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Community-Driven Data Curation System for Reusability

Published: 23 May 2018 Publication History

Abstract

Due to recent data explosion, scientists invest most of their efforts in the collection of data needed for research. In this paper, we address the community-driven data curation system which is essential to enhancing data understandability and reusability, thereby reducing the efforts for data collection. The curation system focuses on the interlinking between data and their related literatures to capture and organize the associations among research output. The system also focuses on domain-specific contextual information to help users understand data. A global research group in protein study has adopted the system to build a community-driven curated database and established a guideline for scientific discovery.

References

[1]
CrowdFlower, 2017 Data Scientist Report, CrowdFlower 2017.
[2]
Ixchel Faniel et al., "A Context-driven Approach to Data Curation for Reuse," International Digital Curation Conference, Amsterdam, February 22, 2016.
[3]
RCSB PDB, http://www.rcsb.org/pdb/
[4]
GenBank, http://www.ncbi.nlm.nih.gov/genbank/
[5]
Hyun Lee et al. "Local Structural Elements in the Mostly Unstructured Transcriptional Activation Domain of Human p53," The Journal of Biological Chemistry, Vol. 275, No. 38, 2000, pp29426--294323.

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  • (2022)Digital PreservationHandbook of Research on Emerging Trends and Technologies in Librarianship10.4018/978-1-7998-9094-2.ch023(352-368)Online publication date: 2022

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  1. Community-Driven Data Curation System for Reusability

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    cover image ACM Conferences
    JCDL '18: Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries
    May 2018
    453 pages
    ISBN:9781450351782
    DOI:10.1145/3197026
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 23 May 2018

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    Author Tags

    1. community-driven data curation
    2. data-literature interlinking
    3. reusability
    4. trustworthiness

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    • KISTI Project K-18-L11

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    JCDL '18 Paper Acceptance Rate 26 of 71 submissions, 37%;
    Overall Acceptance Rate 415 of 1,482 submissions, 28%

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    • (2022)Digital PreservationHandbook of Research on Emerging Trends and Technologies in Librarianship10.4018/978-1-7998-9094-2.ch023(352-368)Online publication date: 2022

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