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Counting Fish, Tracking Dollars, Making Maps, and Collaborating on the Web with Reverse Proxy Server. NOAA WebShop 2004 July 27, 2004. Brendan Sylvander GIS Coordinator 206-860-3252 Issues, Concerns and Opportunities.

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Counting Fish, Tracking Dollars,

Making Maps, and Collaborating

on the Web with Reverse Proxy Server

NOAA WebShop 2004

July 27, 2004

Brendan Sylvander

GIS Coordinator


issues concerns and opportunities
Issues, Concerns and Opportunities
  • Where is the data (tabular and spatial), metadata, documents, analysis tools, discussions, links, project information and contacts needed for BIOP, M&E and Salmon Recovery activities
  • How do researchers, project managers, and the public better interface with the Web as a “working system” to store, find, analyze, collaborate, and share data and documents in a distributed environment
  • How can we get access to salmon and environmental data in a way easy for users to use and update? Example: Salmon Abundance, Genetics, Telemetry, Streamnet, OWEB, PRISM, CALFISH, SSHIAP, DART, EMAP, NRIS, hatcheries data, data not on the internet such as spreadsheets, ASCII files, paper, etc.

-How can we better utilize current software/hardware advancements with dedicated application development teams and analysts to support BIOP, M&E, CBCIS, and Pacific Coast Salmon Recovery Fund efforts

sdm mission statement

SDM Mission Statement

The Salmon Data Management team will, for NWFSC scientists and external customers:

Promote collaboration, communication, and coordination using e-Gov principles and enterprise-wide architecture framework to share and access internal and external information and data;

Provide and maintain “corporate” data, metadata, and applications;

Support analysis and project management services, and

Respond in a timely and effective manner.

sdm methodology
SDM Methodology
  • Awareness
  • Assessment
  • Design/Development/Testing
  • Transition/Training
  • Deployment
  • Maintenance
  • Project Planning
  • Documentation
  • Independent Validation and Verification
sdm development environment
SDM Development Environment
  • Setup and Baseline SDM Development Environment using “Corporate” Software and Hardware – Winter 2002/03

- Oracle 8.1.7 DBMS w/ 440 Gigs

- Oracle9iAS, Oracle Designer 6i, Oracle Developer

- ESRI SDE and IMS Web Server

- ESRI/ERDAS License Key Manager

- SDM Staff Fileserver 340 Gigs at Raid 5

- 5 Dual P4 1.7 GHz 1 Gig Workstations/Servers

- Network upgrades to 100 MB LAN and 1 Gig Fiber

sdm production environment
SDM Production Environment
  • Setup and Baseline SDM Production Environment using “Corporate” Software and Hardware – Spring 2003

- Oracle 8.1.7 and 9i DBMS Servers

- Oracle9iAS, Oracle Forms and Reports Servers

- ESRI SDE and IMS Web Servers

- 7 Dual P4 2.4 GHz 2 Gig Servers w/ 330 Gigs Raid

- Network upgrades to 1 Gig Fiber

pacific coastal salmon recovery fund database http webapps nwfsc noaa gov pcsrf
Pacific Coastal Salmon Recovery Fund Database
live demonstration of
Live Demonstration of…
  • NWFSC Salmonid Database Pilot V.1.4
  • PCSRF Public Database V.1.0
  • SDM Web Pilot V.1.3
lesson learned
Lesson Learned
  • Hardware is cheap – capability doubles every 18 months at same cost
  • MS Windows 2000 Server is easy to manage compared to Unix
  • NMFS Oracle support license has been great but now charge as used
  • ESRI GSA support license is expensive - $36K/yr for NWFSC
  • Reverse Proxy Server was difficult to setup with Oracle AS but now stable
  • Disaster recovery and backup for Development servers with Ghost at $54/server compared to typical $750/server is absolutely essential
  • Reusing Oracle Web Forms and Portals templates
  • Oracle Designer 6i Metadata Repository is invaluable
  • Documentation, documentation, documentation for DQA
  • 508 is a continuous improvement process and tradeoffs are involved
  • People and/or development costs are the most expensive component
  • Moving toward Mercury TestDirector automated testing, MS Visual Sourcesafe, and increased project management
  • Data quality issues for both primary and secondary data continue to pose the most difficult challenges in time and labor
  • Managing “change” for all of the above will be even more difficult over the life cycle