Visualizing and Sharing Data with HDF Studio
Explore HDF Studio, a powerful set of software components designed to help users visualize, understand, and share large structured datasets. Learn about its features, limitations, architecture, components, and challenges related to authentication, performance, scalability, and reliability.
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Presentation Transcript
The HDF Group HDF Studio John Readey The HDF Group July 8 11, 2014 1 www.hdfgroup.org ESIP Summer Meeting
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 3rd party sellers AWS Diagnostic Tools The HDF Group: 2014 - ? Tools & Cloud Technology 2 www.hdfgroup.org July 8 11, 2014 ESIP Summer Meeting
What is HDF Studio? 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) 3 www.hdfgroup.org July 8 11, 2014 ESIP Summer Meeting
Limitations of HDFView as a Platform 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 4 www.hdfgroup.org July 8 11, 2014 ESIP Summer Meeting
HDF Studio Architecture 5 www.hdfgroup.org July 8 11, 2014 ESIP Summer Meeting
HDF Studio Components 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 6 www.hdfgroup.org July 8 11, 2014 ESIP Summer Meeting
Challenges 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) 7 www.hdfgroup.org July 8 11, 2014 ESIP Summer Meeting
Where we are now Just getting started! Welcome: Comments Cool ideas Areas for collaboration Intent is to release updates incrementally 8 www.hdfgroup.org July 8 11, 2014 ESIP Summer Meeting
Questions? 9 www.hdfgroup.org July 8 11, 2014 ESIP Summer Meeting
