• 제목/요약/키워드: Data Maturity

검색결과 607건 처리시간 0.023초

도서관 데이터 성숙도 평가모형 개발 연구 (A Study on the Development of Assessment Model for Data Maturity of Library)

  • 한상우
    • 한국문헌정보학회지
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    • 제57권1호
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    • pp.213-231
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    • 2023
  • 본 연구는 도서관의 데이터 성숙도를 평가할 수 있는 모형(안)을 개발하고 제시하는 것을 목적으로 한다. 이를 위해 데이터 성숙도와 관련된 선행연구를 분석하여 도서관에 적용할 수 있는 성숙도 평가모형을 구성하고자 하였다. 본 연구의 결과 5개 영역의 19개 평가 요소로 구성된 데이터 성숙도 모형을 설계하였고, 성숙도 단계는 5단계로 설정하였다. 향후 데이터 성숙도 평가모형을 이용하여 도서관 빅데이터 사업에 참여하고 있는 도서관의 데이터 성숙도를 측정할 수 있을 것이며, 장기적으로 데이터 기반 도서관 운영 및 데이터 활용 발전 방향성을 제시할 수 있을 것으로 기대할 수 있다.

A Data Quality Management Maturity Model

  • Ryu, Kyung-Seok;Park, Joo-Seok;Park, Jae-Hong
    • 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.

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데이터 리터러시와 데이터 분석 성숙도의 관계에서 조직문화의 조절효과 (Data Literacy, Organizational Culture, and Data Analytics Maturity: Moderating Effect of Organizational Culture)

  • 박종남;조예은
    • 정보화정책
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    • 제28권1호
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    • pp.43-63
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    • 2021
  • 최근 빠르게 변화하는 내·외부 환경에 대응하기 위해 데이터 분석 역량이 강조되고 있다. 본 연구는 조직문화가 데이터 기반 성과창출의 결정적인 역할을 한다는 점에 주목하여 조직문화 유형에 따른 데이터 리터러시와 데이터 분석 성숙도의 관계를 실증적으로 규명하였다. 첫 번째 분석 주제인 데이터 리터러시와 데이터 분석 활용도의 관계에서는 조직 구성원의 데이터 리터러시가 높을수록 조직의 데이터 분석 성숙도가 높다고 인식하고 있었다. 두 번째 주제인 조직문화와 데이터 분석 활용도의 관계를 살펴보면, 조직 구성원이 조직의 문화를 관계지향 문화와 혁신지향 문화라고 인식할수록 데이터 분석 성숙도가 높아진다고 인식하고 있다. 세 번째 분석인 데이터 리터러시와 데이터 분석 성숙도의 관계성은 관계지향 문화와 위계지향 문화에 의해서 달라짐을 발견하였다. 관계지향 문화는 데이터 리터러시가 데이터 분석 성숙도 인식에 미치는 영향에 대한 상승효과로 나타났으나, 위계지향 문화는 완충효과가 있는 것으로 나타났다.

골 성숙도 판별을 위한 심층 메타 학습 기반의 분류 문제 학습 방법 (Deep Meta Learning Based Classification Problem Learning Method for Skeletal Maturity Indication)

  • 민정원;강동중
    • 한국멀티미디어학회논문지
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    • 제21권2호
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    • pp.98-107
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    • 2018
  • In this paper, we propose a method to classify the skeletal maturity with a small amount of hand wrist X-ray image using deep learning-based meta-learning. General deep-learning techniques require large amounts of data, but in many cases, these data sets are not available for practical application. Lack of learning data is usually solved through transfer learning using pre-trained models with large data sets. However, transfer learning performance may be degraded due to over fitting for unknown new task with small data, which results in poor generalization capability. In addition, medical images require high cost resources such as a professional manpower and mcuh time to obtain labeled data. Therefore, in this paper, we use meta-learning that can classify using only a small amount of new data by pre-trained models trained with various learning tasks. First, we train the meta-model by using a separate data set composed of various learning tasks. The network learns to classify the bone maturity using the bone maturity data composed of the radiographs of the wrist. Then, we compare the results of the classification using the conventional learning algorithm with the results of the meta learning by the same number of learning data sets.

SLA의 수행 단계별 성숙도가 SLA 성과에 미치는 영향에 관한 연구 (A Study of SLA's Maturity Level on Performance)

  • 남기찬;김주희
    • Journal of Information Technology Applications and Management
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    • 제14권1호
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    • pp.1-20
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    • 2007
  • IT outsourcing becomes one of the important shills for managing diverse and complex information systems, SIA is considered as an one of the success factors for the successful outsourcing management. Since it helps to establish common goal and provides better visibility of trends and performance, the SLA process must go beyond mere measurement to include a methodology for the ongoing management of service levels, and for the continuous improvement of service activities, functions and processes. Despite SLA is one of the most important skills for the successful outsourcing, few studies have been conducted for academic as well as practical purpose. For this reason, The objective of this study is to develop an SLA's maturity model and empirically demonstrate how SLA's maturity level affects its Performance through SLA's maturity model. The major contributions of this study are in two areas. This study contributes to academicians as well as practitioners. First, from the academic perspectives this study tries investigating the maturity level of the SLA based on empirical data. Second, practitioners can self-test their firms' maturity level using the proposed model. The results of this study show that the SLA's maturity level affected positively SLA's performance. It is founded that the SLA's maturity level had a significant impact on SLA's performance.

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Development of a classification model for tomato maturity using hyperspectral imagery

  • Hye-Young Song;Byeong-Hyo Cho;Yong-Hyun Kim;Kyoung-Chul Kim
    • 농업과학연구
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    • 제49권1호
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    • pp.129-136
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    • 2022
  • In this study, we aimed to develop a maturity classification model for tomatoes using hyperspectral imaging in the range of 400 - 1,000 nm. Fifty-seven tomatoes harvested in August and November of 2021 were used as the sample set, and hyperspectral data was extracted from the surfaces of these tomatoes. A combined method of SNV (standard normal variate) and SG (Savitzky-Golay) methods was used for the pre-processing of the hyperspectral data. In addition, the hyperspectral data were analyzed for all maturity stages and considering bandwidths with different FWHM (full width at half maximum) values of 2, 25, and 50 nm. The PCA (principal component analysis) method was used to analyze the principal components related to maturity stages for the tomatoes. As a result, 500 - 550 nm and 650 - 700 nm bands were found to be related to the maturity stages of tomatoes. In addition, PC1 and PC2 explained approximately 97% of the variance at all FWHM conditions and thus were used as input data for classification model training based on the SVM (support vector machine). The SVM models were able to classify tomato maturity into five stages (Green, Turning, Pink, Light red, and Red) with over 95% accuracy regardless of the FWHM condition. Therefore, it was considered that hyperspectral data with 50 nm FWHM and SVM is feasible for use in the classification of tomato maturity into five stages.

초등학교 여학생의 성적 성숙도, 부모자녀 의사소통 및 성숙 불안에 관한 연구 (Association of Sexual Maturation and Parent-Child Communication on Maturity Fears in Elementary School Girls)

  • 조헌하;문소현
    • Child Health Nursing Research
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    • 제22권2호
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    • pp.137-144
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    • 2016
  • Purpose: The purpose of this study was to investigate factors that influence maturity fears in elementary school girls. Methods: The participants were 118 3rd and 4th grade students from 3 elementary schools in 3 cities in Korea. Data were collected using questionnaires which included measurement scales for the relative variables and demographic data. Data were analyzed using t-test, ANOVA, Pearson correlation coefficients, and hierarchial regression analysis with SPSS/WIN 21.0. Results: The significant predictors of maturity fears were weight, father-child communication, frequency of maturity communication with father, and close relation with mother. Conclusion: For effective management of maturity fears in elementary school girls, programs including weight control, functional communication with father and supportive nurturance of mother should be developed.

초등학생의 진로의식성숙도에 애착과 자아개념이 미치는 효과: 성차, 동시효과 및 지연효과에 관하여 (The Effects of Attachment and Self Concept on Career Maturity of Elementary School Students: Gender Differences, Concurrent and Lagged Effects)

  • 장영은
    • 대한가정학회지
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    • 제48권6호
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    • pp.71-82
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    • 2010
  • This study examined the effects of parent-, peer-, and teacher-attachment on development of career maturity via the mediating effects of self concept. There were 2844 elementary school students, ages 12 to 13 years old, who participated in the Korean Youth Panel Survey. All data were used for the analyses. Gender differences were found in most of the variables, including attachment, self concept, and career maturity. The Structural Equation Modeling technique applied to the data revealed that there were both concurrent and lagged effects of attachment and self concept on career maturity. It was found that self concept played a mediating role on career maturity.

의사결정나무 분석을 이용한 고등학생의 진로 성숙도 관련 요인 분석 (A Prediction Model of Factors related to Career Maturity in Korean High School Students)

  • 서지영;김민주
    • Child Health Nursing Research
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    • 제25권2호
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    • pp.95-102
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    • 2019
  • Purpose: The purpose of this study was to identify factors associated with career maturity among Korean high school students. Methods: A descriptive cross-sectional design was adopted using secondary data from the 2012 Korean Welfare Panel Study (KoWePS). The participants were 496 high school students who completed the supplemental survey for children, which included items on career maturity, self-esteem, study stress, teacher attachment, relationship with parents, peer attachment, depression and anxiety. Descriptive statistics, the chi-square-test, the t-test, and a decision tree were used for data analysis. Results: The decision tree identified five final nodes predicting career maturity after forcing self-esteem as the first variable. The highest predicted rate of high career maturity was associated with high self-esteem, experience of career counseling, and high teacher attachment. The lowest predicted rate of high career maturity was associated with low self-esteem and low attachment to friends. Conclusion: Factors influencing career maturity were varied by levels of self-esteem in Korean high school students. Thus, it is necessary to develop different approaches to enhance career maturity according to levels of self-esteem.

기업 데이터 전략과 투자를 위한 빅데이터 성숙도 평가 프레임워크 실증 연구 (A Study on Big Data Maturity Assessment Framework for Corporate Data Strategy and Investment)

  • 김옥기;박정;조완섭
    • 한국빅데이터학회지
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    • 제6권1호
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    • pp.13-22
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    • 2021
  • 본 연구의 목적은 기업의 효과적인 데이터 전략 수립과 효율적 투자를 위해 빅데이터 성숙도를 평가하기 위한 프레임워크를 개발하고 이를 실증하는데 있다. 이를 위해 현재까지 개발된 평가의 단점을 보완하여, 기업의 빅데이터 성숙도를 프로세스 통합적으로 평가할 수 있는 프레임워크를 개발하였다. 그 결과 '비전과 전략', '관리', '분석', '활용'의 4가지 평가 영역과 각 영역별 평가항목, 세부내용 및 단계별 준거를 도출하였다. 이를 기업인 설문을 통해 실증하였으며 국내 기업의 빅데이터 성숙도를 진단하였다. 향후 연구방향으로 산업별 특성에 따른 세부 평가요소 개발, 평가 결과에 따른 데이터 활용 프레임워크의 발전, 검증 대상의 조정을 통한 추가적인 타당성 및 신뢰도 향상을 제안하였다.