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

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

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

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

Current Situation SOTR Population models Population. Comprehensive Data Assessments Subbasin planning Planning Delivery System. Current Situation SOTR Population models Population. Comprehensive Data Assessments Subbasin planning Planning Delivery System. HLIs Management Public, etc. Database Projects ? db db Data sources: Agencies / Tribes / Projects

Database Project Agency Database 2 6 9 5 3 1 8 7 4 Data Database Project Agency Database 2 6 9 5 3 1 8 7 4 Data sources: field offices, research projects

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

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

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

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

Comprehensive data delivery Output Interface Data Management System standards Standards Water db db db Comprehensive data delivery Output Interface Data Management System standards Standards Water db db db Standards Habitat db db Fish db db db … Multiple types of data from multiple sources, standardized by data type

Comprehensive data delivery Output Interface Water db db db Habitat db db Fish db Comprehensive data delivery Output Interface Water db db db Habitat db db Fish db db db … Multiple types of data from multiple sources, standardized by data type

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

Approach: n Non-prescriptive n Recognizes multiple approaches Approach: n Non-prescriptive n Recognizes multiple approaches

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

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

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

The Data Sharing Guide is intended to help development of coordinated data management, from 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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Regional policy makers n Priorities n Policies to encourage data sharing n Agency commitments Regional policy makers n Priorities n Policies to encourage data sharing n Agency commitments

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

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

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