• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.11a
• /
• pp.85-88
• /
• 2023

오픈 사이언스 운동의 활성화로 인해 다양한 연구 관련 자원들 간의 상호 운용성 확보를 위한 노력이 활발해지고 있다. 특히, 글로벌 연구데이터 커먼즈(Global Open Research Commons) 모델 개발 관련 표준화 활동이 세계 최대 연구데이터 커뮤니티인 RDA(Research Data Alliance)의 주도로 진행되어 왔고, 최근에 GORC Working Group 에서 버전 1.0 모델을 오픈하였다. 이에 이 모델에 대해 살펴보고 국내의 연구데이터 커먼즈인 KRDC(Korea Research Data Commons)와 비교 및 시사점을 논하고 향후 연구 방향을 소개한다.

• Journal of the Korean Society for Library and Information Science
• /
• v.57 no.4
• /
• pp.209-232
• /
• 2023

In order to embrace open research commons, this study looked at the requirements that researchers have for research data platforms. A survey questionnaire was developed using the results of Australian ARDC and European EOSC case studies. The questionnaire addressed five main areas: the need for research data commons, analysis tools, computing resources, consumption of research data, and general respondent characteristics. To determine the requirements for research data platforms, an analysis was conducted on the responses provided by 550 potential platform users. The findings demonstrated that more than 85% of participants concurred on the significance of open research commons. Additionally, there was a high willingness to use research data (77%), analysis tools (84%), share research data (92%), analysis tools (93%), and computing resources (93%) if commons services were provided. The results of this study show that there is a significant demand for open research commons among researchers. Discussions on research data commons are still hard to come by in Korea's research data services sector, though. Research on a range of subjects, such as subject areas, stakeholder characteristics, and real users of commons platforms, need be conducted in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.430-432
• /
• 2022

With the recent increase in interest in the open science movement in science and technology fields such as open access, open data, and open source, the movement to share and utilize publicly funded research products is materializing and revitalizing. In line with this trend, many efforts are being made to establish and revitalize a system for sharing and utilizing research data, which is a key resource for research in Korea. These efforts are mainly focused on collecting research data by field and institution, and linking it with DataON, a national research data platform, to search and utilize it. However, developed countries are building a system that can share and utilize not only such research data but also various types of R&D-related computing resources such as IaaS, PaaS, SaaS, and MLaaS. EOSC (European Open Science Cloud), ARDC (Australian Research Data Commons), and CSTCloud (China S&T Cloud) are representative examples. In Korea, the Korea Research Data Commons (KRDC) is designed and a core framework is being developed to facilitate the sharing of these computing resources. In this study, the necessity, concept, composition, and future plans of KRDC are introduced.

• Journal of Information Science Theory and Practice
• /
• v.1 no.2
• /
• pp.84-92
• /
• 2013

In this study, the properties of the object types required to describe the relationship among research data resources, which may be generated during the life cycle of the research, are derived. The properties of Fedora Commons and DSpace, which are open source software used for resource management, and schema properties published in DataCite were analyzed. Based on relation names of Fedora Commons, nine new relation names were derived. Thirty-eight object type properties consolidating the target properties of the analysis were derived. The result of this study can be used as basic material for crosswalk research studies of object type relation terms to ensure interoperability among the systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.436-438
• /
• 2022

National Research Data Commons aims to build a system that can be used jointly by arranging analysis resources such as computing infrastructure, software, toolkit, API, and services used for data analysis together with research data to maximize the use of research data. do. The sharing and utilization system for publications and research data in the R&D process is well known. However, the environment in which data and tightly coupled software and computing infrastructure can be shared and utilized is insignificant and there is no management system. In this study, a data model is designed to systematically manage information on digital research resources required in the data-oriented R&D research process. This will be used to register and manage digital research resource information in the National Research Data Commons Service.

• The Journal of Industrial Distribution & Business
• /
• v.7 no.1
• /
• pp.15-17
• /
• 2016

Purpose - During the past twenty years, China has developed rapidly in economy. Meanwhile China's economic development has brought great many problems. Sustainable development is to achieve coordination in the ecological, economic and social aspects. Among them, the environment and resource issues are the most critical issues which affecting sustainable development in China. With China's rapid economic development, China's ecological environment is facing the most serious threat in water pollution, air pollution, solid waste pollution and the destruction of forests and biodiversity, resulting in a significant loss of the national economy. This research aims to examine whether the tragedy of the commons has hindered the sustainable development of China's economy or not. On the other hand, we try to analyze a solution to improve this situation. Research design, data, and methodology - Theoretical background study, finding optimization models, and data analysis. Results - In the case of a clear definition of property rights, the air will have a market price. The market price will coordinate pollutant emissions. Conclusions - The tragedy of commons has hindered the sustainable development. The model of China's Economic development should be changed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.433-435
• /
• 2022

In this paper, we introduce a computing resource standard metadata schema design plan for registering, retrieving, and managing computing resources used for research data analysis and utilization in the Korea Research Data Commons(KRDC). KRDC is a joint utilization system of research data and computing resources to maximize the sharing and utilization of research data. Computing resources refer to all resources in the computing environment, such as analysis infrastructure and analysis software, necessary to analyze and utilize research data used in the entire research process. The standard metadata schema for KRDC computing resource management is designed by considering common attributes for computing resource management and other attributes according to each computing resource feature. The standard metadata schema for computing resource management consists of a computing resource metadata schema and a computing resource provider metadata schema. In addition, the metadata schema of computing resources and providers was designed as a service schema and a system schema group according to their characteristics. The standard metadata schema designed in this paper is used for computing resource registration, retrieval, management, and workflow services for computing resource providers and computing resource users through the KRDC web service, and is designed in a scalable form for various computing resource links.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.11a
• /
• pp.311-313
• /
• 2023

딥러닝에 대한 관심이 증가함에 따라 다양한 분야의 연구자 사이에 딥러닝 모델의 적용 및 재현이 중요한 작업으로 자리잡았다. 하지만 모델을 재현하고 활용하는데 있어 다양한 환경과 자원의 한계가 발생하여 문제가 되고 있다. 이러한 문제를 해결하기 위해 본 논문에서는 국가연구데이터커먼즈체계인 KRDC 프레임워크를 활용하여 딥러닝 학습 모델의 재현 방안을 제안하였다. 이를 통해 딥러닝 연구에 익숙하지 않은 사용자도 학습 모델의 적용 및 활용을 용이하게 할 수 있음을 확인하였다. KRDC 프레임워크는 사용자가 원하는 데이터와 태스크를 정의하고, 워크플로우로 구성, 학습 모델의 재현 및 활용을 지원한다.

• Journal of the Korean Society for information Management
• /
• v.41 no.1
• /
• pp.465-486
• /
• 2024

The purpose of this study is to identify the current status of infrastructure and services for analyzing research data for research data managers at government-funded research institutions under the National Research Council for Science and Technology (NST) who will actually use the Korea Research Data Commons (KRDC), which is being developed by the Korea Institute of Science and Technology Information (KISTI) and to investigate the perceptions of research data managers related to the establishment of KRDC system. For the study, we conducted a survey targeting 24 government-funded research institutes, excluding KISTI, and interviewed research data managers from 9 of the 15 institutions surveyed who agreed to follow-up interviews. As a result of the survey, most institutions were providing related services, and their willingness to introduce an integrated analysis framework for the use of research data and provide a system for using externally released analysis software was also high. Meanwhile, when we investigated the external disclosure status of each institution's analysis services through follow-up interviews, only a minimal number of institutions were disclosing them to the outside world. The findings reveal that there is a demand to utilize analysis infrastructure and services when provided through the framework. However, it is difficult to disclose and share the analysis resources held by each organization. In order to establish the KRDC system, it is essential to share research sites' analysis infrastructure and services, and in addition, changes in the perception of research sites and institutional changes are necessary. Furthermore, there is a need to establish policies that consider the system's convenience, security, and compensation system raised in the follow-up interviews.

• Journal of Information Science Theory and Practice
• /
• v.10 no.spc
• /
• pp.25-38
• /
• 2022

Research data means data used or created in the course of research or experiments. Research data is very important for validation of research conducted and for use in future research and projects. Recently, convergence research between various fields and international cooperation has been continuously done due to the explosive increase of research data and the increase in the complexity of science and technology. Developed countries are actively promoting open science policies that share research results and processes to create new knowledge and values through convergence research. Communities to promote the sharing and utilization of research data such as RDA (Research Data Alliance) and COAR (Confederation of Open Access Repositories) are active, and various platforms for managing and sharing research data are being developed and used. OpenAIRE (Open Access Infrastructure for Research In Europe), a research data platform in Europe, ARDC (Australian Research Data Commons) in Australia, and IRDB (Institutional Repositories DataBase) in Japan provide research data or research data related services. Korea has been establishing and implementing a research data sharing and utilization strategy to promote the sharing and utilization of research data at the national level, led by the central government. Based on this strategy, KISTI has been building a Korean research data platform (DataON) since 2018, and has been providing research data sharing and utilization services to users since January 2020. This paper reviews the characteristics of DataON and how it is used for research by showing its applications.