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

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.100-102
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• 2023

최근 오픈 사이언스 문화가 확산됨에 따라 오픈 데이터, 오픈 소스 소프트웨어와 같은 공개된 리소스들을 효율적으로 공유 및 활용하기 위한 방법이 주목을 받고 있다. 본 논문에서는 연구 소프트웨어의 재현성을 향상시키기 위한 국가연구데이터커먼즈(KRDC)를 소개하고 다중 KRDC 클러스터 간 워크플로우 연계 방안을 제안한다. 국가연구데이터커먼즈는 연구 소프트웨어와 분석 환경인 인프라를 결합하여 함께 제공하는 서비스로, 멀티 노드 쿠버네티스(kubernetes) 클러스터를 기반으로 동작한다. 따라서, 서로 다른 KRDC 프레임워크에 존재하는 리소스들을 하나의 워크플로우로 연계하는 것은 복잡한 사용자 인증/인가 문제, 보안 상의 문제를 고려하여야 한다. 본 논문에서는 프록시(proxy) 앱을 사용하는 워크플로우 연계 기능을 제안하고, 이를 지원하기 위한 통합 인증, 인가 체계와 연계 방안을 구현한다. 제안하는 방법을 두 개의 KRDC 프레임워크를 대상으로 적용하여 제안 워크플로우 연계 방법의 유효함을 확인한다. 본 논문에서 제안하는 워크플로우 연계 방법과 시나리오는 실제 멀티 클러스터 연계 방안을 구현한 사례로, KRDC 프레임워크 뿐만 아니라 다양한 쿠버네티스 기반 리소스 연계에 활용할 수 있는 우수한 결과로 사료된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.311-313
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• 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
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• v.41 no.1
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• pp.465-486
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• 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.

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