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Cloud Optimized Data FormatsCloud computing offers the promise of being able to analyze Big Data earth Observations at scale, by allowing scientists to deploy many nodes at once to analyze the data. However, in order to take full advantage of cloud scalability, it is often necessary to reorganize and reformat the data to enable fine-grained, parallel access to the data in Web Object Storage. NASA recently conducted a study of several formats that are optimized for analysis in the cloud: Parquet, zarr, HDF (Hierarchical Data Format) in the Cloud, and Cloud-Optimized GeoTIFF (Tagged Image File Format). They were compared against non-cloud-optimized formats, netCDF (network Common Data Form) and GeoTIFF, with criteria based both on stewardship and analysis performance.
Document ID
20205000309
Acquisition Source
Goddard Space Flight Center
Document Type
Presentation
Authors
Christopher Lynnes
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Patrick Michael Quinn
(E)
Chris Durbin
(Raytheon (United States) Waltham, Massachusetts, United States)
Dana Leigh Shum
(Raytheon (United States) Waltham, Massachusetts, United States)
Date Acquired
April 1, 2020
Subject Category
Earth Resources And Remote Sensing
Meeting Information
Meeting: 49th Meeting of the Working Group on Information Systems & Services
Location: Virtual
Country: US
Start Date: April 21, 2020
End Date: April 24, 2020
Sponsors: Committee on Earth Obersvation Satellites (CEOS)
Funding Number(s)
WBS: 656052.04.05.01
Distribution Limits
Public
Copyright
Public Use Permitted.
Technical Review
Single Expert
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