• Asian Journal of Innovation and Policy
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• v.4 no.3
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• pp.381-396
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• 2015

Cyberinfrastructure is a research infrastructure that provides an environment in which research communities can get access to distributed resources and collaborate at unprecedented levels of computation, storage, and network capacity. The Worldwide LHC Computing Grid (WLCG) is a global collaborative project of computing or data centers that enables access to scientific data generated by the Large Hadron Collider (LHC) experiments at CERN. This case study analyzes the WLCG as a model of cyberinfrastructure in research collaboration. WLCG provides a useful case of how cyberinfrastructure can work in providing an infrastructure for collaborative researches under data-intensive paradigm. Cyberinfrastructure plays the critical role of facilitating collaboration of diverse and widely separated communities of researchers. Data-intensive science requires new strategies for research support and significant development of cyberinfrastructure. The sustainability of WLCG depends on the resources of partner organizations and virtual organizations at international levels, essential for research collaboration.

• IE interfaces
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• v.22 no.2
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• pp.174-184
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• 2009

As R&D environment was changed, the research through Cyberinfrastructure emerged as a new paradigm. Advanced countries such as U.S. and U.K. invested heavily in the system for advancing R&D by building national Cyberinfrastructure. It is required to analyze how to build and utilize Cyberinfrastructure in science and technology. This paper aims to investigate and analyze the utilization status and demand of Cyberinfrastructure and to propose directions for operating it in Korea. This study is expected to be a principle foundation for decision making about developing it.

• Journal of Scientific & Technological Knowledge Infrastructure
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• s.13
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• pp.40-47
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• 2004

최근 NSF는 Cyberinfrastructure를 통한 과학과 공학의 혁명을 위해 산.학.연 전문가의 의견을 수렴하여 Blue-Ribbon Advisory Panel on Cyberinfrastructure(2003. 1)의 보고서를 통해 ACP(Advanced Cyberinfrastructure Program)을 제안하였다. ACP의 목표는 정보기술을 응용하여 과학 및 공학 연구에 혁신적인 발전을 가져오는데 있다. 본고에서는 미국, 유럽의 대표적 슈퍼컴퓨팅센터인 NCSA와 EPCC(Edenbugh Parallel Computing Center, 영국), HLRS(High Performance Computing Center Stuttgart, 독일)에 대한 분석을 수행해보고자 한다.

• Journal of Korea Technology Innovation Society
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• v.13 no.3
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• pp.423-445
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• 2010

This study purposes to suggest a next generation research and education environment which is possible by the linkage of two sectors based on cyberinfrastructure. It is to design a new research-education linkage system which can apply the results of R&D to the higher education in natural science and engineering areas. literatures were reviewed on new paradigms of R&D triggered by the advent of cyberinfrastrcuture. A couple of overseas and domestic cases of such paradigm were introduced. With the backgrounds of case studies and theoretical models, a new research-education linkage environment system was suggested. Specially e-AIRS system was introduced as an example of new model in Korea. In addition, some policy issues were discussed as related to the successful promotion of such programs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2084-2093
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• 2016

It is crucial to predict water temperature for aquatic ecosystem studies and management. In this paper, we first address challenging issues in predicting water temperature in a real time manner and propose a distributed computing model to address such issues. Then, we present an Artificial Neural Network (ANN)-based water temperature prediction model developed for the Soyang River and a cyberinfrastructure system called WT-Agabus to run such prediction models in an automated and real time manner. The ANN model is designed to use only weather forecast data (air temperature and rainfall) that can be obtained by invoking the weather forecasting system at Korea Meteorological Administration (KMA) and therefore can facilitate the automated and real time water temperature prediction. This paper also demonstrates how easily and efficiently the real time prediction can be implemented with the WT-Agabus prototype system.

• Smart Structures and Systems
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• v.1 no.1
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• pp.1-12
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• 2005

This paper describes the area of intelligent systems research as funded by the Civil and Mechanical Systems (CMS) Division of the National Science Foundation (NSF). With developments in computer science, information technology, sensing and control the design of typical machines and structures by civil and mechanical engineers is evolving toward intelligent systems that can sense, decide and act. This trend toward electro-mechanical design is well-established in modern machines (e.g. vehicles, robots, disk drives) and often referred to as mechatronics. More recently intelligent systems design is becoming an important aspect of structures, such as buildings and bridges. We briefly review recent developments in structural control, including the role that NSF has played in their development, and discuss on-going CMS activities in this area. In particular, we highlight the interdisciplinary initiative on Sensors and Sensor Networks and the Network for Earthquake Engineering Simulation (NEES). NEES is a distributed cyberinfrastructure to support earthquake engineering research, and provides the pioneering NEES grid computing environment for simulation, teleoperation, data collection and archiving, etc.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.11-14
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• 2018

본 논문에서는 다양한 과학기술 분야의 연구자들이 R&D 수행에 있어서 필요한 인프라로서 클라우드 서비스를 활발히 이용하도록 하기 위해서 요구되는 정책적 기술적 개선 방안을 도출하였다. 이를 위해서 R&D를 위한 클라우드 서비스의 해외 사례를 조사하고, 국내 출연(연) 대학 등 연구현장의 다양한 분야의 연구자들로부터 클라우드 서비스에 대한 인식 조사 및 수요 분석을 실시하였다. 이러한 조사 분석 결과 과학기술 및 공학 ICT 등 다양한 분야의 연구에서 요구되는 수요를 충족할 수 있는 클라우드 서비스의 필요성을 도출하였으며, 보안 및 행정제도 등에 있어서도 개선점을 도출할 수 있었다. 연구를 통하여 우리는 국가 R&D를 수행하는 연구자들이 기존 클라우드 서비스에 대한 제약을 해소하고 더 나은 연구환경을 지원받도록 하기 위한 R&D 사이버인프라스트럭쳐로서의 클라우드 서비스를 제안하였다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2075-2083
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• 2016

The real time IAQ (Indoor Air Quality) management is very important for large buildings and underground facilities such as subways because poor IAQ is immediately harmful to human health. Such IAQ management requires monitoring, prediction and control in an integrated and real time manner. In this paper, we present three PM10 hourly prediction models for such realtime IAQ management as both Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models. Both MLR and ANN models show good performances between 0.76 and 0.88 with respect to R (correlation coefficient) between the measured and predicted values, but the MLR models outperform the corresponding ANN models with respect to RMSE (root mean square error).

• Proceedings of the Korean Information Science Society Conference
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• 2010.06b
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• pp.231-235
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• 2010

요즘 들어 컴퓨터 처리 능력의 향상에 따라 사이버인프라스트럭처(Cyberinfrastructure)를 이용하는 계산과학이 주목을 받고 있다. 그 중에서도 대용량 데이터의 복잡한 계산과 시뮬레이션을 동반하는 계산화학 연구 분야에서의 컴퓨터 활용은 매우 중요하다. 계산화학을 간단하게 설명하자면 컴퓨터를 이용한 계산을 통하여 이론 화학의 문제를 다루는 화학의 한 분야라고 말할 수 있다. 계산화학 분야의 연구를 위하여 고성능 컴퓨터와 데이터를 처리, 분석하는 계산화학 도구는 이론연구자 및 실험연구자 모두에게 있어 필수적인 요소이다. 더불어 계산화학 연구자간의 협업과 원격지에 있는 사이버인프라스트럭처 자원의 활용을 위해 e-Science 환경에서의 연구 및 교육 환경이 개발되어야 한다. 이에, 본 논문에서는 한국과학기술정보연구원(KISTI)이 보유 및 운영하고 있는 사이버인프라스트럭처(고성능 컴퓨터, 초고속 네트워크)를 기반으로 컴퓨터에 익숙하지 않은 계산화학 관련 연구자 및 전공자들이 인터넷 상에서 계산화학 분야 교육을 받을 수 있는 e-Science 기반 계산화학 교육을 위한 환경을 설계하고자 한다. 이를 위해 1) 세계적으로 유명한 GridChem, CICC, NBCR 웹사이트를 이용하여 발표된 논문을 분석하였으며, 2) 분석된 결과를 가지고 주로 사용되는 계산화학 도구의 통계를 산출하여, 3) 이를 바탕으로 KISTI 사이버인프라스트럭처를 활용한 e-Science 기반 계산화학 교육 환경(e-Chem)을 설계하였다.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.187-192
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• 2023

The United States (US) National Science Foundation's (NSF's) National Ecological Observatory Network (NEON) is a continental-scale observation facility, constructed and operated by Battelle, that collects long-term ecological data to better understand and forecast how US ecosystems are changing. All data and samples are collected using standardized methods at 81 field sites across the US and are freely and openly available through the NEON data portal, application programming interface (API), and the NEON Biorepository. NSF led a decade-long design process with the research community, including numerous workshops to inform the key features of NEON, culminating in a formal final design review with an expert panel in 2009. The NEON construction phase began in 2012 and was completed in May 2019, when the observatory began the full operations phase. Full operations are defined as all 81 NEON sites completely built and fully operational, with data being collected using instrumented and observational methods. The intent of the NSF is for NEON operations to continue over a 30-year period. Each challenge encountered, problem solved, and risk realized on NEON offers up lessons learned for constructing and operating distributed ecological data collection infrastructure and data networks. NEON's construction phase included offices, labs, towers, aquatic instrumentation, terrestrial sampling plots, permits, development and testing of the instrumentation and associated cyberinfrastructure, and the development of community-supported collection plans. Although colocation of some sites with existing research sites and use of mostly "off the shelf" instrumentation was part of the design, successful completion of the construction phase required the development of new technologies and software for collecting and processing the hundreds of samples and 5.6 billion data records a day produced across NEON. Continued operation of NEON involves reexamining the decisions made in the past and using the input of the scientific community to evolve, upgrade, and improve data collection and resiliency at the field sites. Successes to date include improvements in flexibility and resilience for aquatic infrastructure designs, improved engagement with the scientific community that uses NEON data, and enhanced methods to deal with obsolescence of the instrumentation and infrastructure across the observatory.