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

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.99-108
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• 2017

Open Science is evolving not only to share research results, but also to open the research process. We are developing the EDISON platform for the spread of open science in computational science and engineering. The EDISON platform provides online simulation services developed by computational science and engineering researchers. It also provides an environment for sharing source code, data, and related research publications. An effective simulation software registration management system is required for successful service on the EDISON platform. In this paper, we proposes a simulation software management system to provide online simulation service through EDISON platform. The proposed system allows the developer to register the simulation software on the EDISON platform without administrator intervention and effectively build a web-based simulation environment.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2073-2081
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• 2021

Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by simultaneously playing pioneering and gatekeeping roles. The application of deep learning technology in medicine is sometimes restricted by ethical or legal issues, including patient privacy and confidentiality, data ownership, and limitations in patient agreement. In this paper, we present an open platform, MI2RLNet, for sharing source code and various pre-trained weights for models to use in downstream tasks, including education, application, and transfer learning, to encourage deep learning research in radiology. In addition, we describe how to use this open platform in the GitHub environment. Our source code and models may contribute to further deep learning research in radiology, which may facilitate applications in medicine and healthcare, especially in medical imaging, in the near future. All code is available at https://github.com/mi2rl/MI2RLNet.

• Journal of Sensor Science and Technology
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• v.20 no.4
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• pp.272-278
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• 2011

Recently, the performance of binaural hearing aids is rapidly improved with the technology advancement of wireless communication, digital signal processing, and integrated circuit design. However, the previous hearing aids developer platforms can't be applied to binaural hearing aids developing, because it has no consideration for wireless communication and binaural hearing control. Also, the previous developer platforms are not easy to use for the algorithm development, because programming languages are limited. In this paper, we designed and implemented the open platform board for binaural hearing aids developing. The designed board can be programmed by general programming language and can be used wireless communication module. In order to verify the designed open platform board, we used the volume control algorithm using two open platform board. As a result of experiment, we verified the performance of designed and implemented open platform board that was successfully operated the binaural hearing control and the wireless communication.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2434-2454
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• 2021

This paper developed the software testing factory-cloud testing platform (STF-CTP) to address the software compatible issues in various smart devices. Software developers who only require uploading the application under test (AUT) and test script can test plenty of smart devices in STF-CTP. The challenge for the cloud test platform is how to optimize the resource and increase the performance in the limited resource. This paper proposed a new scheduling mechanism and a new process of the system operation which is based on the OpenStack platform. We decrease about 40% memory usage of OpenStack server, increase 3% to 10% Android device usage of STF-CTP, enhance about 80% test job throughput and reduces about 40% test job average waiting time.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1183-1191
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• 2017

In order to support the service efficiently, a Science and Technology information platform that can share the same contents and technologies is needed. Therefore this study develop a platform that can use various contents and technologies as a common utilization factor, and support a fast and efficient service. In addition, It suggest examples of various APIs in a platform environment system that can utilize scientific data and technologies in various forms according to their use. Throughout the studies, various contents and technologies will be able to connect and interact with each other through the API Gateway on the platform, as well as to integrate Science and Technology contents based on identified researchers, institutions, and terminology data.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.202-204
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• 2018

2018년 현재 한국과학기술정보연구원(KISTI)은 계산과학공학 플랫폼 기반으로 온라인 시뮬레이션이 가능한 EDISON(EDucation-research Integration through Simulation On the Net) 서비스를 제공하고 있다. 해당 플랫폼 서비스는 7개 전문분야(전산의학, 전산설계, 전산열유체, 구조동역학, 계산화학, 나노물리, 도시환경)의 학생 및 연구자들이 학습 및 시뮬레이션을 실행하고 결과를 활용할 수 있도록 지원하고 있다. 하지만 EDISON 플랫폼은 시뮬레이션 서비스에 초점을 맞춰 개발과 서비스를 제공했기 때문에 국내외 MOOC(Massive Open Online Course) 서비스들에 비해 아직 교육 콘텐츠가 부족하다. 그리하여 본 논문에서는 계산과학공학 플랫폼에 교육 콘텐츠를 체계적으로 제공하기 위한 커리큘럼 서비스를 설계 및 제안하였다.

• Journal of Platform Technology
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• v.6 no.3
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• pp.31-37
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• 2018

Recently, the platforms for open science are being developed for helping researchers and scientists who are interested in convergence studies. This paper is focused on deriving a design method for an integrated architecture for knowledge infrastructure in science and technology and to set up the integration level of details and association between data and services in the integrated architecture. To facilitate the open science in research lifecycle, reconstructing individual services into modular and independent function blocks needs to be reusable and interoperable. The proposed design methodology is used for manipulating a service integration for the convergence service of S&T(Science and Technology) knowledge infrastructure. It can support to seamlessly access computing resources and the research results including artifacts digitally enabled scholars, researchers, and engineers participating in multidisciplinary collaborations.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.1-4
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• 2022

As computers can express and utilize information in a semantic dimension different from the real world, humans have opened the door to the digital world and have played a pivotal role in the transformation of the human habitual environment. Using metaverse, it can be possible to predict concepts such as virtual currency, artificial intelligence, and virtual reality, which have now become possible for practical systemic visualization. In order to implement the metaverse in the realm of technology, it requires not only a multifaceted discussion on the platform, but also research on an architect that can include the intrinsic complexity of the metaverse. In this paper, we discuss the architecture for an open metaverse platform based on convergence wrapping that can converge various contents into one space, and propose a comprehensive platform design.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.123-130
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• 2018

With the emergence of a new paradigm called Open Science and Big Data, the need for data sharing and collaboration is also emerging in the computational science field. This paper, we analyzed data-driven research cases for computational science by field; material design, bioinformatics, high energy physics. We also studied the characteristics of the computational science data and the data management issues. To manage computational science data effectively it is required to have data quality management, increased data reliability, flexibility to support a variety of data types, and tools for analysis and linkage to the computing infrastructure. In addition, we analyzed trends of platform technology for efficient sharing and management of computational science data. The main contribution of this paper is to review the various computational science data repositories and related platform technologies to analyze the characteristics of computational science data and the problems of data management, and to present design considerations for building a future computational science data platform.