• Title/Summary/Keyword: 연구데이터 공유

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A Study on the Factors Affecting Sharing of Research Data of Science and Technology Researchers (과학기술분야 연구자의 연구데이터 공유의 영향요인에 대한 연구)

  • Kim, Moonjeong;Kim, Seonghee
    • Journal of the Korean Society for Library and Information Science
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    • v.49 no.2
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    • pp.313-334
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    • 2015
  • The purpose of this study was to investigate factors affecting the sharing of research data of science and technology researchers. Data was collected through a survey of 198 science and technology researchers. Independent variables in this study included perception, openness in communication, collaboration, and trust. Latent variable was selected as reward system and dependent variable was research data sharing. The results of analysis of structural equation modeling showed that perception were found to have a positive impact on reward system for data sharing for research. Other factors such as trust, openness in communication and collaboration were not statistically significant in their affect on reward system for data sharing. Finally, reward system was identified as the influential factor on research data sharing.

A Study on Use Case of Research Data Sharing in Biotechnology (생명공학분야의 연구데이터 공유 사례에 관한 연구)

  • Park, Miyoung;Ahn, Inja;Kim, Junmo
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.29 no.1
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    • pp.393-416
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    • 2018
  • In this study, major steps of the research data management plan were derived through the research data management guidelines of major countries (NISO DMP in the US, UK DMP in UK archives, etc.). The results obtained are support for research data policy & planning, research data technical support, research data sharing support, research data legal mechanism support, and research data education support. In this study, we analyzed seven cases of data sharing among 7 domestic and foreign biotechnology. Shared use case countries are limited to the United Kingdom and the United States, which play a leading role in the management of research data. In Korea, shared cases were analyzed for the Korean Bio Information Center and related systems, which is a research and performance management and distribution agency designated by the Ministry of Science and Technology.

Developing a Roadmap for National Research Data Management Governance: Based on the Analysis of United Kingdom's Case (국가 차원의 연구데이터 관리체계 구축을 위한 로드맵 제안 - 영국 사례 분석을 중심으로 -)

  • Shim, Wonsik
    • 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.

An Auto-Labeling based Smart Image Annotation System (자동-레이블링 기반 영상 학습데이터 제작 시스템)

  • Lee, Ryong;Jang, Rae-young;Park, Min-woo;Lee, Gunwoo;Choi, Myung-Seok
    • The Journal of the Korea Contents Association
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    • v.21 no.6
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    • pp.701-715
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    • 2021
  • The drastic advance of recent deep learning technologies is heavily dependent on training datasets which are essential to train models by themselves with less human efforts. In comparison with the work to design deep learning models, preparing datasets is a long haul; at the moment, in the domain of vision intelligent, datasets are still being made by handwork requiring a lot of time and efforts, where workers need to directly make labels on each image usually with GUI-based labeling tools. In this paper, we overview the current status of vision datasets focusing on what datasets are being shared and how they are prepared with various labeling tools. Particularly, in order to relieve the repetitive and tiring labeling work, we present an interactive smart image annotating system with which the annotation work can be transformed from the direct human-only manual labeling to a correction-after-checking by means of a support of automatic labeling. In an experiment, we show that automatic labeling can greatly improve the productivity of datasets especially reducing time and efforts to specify regions of objects found in images. Finally, we discuss critical issues that we faced in the experiment to our annotation system and describe future work to raise the productivity of image datasets creation for accelerating AI technology.

Factor Analysis of Effects on Research Data Collection (연구데이터 수집에 영향을 미치는 요인 분석)

  • Kim, Eun-Jeong;Nam, Tae-Woo
    • Journal of the Korean Society for information Management
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    • v.29 no.2
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    • pp.27-44
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    • 2012
  • The purpose of this study is to examine the factors which have an effect on researcher's behavior and attitudes about depositing data from sponsored research. I analyzed the behavior, barriers, incentives and information infrastructure of 135 researchers in 35 Korean research institutes. The survey identified several factors that may encourage timely deposit of data by researchers. According to the analyzing factors, I propose the following methods in perception, incentives, use, policy and information infrastructure aspects.

Open Research Data Policy Trends and Domestic Status (오픈 연구데이터 정책 동향 및 국내 현황)

  • Choi, Myung-Seok
    • Proceedings of the Korean Society for Information Management Conference
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    • pp.97-97
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    • 2017
  • 최근 연구 환경과 연구 패러다임이 데이터 중심으로 변화되고 있다. 특히, 공공 연구성과의 개방과 공유에 기반한 오픈 사이언스(Open Science)가 과학 연구의 글로벌 어젠더로 새롭게 부각되고 있다. OECD는 오픈 사이언스를 정책의제로 채택하고 있으며, 미국, 영국, 호주 등 세계 선진국에서는 공공자금이 투입된 연구과제로부터 생산된 연구데이터의 체계적인 관리와 쉬운 접근, 재사용을 통한 가치 창출을 위해 데이터 관리 계획(Data Management Plan)을 비롯한 오픈 연구데이터 정책을 적극적으로 시행하고 있다. 하지만 국내에서는 연구데이터를 공유 활용하기 위한 법제도적 기반과 관련 인프라가 아직 미흡한 실정이다. 이 연구에서는 오픈 연구데이터를 위한 세계 각국의 정책 동향을 소개한다. 그리고, 국가과학기술연구회 소속 22개 정부출연 연구기관과 국내 20개 대학의 연구자를 대상으로 조사한 연구데이터 생산, 관리, 활용 현황과 데이터 공유 활용을 위한 시사점과 개선방향을 살펴본다.

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Analysis on the interrupt coalescence effect in cluster file systems for scientific computation (과학계산용 클러스터 파일시스템에서의 인터럽트 통합효과 분석)

  • Park, Seok-Jung;Woo, Joon;Lee, Jae-Kook;Kim, Hyong-Shik
    • Proceedings of the Korean Information Science Society Conference
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    • pp.105-109
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    • 2008
  • 클러스터 파일시스템은 근거리 또는 원거리에 있는 클러스터 시스템 간에 연구데이터 공유 뿐 아니라, 실시간 계산을 위한 데이터 저장 공간으로 사용되는 네트워크 기반의 파일시스템이다. 고도의 과학계산을 처리할 때 계산노드들은 네트워크를 통해 연결된 클러스터 파일시스템으로부터 대용량의 데이터를 송수신하는 과정에서 CPU의 부하가 생기게 되고 이러한 문제는 계산노드로 하여금 과학계산의 속도를 저하시키는 요인이 된다. 본 논문에서는 패킷 송수신으로 인한 CPU 부하를 줄이고 이를 통하여 계산 성능을 향상시킬 목적으로 계산노드에서 수신하는 패킷들에 대해 인터럽트를 통합할 때 CPU 사용률에 미치는 영향을 분석하였다.

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A Study on Publication and Citation of Research Data (연구 데이터의 출판과 인용에 관한 연구)

  • Lee, sang-ho
    • Proceedings of the Korea Contents Association Conference
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    • pp.65-66
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    • 2017
  • 최근 오픈 사이언스 운동과 함께 정부 부처, 연구비 지원기관 등에서는 공적 기금으로 연구를 수행하는 경우 생성된 각종 연구 데이터를 관리하고 공개하도록 의무화하려는 움직임이 있다. 데이터에 DOI와 같은 식별자를 부여하여 데이터 리파지토리를 통해 출판하면 이해당사자들에게 많은 이익을 가져다 줄 수 있으며, 데이터의 인용을 활성화하기 위해 주제별 또는 기관별 리파지토리나 데이터센터에서 표준적인 인용 방법과 인용 요소들을 발표하고 있다. 앞으로 과학연구의 공개, 개방화가 더욱 추진되면 더욱 많은 연구데이터의 공유 활동이 일어날 것으로 예상되며 분야별 또는 유형별로 국제적인 데이터 리파지토리들이 출현하여 학술 논문의 근거가 되는 데이터 저장소로서의 역할을 수행할 것으로 생각된다.

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A Study on Analysis of Research Data Repository in Humanities and Social Sciences (re3data를 기반으로 한 인문사회 RDR 연구)

  • Cho, Jane;Park, Jong-Do
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.30 no.2
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    • pp.69-87
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    • 2019
  • As the discussions on sharing research data prevail by the chance of the inauguration of the International Open Data Charter, research support organizations in the United States, the United Kingdom, and Japan are encouraging researchers to deposit their findings in a credible repository. Humanities and social sciences field, in which research data sharing culture and storage infrastructure are immature compared to life science and natural science, also needs to establish and operate a reliable storage infrastructure to guarantee the continuous access and utilization of data. This study analyzed the overall operational status of 305 subject repositories registered in re3data for the humanities and social sciences and clustered them according to the operational level using 5 indicators. As a result, 70% of the population were identified as universal clusters, and 20% of the excellent cluster was found to have the largest number of linguistic fields and the German-operated. In addition, this study confirmed through correspondence analysis that there is a relation between the sub-theme fields of humanities and social sciences and the types of data to be archived. The history and art domians are related to images, and social studies are related to statistical data. Linguistics has also been analyzed to be related to audio, plain text, and code.