HDF Studio

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HDF and HDF-EOS Workshop XVII (2014)
John Readey

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  • Limitations of HDFView as a data sharing platform
  • HDF Studio

    1. 1. www.hdfgroup.org The HDF Group ESIP Summer Meeting HDF Studio John Readey The HDF Group 1July 8 – 11, 2014
    2. 2. www.hdfgroup.orgESIP Summer Meeting About Me (briefly) July 8 – 11, 2014 2 • 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
    3. 3. www.hdfgroup.orgESIP Summer Meeting What is HDF Studio? July 8 – 11, 2014 3 • 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)
    4. 4. www.hdfgroup.orgESIP Summer Meeting Limitations of HDFView as a Platform July 8 – 11, 2014 4 • 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
    5. 5. www.hdfgroup.orgESIP Summer Meeting HDF Studio Architecture July 8 – 11, 2014 5
    6. 6. www.hdfgroup.orgESIP Summer Meeting HDF Studio Components July 8 – 11, 2014 6 • 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
    7. 7. www.hdfgroup.orgESIP Summer Meeting Challenges… July 8 – 11, 2014 7 • 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)
    8. 8. www.hdfgroup.orgESIP Summer Meeting Where we are now… July 8 – 11, 2014 8 • Just getting started! • Welcome: • Comments • Cool ideas • Areas for collaboration • Intent is to release updates incrementally
    9. 9. www.hdfgroup.orgESIP Summer Meeting Questions? July 8 – 11, 2014 9

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