HDF Studio
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www.hdfgroup.o rg The HDF Group ESIP Summer Meeting HDF Studio John Readey The HDF Group 1 July 8 – 11, 2014
description
HDF Studio. John Readey The HDF Group. About Me (briefly). IBM/Portable Graphics: 1990-1997 3D graphics – OpenGL, Open Inventor DEC/ Intel: 1997 – 2006 Developed Intel Array Visualizer (first exposure to HDF!) Amazon.com : 2006-2014 FBA – Fulfillment for 3 rd party sellers - PowerPoint PPT Presentation
Transcript of HDF Studio
www.hdfgroup.org
The HDF Group
1ESIP Summer Meeting
HDF Studio
John ReadeyThe HDF Group
July 8 – 11, 2014
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About Me (briefly)
July 8 – 11, 2014
• IBM/Portable Graphics: 1990-1997• 3D graphics – OpenGL, Open Inventor
• DEC/Intel: 1997 – 2006• Developed Intel Array Visualizer (first exposure to
HDF!)• Amazon.com: 2006-2014• FBA – Fulfillment for 3rd party sellers• AWS – Diagnostic Tools
• The HDF Group: 2014 - ?• Tools & Cloud Technology
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What is HDF Studio?
July 8 – 11, 2014
• A set of server and client side software components that enables people to visualize and understand their data and to share that knowledge with others
• Details:• Focus on large structured datasets (HDF5)• Share not only the data, but representations of data• Utilize Web Standards (REST, JSON, Oauth)• Highly scalable (by collection size and number of
users)
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Limitations of HDFView as a Platform
July 8 – 11, 2014
• Data is shared by copying files (e.g. through FTP)• Views (graphs) are not persisted• Limited ability to handle large data sets• Does not address collections (related sets of files)• Extending (i.e. plugin architecture) is hard
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HDF Studio Architecture
July 8 – 11, 2014
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HDF Studio Components
July 8 – 11, 2014
• Cloud based repository for data• REST API for reading and writing data• OPeNDAP support• HDF5 library modified to use REST API• Studio Desktop App – view and edit data local or remote• Plugin model – extensions to Studio can be pulled in
dynamically from common repository
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Challenges…
July 8 – 11, 2014
• Authentication and permission model• Let people keep data private or share with others
• Performance• Goal – comparable to local file system
performance• Scalability• Support arbitrary numbers of users accessing
service• Arbitrary large data collection size
• Reliability• Service should work almost always (99.99%
uptime)
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Where we are now…
July 8 – 11, 2014
• Just getting started!• Welcome:• Comments• Cool ideas• Areas for collaboration
• Intent is to release updates incrementally
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Questions?
July 8 – 11, 2014
