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A Lightweight Framework for Research Data Management

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Published:28 July 2019Publication 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.

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  1. A Lightweight Framework for Research Data Management

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        • Published in

          cover image ACM Other conferences
          PEARC '19: Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning)
          July 2019
          775 pages
          ISBN:9781450372275
          DOI:10.1145/3332186
          • General Chair:
          • Tom Furlani

          Copyright © 2019 ACM

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 28 July 2019

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          • research-article
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          • Refereed limited

          Acceptance Rates

          Overall Acceptance Rate133of202submissions,66%

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