Panel Questions:
- What technical solutions exist that meet your academic project requirements?
- What technical solutions exist that meet corporate requirements?
- What requirements are unique to the academic environment?
- What requirements are unique to the corporate environment?
- Are there common approaches for managing large-scale collections?
John Orcutt, Ocean Observatories Initiative [home page]
- linking observational data and users
- uses message-based technology - this enables better enforcement of policy
- uses only cloud services
- has three components (1) deep sea nodes (2) coastal nodes (3) regional cable network
- 25 year operational lifetime
- transformative
- policy-based data systems
- rich data and metadata practices
- scalable architecture
- both geospatial and temporal enabled
Ed Kearns, National Climatic Data Center [PowerPoint presented by Kenneth Galluppi]
Laurin Herr, Cinegrid [PowerPoint]
- media convergence motivates CineGrid
- media technology is driven by 3 sectors - entertainment/media/the arts - science/medicine/education/research - military/intelligence/security/police
- 35mm is still the standard but digital films may never see this format
- hollywood studios now facing decisions about what to throw away - eg out-takes
- use RDF framework for objects
- use iRODS because of programmable microservices
Philip Maechling, Southern California Earthquake Center [PowerPoint]
- data is both observational and from simulations
- the majority of data is from simulations
- 2-way inter-dependence of data and models
- computer-generated models should always have associated verified and validated results and code must be included
- metadata strategies - tools for converting wikis, labels and entries into the metadata store
- advocates practical metadata standard - should be just enough to go from the data to the results
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