Conceptual design for comprehensive research support platform: Successful research data management generating big data from little data

Mamiko Matsubayashi, Keiko Kurata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Data sharing, which is hot issues in scholarly communication, is regarded as generating big data from little data in little science. In this article, a conceptual framework for research support platform in university is proposed, by the survey of two cases of representative and subject-based data archives in Japan; Data Integration and Analysis System Program (DIAS) and Inter-university Upper atmosphere Global Observation Network (IUGONET).

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
EditorsJian-Yun Nie, Zoran Obradovic, Toyotaro Suzumura, Rumi Ghosh, Raghunath Nambiar, Chonggang Wang, Hui Zang, Ricardo Baeza-Yates, Ricardo Baeza-Yates, Xiaohua Hu, Jeremy Kepner, Alfredo Cuzzocrea, Jian Tang, Masashi Toyoda
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4407-4409
Number of pages3
ISBN (Electronic)9781538627143
DOIs
Publication statusPublished - 2017 Jul 1
Event5th IEEE International Conference on Big Data, Big Data 2017 - Boston, United States
Duration: 2017 Dec 112017 Dec 14

Publication series

NameProceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
Volume2018-January

Other

Other5th IEEE International Conference on Big Data, Big Data 2017
CountryUnited States
CityBoston
Period17/12/1117/12/14

Keywords

  • data archive
  • data sharing
  • open science
  • research data management
  • scholarly communication

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Control and Optimization

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  • Cite this

    Matsubayashi, M., & Kurata, K. (2017). Conceptual design for comprehensive research support platform: Successful research data management generating big data from little data. In J-Y. Nie, Z. Obradovic, T. Suzumura, R. Ghosh, R. Nambiar, C. Wang, H. Zang, R. Baeza-Yates, R. Baeza-Yates, X. Hu, J. Kepner, A. Cuzzocrea, J. Tang, & M. Toyoda (Eds.), Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017 (pp. 4407-4409). (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2017.8258475