@inproceedings{
 title = {A Lightweight Framework for Research Data Management},
 type = {inproceedings},
 year = {2019},
 pages = {1-4},
 publisher = {Association for Computing Machinery (ACM)},
 id = {5fc03501-5af9-326b-8c71-d2f8a757554f},
 created = {2019-10-01T17:20:27.382Z},
 accessed = {2019-08-27},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 last_modified = {2020-05-11T14:43:31.431Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Nikolov2019},
 private_publication = {false},
 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.},
 bibtype = {inproceedings},
 author = {Nikolov, Dimitar and Tuna, Esen},
 doi = {10.1145/3332186.3333157},
 booktitle = {Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) (PEARC '19)}
}

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