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A Lightweight Framework for Research Data Management

Published: 28 July 2019 Publication History

Abstract

We describe a framework for managing live research data involving two major components. First, a system for the scalable scheduling and execution of automated policies for moving, organizing, and archiving data. Second, a system for managing metadata to facilitate curation and discovery with minimal change to existing workflows. Our approach is guided by four main principles: 1) to be non-invasive and to allow for easy integration into existing workflows and computing environments; 2) to be built on established, cloud-aware, open-source tools; 3) to be easily extensible and configurable, and thus, adaptable to different academic disciplines; and 4) to integrate with and take advantage of infrastructure and services available on academic campuses and research computing environments. These principles give our solution a well-defined place along the spectrum of research data management software such as sophisticated electronic lab notebooks and science gate-ways. Our lightweight and flexible data management framework provides for curation and preservation of research data within a lab, department or university cyberinfrastructure.

References

[1]
Declan Butler. 2005. A new leaf. Nature 436 (06 07 2005), 20--21.
[2]
I. Foster. 2011. Globus Online: Accelerating and Democratizing Science through Cloud-Based Services. IEEE Internet Computing 15, 3 (May 2011), 70--73.
[3]
Apache Foundation. 2019. Apache Airflow. https://airflow.apache.org. (2019). {Online; accessed 20-February-2019}.
[4]
Arcot Rajasekar, Mike Wan, Reagan Moore, and Wayne Schroeder. 2006. A prototype rule-based distributed data management system. (2006).
[5]
R. W. Watson. 2005. High performance storage system scalability: architecture, implementation and experience. In 22nd IEEE / 13th NASA Goddard Conference on Mass Storage Systems and Technologies (MSST'05). IEEE Computer Society, Washington, DC, USA, 145--159.
[6]
Nancy Wilkins-Diehr. 2007. Special Issue: Science Gateways --- Common Community Interfaces to Grid Resources. Concurrency and Computation: Practice and Experience 19, 6 (2007), 743--749. arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.1098

Cited By

View all
  • (2023)Scholarly Data Share 2.0: Granular Access to Research DataPractice and Experience in Advanced Research Computing 2023: Computing for the Common Good10.1145/3569951.3597585(177-180)Online publication date: 23-Jul-2023
  • (2022)Scholarly Data Share: A Model for Sharing Big Data in Academic ResearchPractice and Experience in Advanced Research Computing 2022: Revolutionary: Computing, Connections, You10.1145/3491418.3530297(1-8)Online publication date: 8-Jul-2022
  • (2021)Automating Research Data Management Using Machine-Actionable Data Management PlansACM Transactions on Management Information Systems10.1145/349039613:2(1-22)Online publication date: 11-Dec-2021

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Information & Contributors

Information

Published In

cover image ACM Other conferences
PEARC '19: Practice and Experience in Advanced Research Computing 2019: Rise of the Machines (learning)
July 2019
775 pages
ISBN:9781450372275
DOI:10.1145/3332186
  • General Chair:
  • Tom Furlani
Permission to make digital or hard copies of all or part 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 components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 July 2019

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Author Tags

  1. data curation
  2. data management
  3. data policies
  4. metadata management

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  • Research-article
  • Research
  • Refereed limited

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PEARC '19

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Overall Acceptance Rate 133 of 202 submissions, 66%

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Cited By

View all
  • (2023)Scholarly Data Share 2.0: Granular Access to Research DataPractice and Experience in Advanced Research Computing 2023: Computing for the Common Good10.1145/3569951.3597585(177-180)Online publication date: 23-Jul-2023
  • (2022)Scholarly Data Share: A Model for Sharing Big Data in Academic ResearchPractice and Experience in Advanced Research Computing 2022: Revolutionary: Computing, Connections, You10.1145/3491418.3530297(1-8)Online publication date: 8-Jul-2022
  • (2021)Automating Research Data Management Using Machine-Actionable Data Management PlansACM Transactions on Management Information Systems10.1145/349039613:2(1-22)Online publication date: 11-Dec-2021

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