence of safety data and farmer's DB data. Exploratory data analysis and association rule analysis were used for extracting factors related to unconformity. Results: The results of this study are as follows; regarding the exploratory data analysis, it was found that factors of farmers influencing unconformity in residual pesticides by total 9 factors; sampling time, gender, age, cultivation region, farming career, agricultural start form, type of agriculture, cultivation area, classification of agricultural products. Regarding the association rule analysis, non-conformity association rules were found over the past three years. There was a difference in the pattern of nonconforming farmers depending on the cultivation period. Conclusion: Exploratory data analysis and association rule analysis will be useful tools to establish more efficient and economical safety management plan for agricultural products.