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논문검색

KNLTER Network : Facilitating Global Data-Sharing

초록

영어

Reliable data sharing and long-term data archiving and reuse are becoming very important in global cooperative research. Concomitantly, many types of global data-based research have been conducted on the Long-Term Ecological Research (LTER) network, with the objective of getting it to respond effectively to future changes in ecology, environment, and climate, by monitoring long-term ecological and environmental data. Korean National Long-Term Ecological Research (KNLTER), however, lacks a system for performing data collection, management, curation, and publication, and therefore global cooperative research through global data sharing is difficult in Korea. In this paper, we analyze one of the best practices link models, the TERN network, and the global data-sharing trend in the LTER area. Further, we propose a link model and necessary technologies for KNLTER and suggest a possible future direction for KNLTER.

목차

Abstract
 1. Introduction
 2. Related Research
  2.1. DataONE – Research Data Sharing for Earth Science
  2.2. KNB – Representative Member Node of DataONE
  2.3. RDA – Global Research Data Sharing
 3. Best Practice: TERN Network
 4. KNLTER: Global Data Linking Methods and Technologies
  4.1. Metacat
  4.2. DOI
  4.3. Data License
  4.3. Data Platform Model
 5. Conclusions
 Acknowledgments
 References

저자정보

  • Taesang Huh National Institute of Supercomputing and Networking, KISTI, 245 Daehak-ro, Yuseong-gu, Daejeon 34141, KOREA
  • Sunil Ahn National Institute of Supercomputing and Networking, KISTI, 245 Daehak-ro, Yuseong-gu, Daejeon 34141, KOREA
  • Dukyun Nam National Institute of Supercomputing and Networking, KISTI, 245 Daehak-ro, Yuseong-gu, Daejeon 34141, KOREA
  • Hoe-Kyung Jung Dept. of Computer Engineering, Pai Chai University, Doma2-Dong, Seo-gu, Daejeon 35345, KOREA

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