• Title/Summary/Keyword: Research Data Curation

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An Examination of Core Competencies for Data Librarians (데이터사서의 핵심 역량 분석 연구)

  • Park, Hyoungjoo
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.33 no.1
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    • pp.301-319
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    • 2022
  • In recent decades, research became more data-intensive in the fast-paced information environment. Researchers are facing new challenges in managing their research data due to the increasing volume of data-driven research and the policies of major funding agencies. Information professionals have begun to offer various data support services such as training, instruction, data curation, data management planning and data visualization. However, the emerging field of data librarians, including specific roles and competencies, has not been clearly established even though librarians are taking on new roles in data services. Therefore, there is a need to identify a set of competencies for data librarians in this growing field. The purpose of this study is to consider varying core competencies for data librarians. This exploratory study examines 95 online recruiting advertisements regarding data librarians posted between 2017 and 2021. This study finds core competencies for data librarians that include skills in technology, communication and interpersonal relationships, training/consulting, service, library management, metadata knowledge and knowledge of data curation. Specific core technology skills include knowledge of statistical software and computer programming. This study contributes to an understanding of core competencies for data librarians to help future information professionals prepare their competencies as data librarians and the instructors who develop and revise curriculum and course materials.

A Study on Functional Details and Importance of Geoscience Research Data Management (Geoscience 연구데이터 관리를 위한 기능별 세부요소 및 중요도에 관한 연구)

  • Kim, Juseop;Kim, Suntae;Choi, Sangki
    • Journal of the Korean Society for Library and Information Science
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    • v.54 no.1
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    • pp.411-440
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    • 2020
  • The purpose of this study is to derive the detailed elements of each RDM function that can be applied to the development of research data management system in Geoscience field in Korea. Eight institutions related to RDM services were analyzed to achieve the research purpose. As a result of the analysis, 80 detailed elements of Geoscience RDM function were derived, and a survey was conducted to domestic experts to verify the derived details. As a result, 80 RDM functional details for Geoscience are presented in order of importance. The elements presented can be presented as functional details in the establishment and operation of RDM services in the field of Geoscience in research institutes or university libraries in Korea.

Identification and Analysis of Experts in the Field of Disaster and Safety based on Domestic Scholarly Content (국내 학술콘텐트 기반 재난안전분야 전문가 식별 및 분석)

  • Kim, Byungkyu;Shin, Jin-Seop;You, Beon-Jong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2018.07a
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    • pp.80-82
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    • 2018
  • 전세계적으로 대형 자연재난 및 사회재난의 증가로 재난 대응 체계 고도화에 대한 국가적인 관심과 요구가 급증하고 있다. 다양한 재난유형에 대한 효과적인 대응을 위해서는 사전에 구축된 재난유형별 전문가 Pool의 구축과 활용이 매우 중요하다. 본 논문에서는 학술콘텐트를 활용하여 재난안전분야 전문가들을 식별 및 분석하고 식별된 재난분야 학술정보와 전문가 정보 시범 서비스를 구현하였으며, 주요 연구결과는 재난안전정보 공유 플랫폼에 연계하여 재난 단계별 전문가 추천 및 서비스에 활용될 계획이다.

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Empirical Investigation of User Behavior for Financial Mydata: The Moderating Effects of Organizational Information Transparency and Data Security Policy (금융마이데이터 사용자 행동에 관한 실증 연구: 기관정보투명성, 데이터 보안정책의 조절효과)

  • Sohn, Chang Yong;Park, Hyun Sun;Kim, Sang Hyun
    • The Journal of Information Systems
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    • v.32 no.3
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    • pp.85-116
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    • 2023
  • Purpose The importance of data as a key resource of the intelligence revolution is being highlighted, among all those phenomena MyData is attracting attention as a key concept by organizations and individuals that eventually leads the data economy. In this regard, this study was started to contribute to the successful settlement and continuous growth of the domestic MyData industry, which has just entered the system. Design/methodology/approach To develop and test all proposed casual relationships within the research model, we used the Value-Attitude-Behavior(VAB) model as a basic framework. A total of 385 copies were used for the final analysis, and for SPSS 25.0, MS-Excel 2016, and AMOS 24.0 to summarize respondent demographic characteristics, measurement model, and structural model. Findings Findings show that all proposed hypotheses were supported with the exception of the moderating effect of organizational information transparency between data controllability and perceived value, and between data controllability and attitude toward MyData service.

Risk Factors for Sarcopenia, Sarcopenic Obesity, and Sarcopenia Without Obesity in Older Adults

  • Kim, Seo-hyun;Yi, Chung-hwi;Lim, Jin-seok
    • Physical Therapy Korea
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    • v.28 no.3
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    • pp.177-185
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    • 2021
  • Background: Muscle undergoes change continuously with aging. Sarcopenia, in which muscle mass decrease with aging, is associated with various diseases, the risk of falling, and the deterioration of quality of life. Obesity and sarcopenia also have a synergy effect on the disease of the older adults. Objects: This study examined the risk factors for sarcopenia, sarcopenic obesity, and sarcopenia without obesity and developed prediction models. Methods: This machine-learning study used the 2008-2011 Korea National Health and Nutrition Examination Surveys in the analysis. After data curation, 5,563 older participants were selected, of whom 1,169 had sarcopenia, 538 had sarcopenic obesity, and 631 had sarcopenia without obesity; the remaining 4,394 were normal. Decision tree and random forest models were used to identify risk factors. Results: The risk factors for sarcopenia chosen by both methods were body mass index (BMI) and duration of moderate physical activity; those for sarcopenic obesity were sex, BMI, and duration of moderate physical activity; and those for sarcopenia without obesity were BMI and sex. The areas under the receiver operating characteristic curves of all prediction models exceeded 0.75. BMI could predict sarcopenia-related disease. Conclusion: Risk factors for sarcopenia-related diseases should be identified and programs for sarcopenia-related disease prevention should be developed. Data-mining research using population data should be conducted to enhance the effectiveness of early treatment for people with sarcopenia-related diseases through predictive models.

An Economic Ripple Effect Analysis of National Scientific Data Center Construction (국가 과학데이터센터 구축의 경제적 파급효과 분석)

  • Park, Sung-Uk;Hahn, Sun-Hwa
    • Journal of Information Management
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    • v.42 no.3
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    • pp.55-69
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    • 2011
  • In the modern scientific R&D, the efficient acquisition, curation, analysis and visualization are core elements of the science development. The value of scientific data is very important in data intensive research. An output of scientific data is drastically increasing. However we have only each individual system of scientific data in now. Therefore We feel a lack of efficiency of scientific data. In this paper, We analyze an economic ripple effects in terms of production inducement effect, added value inducement effect, labor inducement effect and forward backward linkage effect of national scientific data center construction using an input-out analysis of the bank of Korea(2009). We also examine an economic propriety of national scientific data center construction.

hpvPDB: An Online Proteome Reserve for Human Papillomavirus

  • Kumar, Satish;Jena, Lingaraja;Daf, Sangeeta;Mohod, Kanchan;Goyal, Peyush;Varma, Ashok K.
    • Genomics & Informatics
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    • v.11 no.4
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    • pp.289-291
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    • 2013
  • Human papillomavirus (HPV) infection is the leading cause of cancer mortality among women worldwide. The molecular understanding of HPV proteins has significant connotation for understanding their intrusion in the host and designing novel protein vaccines and anti-viral agents, etc. Genomic, proteomic, structural, and disease-related information on HPV is available on the web; yet, with trivial annotations and more so, it is not well customized for data analysis, host-pathogen interaction, strain-disease association, drug designing, and sequence analysis, etc. We attempted to design an online reserve with comprehensive information on HPV for the end users desiring the same. The Human Papillomavirus Proteome Database (hpvPDB) domiciles proteomic and genomic information on 150 HPV strains sequenced to date. Simultaneous easy expandability and retrieval of the strain-specific data, with a provision for sequence analysis and exploration potential of predicted structures, and easy access for curation and annotation through a range of search options at one platform are a few of its important features. Affluent information in this reserve could be of help for researchers involved in structural virology, cancer research, drug discovery, and vaccine design.

A Study on the Perception of Fashion Platforms and Fashion Smart Factories using Big Data Analysis (빅데이터 분석을 이용한 패션 플랫폼과 패션 스마트 팩토리에 대한 인식 연구)

  • Song, Eun-young
    • Fashion & Textile Research Journal
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    • v.23 no.6
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    • pp.799-809
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    • 2021
  • This study aimed to grasp the perceptions and trends in fashion platforms and fashion smart factories using big data analysis. As a research method, big data analysis, fashion platform, and smart factory were identified through literature and prior studies, and text mining analysis and network analysis were performed after collecting text from the web environment between April 2019 and April 2021. After data purification with Textom, the words of fashion platform (1,0591 pieces) and fashion smart factory (9750 pieces) were used for analysis. Key words were derived, the frequency of appearance was calculated, and the results were visualized in word cloud and N-gram. The top 70 words by frequency of appearance were used to generate a matrix, structural equivalence analysis was performed, and the results were displayed using network visualization and dendrograms. The collected data revealed that smart factory had high social issues, but consumer interest and academic research were insufficient, and the amount and frequency of related words on the fashion platform were both high. As a result of structural equalization analysis, it was found that fashion platforms with strong connectivity between clusters are creating new competitiveness with service platforms that add sharing, manufacturing, and curation functions, and fashion smart factories can expect future value to grow together, according to digital technology innovation and platforms. This study can serve as a foundation for future research topics related to fashion platforms and smart factories.

How Can We Preserve Social Memories?: Exploration of Global Open Archives

  • Gang, Ju-Yeon;Kim, Geon;Oh, Hyo-Jung
    • Journal of Information Science Theory and Practice
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    • v.7 no.3
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    • pp.40-51
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    • 2019
  • Until now, records re-enacting social memories have not been main targets for preservation and management in Korea. However, people have recently begun to focus on forming and maintaining their memories because these personalized records have started to be recognized as social and political issues. In this respect, this study aims to find out how to preserve social memories by comparing various global open archives. For achieving our research goal, we first established the definition of social memories and records and revealed their characteristics. After then, we selected representative open archives' websites to examine their collection polices and compare them according to several criteria. As a result, we distilled insights based on similarities and differences of each archive and discussed considerations in preserving social memories consisting of three phases: analyzing target social memories, establishing collection policies, and collecting actual records. This study has significance in that it examines the characteristics of social memories and records and also suggests preliminary findings for advanced research to develop practical tools for social records management and archives.

Data Science Degree and Curriculum in Korea and its Implications for the Information Field (국내 데이터사이언스 학위 및 교과 운영 현황과 문헌정보학과로의 함의)

  • Park, Hyoungjoo;Lee, Heejin
    • Journal of Korean Library and Information Science Society
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    • v.53 no.3
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    • pp.431-454
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    • 2022
  • This study examined data science degree programs and courses offered by universities, and those offered by the Library and Information Science (LIS) degree programs, to understand its implications for the LIS programs in Korea. This research assessed the status of data science degrees from 439 schools using the list released by the Korea Educational Development Institute in 2022. To be specific, this study analyzed universities, colleges, majors, sub-majors, interdisciplinary majors, convergence majors, micro-degrees, nanodegrees, tracks, modules, and industry-university cooperative programs within the data science field. This research examined 1,148 courses offered by data science degree programs and 1,325 courses offered by LIS degree programs. Data science degrees in Korea offer courses such as introductory, technical, practical, applied, and in-depth subjects related to data science. Although the LIS programs in Korea do not always offer data science, the courses included topics such as the introduction to data science, database, data visualization, data curation, metadata, big data, and information technology, when courses were offered. The researchers hope the findings of this study will be useful as a starting point for the development and revisions of LIS curriculum on data science in Korea.