1. Considerations for Regional Data Collection, Sharing and Exchange Bruce Schmidt StreamNet Program Manager Pacific States Marine Fisheries Commission Presentation to CBFWA Members Advisory Group May 18, 2009 White Paper: www.streamnet.org

2. If everyone wants a regional data delivery system… 2000 BiOp RPA 198 2002 Council Contract with SAIC CBCIS / NED 2008 BiOp RPA 72 2006 Col. Basin Data Center Fish and Wildlife Program Why isn’t there one?

3. Need for Shared Data Legal: Remand, US v OR, PST, etc. ESA Recovery Planning Coordinated Monitoring Population Assessments (VSP) Inter-jurisdictional Management Co- management Listing- Delisting Decisions Increasing Interest in Data Sharing BiOp Compliance

4. Regional Data Systems Functional and Proposed SAIC CBCIS Columbia Basin Data Center NED & PNAMP Columbia Basin Center of Knowledge 2002 BiOp RPA 198 StreamNet PNW Water Quality Data Exchange Fish Passage Center PTAGIS RMIS PACFIN RECFIN DART IBIS

5. Current Situation Data sources: Agencies / Tribes / Projects db Database Projects SOTRPopulation models Population AssessmentsSubbasin planning PlanningHLIs ManagementPublic, etc. Comprehensive Data Delivery System db ??

6. Data sources: field offices, research projects Database Project Agency Database 269 531 874 269 531 874 269 531 874

7. What would a comprehensive data delivery system look like? db … Multiple types of data from multiple sources, standardized by data type WaterHabitatFish db Habitat db Output Interface Data Management System dd Pacific Northwest Water Quality Data Exchange

8. Comprehensive data delivery db … Multiple types of data from multiple sources, standardized by data type WaterHabitatFish db Habitat db Output Interface Data Management System dd db

9. Comprehensive data delivery db … Multiple types of data from multiple sources, standardized by data type WaterHabitatFish db Habitat db Output Interface Data Management System dd db Data flow can be automated Functionally Equivalent!

10. Advantages of automation Efficiency, Speed Automatic data updates Accuracy Canned products Translation to regional format Any database technology

11. Comprehensive data delivery … Multiple types of data from multiple sources, standardized by data type WaterHabitatFish db Output Interface Data Management System standardsStandards

12. Comprehensive data delivery … Multiple types of data from multiple sources, standardized by data type WaterHabitatFish db Output Interface

13. How does the Data Sharing Guide help? Organize discussions Consider ALL components Provide a blueprint Identify needed support Assure that when a system is built, the data are there to deliver!

14. Approach: Non-prescriptive Recognizes multiple approaches

15. Approach: Content neutral Data management, any data type About the container, not the contents

16. Approach: Agency neutral Fish management, land management, environmental quality, etc.

17. Approach: A basic primer Provides a checklist of considerations Elementary Some already met

18. The Data Sharing Guide is intended to help development of coordinated data management, from field to highest reporting need Primary focus is on infrastructure to assure data availability

19. Previous Proposals Pitched the output tool Ignored getting data to the tool The Data Sharing Guide is intended to encourage consideration of all aspects

20. Any data system will need: Uninterrupted data flow, source to output

21. Data Flow Field data creation (local office/project) Regional data application Post data on the Web Describe full data set(metadata) Regional standards Agency data QA / QC Agency database system Local use of data Describe the data (metadata) Quality Assurance / Quality Control Input to electronic form GOAL Steps in data flow Post metadata on the Web Data interoperability

22. Data Flow Field data creation (local office/project) Regional data application Post data on the Web Describe full data set(metadata) Regional standards Agency data QA / QC Agency database system Local use of data Describe the data (metadata) Quality Assurance / Quality Control Input to electronic form GOAL Steps in data flow Post metadata on the Web Data interoperability

23. Data Flow Field data creation (local office/project) Regional data application Post data on the Web Describe full data set(metadata) Regional standards Agency data QA / QC Agency database system Local use of data Describe the data (metadata) Quality Assurance / Quality Control Input to electronic form GOAL Steps in data flow Post metadata on the Web Data interoperability

24. Data Flow Field data creation (local office/project) Regional data application Post data on the Web Describe full data set(metadata) Regional standards Agency data QA / QC Agency database system Local use of data Describe the data (metadata) Quality Assurance / Quality Control Input to electronic form GOAL Steps in data flow Post metadata on the Web Data interoperability Any missed step can prevent data flow! Significant effort to bridge the gaps!

25. Data validated by agency Any data system will need:

26. Data and metadata on the Internet Any data system will need:

27. To be useful, shared data on the Internet must be machine readable! Database: Access SQL Server My SQL Oracle GIS Portable Document Format (.pdf) Word Processing: Word Perfect Word Spread- sheet: Excel Etc. Extensible Markup Language (XML) Delimited Text (ASCII)

28. Data roll together Common definitions & formats, or convertible to standard Any data system will need:

29. All steps must be in place for seamless data delivery We can implement these steps before deciding on a data sharing tool

30. Roles Sampling Crews Sampling Agencies Policy Makers Regional Data Users Database Projects Funding Entities

31. Data Collectors (field crews) Sample Enter the data Quality control Data maintenance Answer local questions

32. Data Collecting Agencies/Projects Establish procedures, standards Agency data systems Post data Select the posting approach Biological and IT responsibilities

33. Funding / recommending entities Negotiate methods data disposition Contract language Support data infrastructure

34. Regional policy makers Priorities Policies to encourage data sharing Agency commitments

35. Database projects Technical guidance Systems development Perform data tasks for agencies Support regional data needs Manage data channels

36. Data Sharing Guide will: Inform development of regional data system Assure all steps are in place (infrastructure) Help us get started

37. Questions? Funded by:Through: Fish and Wildlife Program Administered by: www.streamnet.org