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The Open Storage Network

April 21, 2021

Providing storage services to production users since the beginning of 2020 the Open Storage Network provides easy access and high bandwidth sharing of active scientific data between research institutions.

Increasing amounts of scientific data emerging from projects on all scales are spurring a search among research universities for high capacity (multi-petabyte) storage systems. While the US research community and its funding agencies have made significant strategic investments in advanced computing resources and high-speed network connectivity, storage for research data remains highly balkanized and under-resourced. This calls for a new type of cyberinfrastructure geared towards facilitating the simplification of data sharing and transfer.
The Open Storage Network (OSN), is a distributed data storage service that supports sharing of active scientific data between research institutions. Hosted at the MGHPCC, OSN provides high bandwidth delivery of large data sets allowing ready access to researchers who can leverage that data to train machine learning models, validate simulations, and perform statistical analysis of live data that would otherwise require navigation of administrative barriers and low bandwidth network pathways that are too often a barrier to data sharing. Among the data currently available on the OSN are high-quality infrared bioimaging data that is being used to train machine learning models; synthetic data from ocean models; the widely used Extracted Features Set from the Hathi Trust Digital Library; open-access earth sciences data from Pangeo; Geophysical Data from BCO-DMO, and other scientifically valuable data sets.
In this talk delivered at Supercomputing 2020, John Goodhue, an OSN Co-PI, and Executive Director of the MGHPCC (one of the nodes in the OSN) describes current deployment, which supports five petabytes of usable storage distributed across the US at sites including MGHPCC, SDSC, NCSA, Johns Hopkins University and RENCI; future plans, and information about how to participate.

Links

https://www.openstoragenetwork.org/

Research projects

A Future of Unmanned Aerial Vehicles
Yale Budget Lab
Volcanic Eruptions Impact on Stratospheric Chemistry & Ozone
The Rhode Island Coastal Hazards Analysis, Modeling, and Prediction System
Towards a Whole Brain Cellular Atlas
Tornado Path Detection
The Kempner Institute - Unlocking Intelligence
The Institute for Experiential AI
Taming the Energy Appetite of AI Models
Surface Behavior
Studying Highly Efficient Biological Solar Energy Systems
Software for Unreliable Quantum Computers
Simulating Large Biomolecular Assemblies
SEQer - Sequence Evaluation in Realtime
Revolutionizing Materials Design with Computational Modeling
Remote Sensing of Earth Systems
QuEra at the MGHPCC
Quantum Computing in Renewable Energy Development
Pulling Back the Quantum Curtain on ‘Weyl Fermions’
New Insights on Binary Black Holes
NeuraChip
Network Attached FPGAs in the OCT
Monte Carlo eXtreme (MCX) - a Physically-Accurate Photon Simulator
Modeling Hydrogels and Elastomers
Modeling Breast Cancer Spread
Measuring Neutrino Mass
Investigating Mantle Flow Through Analyses of Earthquake Wave Propagation
Impact of Marine Heatwaves on Coral Diversity
IceCube: Hunting Neutrinos
Genome Forecasting
Global Consequences of Warming-Induced Arctic River Changes
Fuzzing the Linux Kernel
Exact Gravitational Lensing by Rotating Black Holes
Evolution of Viral Infectious Disease
Evaluating Health Benefits of Stricter US Air Quality Standards
Ephemeral Stream Water Contributions to US Drainage Networks
Energy Transport and Ultrafast Spectroscopy Lab
Electron Heating in Kinetic-Alfvén-Wave Turbulence
Discovering Evolution’s Master Switches
Dexterous Robotic Hands
Developing Advanced Materials for a Sustainable Energy Future
Detecting Protein Concentrations in Assays
Denser Environments Cultivate Larger Galaxies
Deciphering Alzheimer's Disease
Dancing Frog Genomes
Cyber-Physical Communication Network Security
Avoiding Smash Hits
Analyzing the Gut Microbiome
Adaptive Deep Learning Systems Towards Edge Intelligence
Accelerating Rendering Power
ACAS X: A Family of Next-Generation Collision Avoidance Systems
Neurocognition at the Wu Tsai Institute, Yale
Computational Modeling of Biological Systems
Computational Molecular Ecology
Social Capital and Economic Mobility
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