• Title/Summary/Keyword: FAIR 데이터 원칙

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FAIR Principle-Based Metadata Assessment Framework (FAIR 원칙 기반 메타데이터 평가 프레임워크)

  • Park, Jin Hyo;Kim, Sung-Hee;Youn, Joosang
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.12
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    • pp.461-468
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    • 2022
  • Development of the big data industry, the cases of providing data utilization services on digital platforms are increasing. In this regard, research in data-related fields is being conducted to apply the FAIR principle that can be applied to the assessment of (meta)data quality, service, and function to data quality evaluation. Especially, the European Open Data Portal applies an assessment model based on FAIR principles. Based on this, a data maturity assessment is conducted and the results are disclosed in reports every year. However, public data portals do not conduct data maturity evaluations based on metadata. In this paper, we propose and evaluate a new model for data maturity evaluation on a big data platform built for multiple domestic public data portals and data transactions, FAIR principles used for data maturity evaluation in Europe's open data portals. The proposed maturity evaluation model is a model that evaluates the quality of public data portal datasets.

Evaluation of Knowledge Graph for Interoperating Digital Records (디지털 기록의 상호운용을 위한 지식그래프의 평가)

  • Haram Park;Haklae Kim
    • Journal of Korean Society of Archives and Records Management
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    • v.23 no.4
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    • pp.159-178
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    • 2023
  • A digital archive is an online platform for preserving and utilizing digital records worthy of continued preservation. However, there are no shared standards for functionality, metadata, or data technical principles across digital archives in Korea. These issues create challenges in linking distributed digital records. This study proposes a common vocabulary for digital archives to enhance the interoperability of digital records and evaluates the interoperability of the digital archive built with the common vocabulary. We collect and analyze data from the digital archive on the Korean financial crisis of 1997 to construct a knowledge graph and compare its interoperability with the knowledge graph built with RiC-O. The archive and the knowledge graph underwent evaluation using the FAIR data principles evaluation framework. The constructed knowledge graph links various objects in the archive and provides contextual information to aid in understanding the archive. The results demonstrate that a knowledge graph built with a common vocabulary significantly improves the linkage, search, and interoperability of digital records compared to a traditional archive.

A Study on the Research Data Management Methods for the Condensed Matter Physics (응집물질물리분야 연구데이터 관리 방안 연구)

  • Kim, Sungwook;Kim, Suntae
    • Journal of the Korean Society for information Management
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    • v.37 no.3
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    • pp.77-106
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    • 2020
  • In this study, we proposed a method to systematically manage research data in the field of condensed matter physics, which is the most active and interdisciplinary field. In the course of the research, a questionnaire was conducted for researchers in the field of condensed matter physics. The questionnaire was constructed based on the research data management tool Data Asset Framework (DAF) and the FAIR principle for data sharing and reuse. The current status of research data management in the field of aggregated material physics was collected from 14 researchers. The collected data consisted of data on the characteristics and basic information of researchers who answered the questionnaire, data preservation and management, and data sharing and access. By analyzing the collected questionnaire results, nine problems were drawn about the characteristics of research data in the field of aggregate material physics, data collection and production, data preservation and management, data sharing and access. In this study, suggestions were made to improve the problems derived from each aspect.

Advancing Reproducibility in Hydrological Modeling: Integration of Open Repositories, Cloud-Based JupyterHub, and Model APIs (온라인저장소, 클라우드기반 JupyterHub와 모델 APIs를 활용한 수자원 모델링의 재현성 개선)

  • Choi, Young Don
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.118-118
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    • 2022
  • 지속적인 학문의 발전을 위해서는 선행연구에 대한 재현성이 무엇보다도 중요하다고 할 수 있다. 하지만 컴퓨터와 소프트웨어의 급속한 발달로 인한 컴퓨터 환경의 다양화, 분석 소프트웨어의 지속적 최신화로 인해서 최근 구축된 모델도 짧게는 몇 달, 길게는 1~2년후면 다양한 에러로 인하여 재현성이 불가능해지고 있다. 이러한 재현성의 극복을 위해서 온라인을 통한 데이터와 소스코드의 공유의 필요성이 제시되고 있으나, 실제로는 개인마다 컴퓨터 환경, 버전, 소프트웨어 설치에 필요한 라이브러리의 버전 또는 디렉토리 등이 달라 단순히 온라인을 통한 데이터와 소스코드의 공유만으로 재현성을 개선하기는 힘든 것이 현실이다. 따라서 이러한 컴퓨터 모델링 환경의 공유는 과거의 형태와 같이 데이터, 소스코드와 매뉴얼의 공유만으로 불가능하다고 할 수 있다. 따라서 본 연구에서는 수자원 모델링의 재현성 개선을 위해 1) 온라인 저장소, 2) 클라우드기반 JupyterHub 모델링 환경과 3) 모델 APIs 3개의 핵심 구성요소를 제시하고, 최근 미국에서 개발된SUMMA(Structure for Unifying Multiple Modeling Alternative) 수자원 모델에 적용하여 재현성 달성을 위한 3개의 핵심 구성요소의 필요성과 용이성을 검증하였다. 첫 번째, 데이터와 모델의 온라인 공유는 FAIR(Findable, Accessible, Interoperable, Reusable) 원칙으로 개발된 수자원분야의 대표적인 온라인 저장소인 HydroShare를 활용하여 모델입력자료를 메타데이터와 함께 공유하였다. 두 번째, HydroShare에서 Web App의 형태로 제공되는 클라우드기반 JupyterHub환경인 CUAHSI JupyterHub(CJH)와 일루노이대학에서 제공하는 CyberGIS-Jupyter for water JupyterHub(CJW)환경에 수자원모델링 환경을 컨테이너(Docker) 환경을 통해 구축·공유하였다. 마지막으로, 클라우드에서 수자원모델의 효율적 이용을 위해 Python기반의SUMMA모델 API인 pySUMMA를 개발·공유하였다. 이와같이 구축된 3개의 핵심 구성요소를 이용하여 2015년 Water Resources Research에 게재된 SUMMA 논문의 9개 Test Cases 중에서 5개를 누구나 쉽게 재현할 수 있음을 증명하였다. 재현성의 중요성에 대한 인식의 증가로 Open과 Transparent Hydrology에 대한 요구가 증대되고 있으며, 이를 위해서 클라우드 기반의 모델링 환경구축 및 제공이 확대되고 있다. 본 연구에서 제시한 HydroShare와 같은 온라인 저장소, CJH와 CJW와 같은 클라우드기반 모델링환경, 모델의 효율적 이용을 위한 모델 APIs는 급속도로 발달하고 있는 컴퓨터 및 소프트웨어 환경에서 핵심구성요소이며, 연구의 재현성 개선을 통해 수자원공학 발전에 기여할 것으로 기대된다.

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A Study on the Applicability of Social Security Platform to Smart City (사회보장플랫폼과 스마트시티에의 적용가능성에 관한 연구)

  • Jang, Bong-Seok
    • Journal of the Korea Convergence Society
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    • v.11 no.11
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    • pp.321-335
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    • 2020
  • Given that with the development of the 4th industry, interest and desire for smart cities are gradually increasing and related technologies are developed as a way to strengthen urban competitiveness by utilizing big data, information and communication technology, IoT, M2M, and AI, the purpose of this study is to find out how to achieve this goal on the premise of the idea of smart well fair city. In other words, the purpose is to devise a smart well-fair city in the care area, such as health care, medical care, and welfare, and see if it is feasible. With this recognition, the paper aimed to review the concept and scope of smart city, the discussions that have been made so far and the issues or limitations on its connection to social security and social welfare, and based on it, come up with the concept of welfare city. As a method of realizing the smart welfare city, the paper reviewed characteristics and features of a social security platform as well as the applicability of smart city, especially care services. Furthermore, the paper developed discussions on the standardization of the city in terms of political and institutional improvements, utilization of personal information and public data as well as ways of institutional improvement centering on social security information system. This paper highlights the importance of implementing the digitally based community care and smart welfare city that our society is seeking to achieve. With regard to the social security platform based on behavioral design and the 7 principles(6W1H method), the present paper has the limitation of dealing only with smart cities in the fields of healthcare, medicine, and welfare. Therefore, further studies are needed to investigate the effects of smart cities in other fields and to consider the application and utilization of technologies in various aspects and the corresponding impact on our society. It is expected that this paper will suggest the future course and vision not only for smart cities but also for the social security and welfare system and thereby make some contribution to improving the quality of people's lives through the requisite adjustments made in each relevant field.