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

Mamiko Matsubayashi; Keiko Kurata

doi:10.1109/BigData.2017.8258475

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

Mamiko Matsubayashi, Keiko Kurata

Department of Library and Information Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (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 language	English
Title of host publication	Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
Editors	Jian-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
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4407-4409
Number of pages	3
ISBN (Electronic)	9781538627143
DOIs	https://doi.org/10.1109/BigData.2017.8258475
Publication status	Published - 2017 Jul 1
Event	5th IEEE International Conference on Big Data, Big Data 2017 - Boston, United States Duration: 2017 Dec 11 → 2017 Dec 14

Publication series

Name	Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
Volume	2018-January

Other

Other	5th IEEE International Conference on Big Data, Big Data 2017
Country/Territory	United States
City	Boston
Period	17/12/11 → 17/12/14

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

Access to Document

10.1109/BigData.2017.8258475

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

Conceptual design for comprehensive research support platform: Successful research data management generating big data from little data. / Matsubayashi, Mamiko; Kurata, Keiko.
Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. ed. / Jian-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. Institute of Electrical and Electronics Engineers Inc., 2017. p. 4407-4409 (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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. Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 4407-4409, 5th IEEE International Conference on Big Data, Big Data 2017, Boston, United States, 17/12/11. https://doi.org/10.1109/BigData.2017.8258475

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

Matsubayashi, Mamiko ; Kurata, Keiko. / Conceptual design for comprehensive research support platform : Successful research data management generating big data from little data. Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. editor / Jian-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. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 4407-4409 (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017).

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title = "Conceptual design for comprehensive research support platform: Successful research data management generating big data from little data",

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).",

keywords = "data archive, data sharing, open science, research data management, scholarly communication",

author = "Mamiko Matsubayashi and Keiko Kurata",

note = "Funding Information: ACKNOWLEDGMENT This work was supported by JSPS KAKENHI Grant Number JP26280121. Publisher Copyright: {\textcopyright} 2017 IEEE.; 5th IEEE International Conference on Big Data, Big Data 2017 ; Conference date: 11-12-2017 Through 14-12-2017",

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doi = "10.1109/BigData.2017.8258475",

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editor = "Jian-Yun Nie and Zoran Obradovic and Toyotaro Suzumura and Rumi Ghosh and Raghunath Nambiar and Chonggang Wang and Hui Zang and Ricardo Baeza-Yates and Ricardo Baeza-Yates and Xiaohua Hu and Jeremy Kepner and Alfredo Cuzzocrea and Jian Tang and Masashi Toyoda",

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A2 - Nie, Jian-Yun

A2 - Obradovic, Zoran

A2 - Suzumura, Toyotaro

A2 - Ghosh, Rumi

A2 - Nambiar, Raghunath

A2 - Wang, Chonggang

A2 - Zang, Hui

A2 - Baeza-Yates, Ricardo

A2 - Hu, Xiaohua

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PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

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

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