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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
Published on: November 22, 2019
A customizable data management framework for high-repetition-rate high-energy-density science
M J-E Manuel1, A Keller1, E Linsenmayer1
1General Atomics, San Diego, California 92121, USA.
Abstract:
The high-energy-density (HED) physics community is moving toward a new paradigm of high-repetition-rate (HRR) operation. To fully leverage the scientific power of HRR HED facilities, all of the components of each subsystem (laser, targetry, and performance diagnostics) must be connected and synchronized in a reliable and robust manner while the data acquired are tagged and archived in real time. To this end, GA has begun developing a generalized NoSQL-database framework, the MongoDB repository for information and archiving. An organizational strategy has been developed that shifts HED data organization from a shot-based to a diagnostic-based approach in order to increase archival and retrieval efficiency that lends itself to optimization applications. This work is a first step in pushing HRR HED science toward data management solutions that emphasize machine actionability and aim to stimulate community engagement to define data standards in HED science.
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