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Accessing Data from Ocean Observatories

Accessing Data from Ocean Observatories. Why Everything Will Keep Changing John Graybeal, MBARI. About Me. 19 years at NASA, 4 years at MBARI Led data team (3 yrs), data projects (4 yrs) Principal Investigator, Marine Metadata Interoperability (http://marinemetadata.org)

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Accessing Data from Ocean Observatories

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  1. Accessing DatafromOcean Observatories Why Everything Will Keep Changing John Graybeal, MBARI

  2. About Me • 19 years at NASA, 4 years at MBARI • Led data team (3 yrs), data projects (4 yrs) • Principal Investigator, Marine Metadata Interoperability (http://marinemetadata.org) • ORION Cyberinfrastructure Committee

  3. The Situation • Ocean.US / IOOS • ORION / OOI • NEPTUNE, PIONEER • MARS, VENUS

  4. The Schedule • 2005 • MARS (starts) • IOOS (planning) • 2006 • MARS (continues) • OOI (starts?) • IOOS (kind of starts?) • 2007 • OOI (starts) • IOOS (starts?) • 2008 • OOI (continues) • IOOS (continues?)

  5. The Data • Regular observations (think meteorology) • Model outputs (think outputs) • Observing campaigns • Irregular data sets

  6. Data Repositories • Big centralized archives • Domain-specific collections • Observatory records • Local data sets (accessible or otherwise)

  7. Data Access (Overview) • Call someone and ask them to send it • Call someone to find out where it is • Use a catalog (GCMD, OPeNDAP, …) • Use Google

  8. Data Access (Detailed) • FTP or download (in standard format?) • DODS/OPeNDAP (gridded data) • Live Access Server (files and plots) • Web Services (think http on steroids)

  9. Data Access Examples • LOBO: Web interface to a data set • AOSN: Web (LAS) interface to a collection • SSDS: Web services to a repository • MMI: Web services to multiple repositories

  10. What Will Drive Change • Increase Access: More data sets • Decrease Access: Security • Automate Access: Workflow • Smarter Access: Semantic Awareness

  11. What Will Change • Available data sets (but not often) • Locations of data • Interfaces to find and access data • Applications to work with data

  12. So (for curricula), What, Then? • Expect dynamic interfaces • Assume (define?) required expertise • Design curricula around basic data sets • Look for structural commitments to data

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