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Data Sharing Across Agencies: A guide to getting on the same page. Bruce Schmidt Pacific States Marine Fisheries Commission Presentation to Oregon Chapter, AFS February, 2010. www.streamnet.org. Increasing Wide-scale Programs. Coordinated Monitoring. ESA Recovery Planning. Population
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Data Sharing Across Agencies:A guide to getting on the same page Bruce Schmidt Pacific States Marine Fisheries Commission Presentation to Oregon Chapter, AFS February, 2010 www.streamnet.org
Increasing Wide-scale Programs Coordinated Monitoring ESA Recovery Planning Population Assessments (VSP) Cross Jurisdictions Need Shared Data High Level Indicators, SOTR Inter-jurisdictional Management BiOp Compliance Co- management Legal: Remand, US v. OR, PST, etc.
Benefits of Sharing Data • Fosters collaboration • Expand scope of analyses (ESU, DPS) • Contributes to multi-agency processes (e.g., ESA analyses, recovery planning and list/delist decisions; co-management; etc.) • Could distribute cost of data collection
Talk of a Comprehensive Regional Data Delivery System… 2002 Council Contract with SAIC 2000 BiOp RPA 198 So why isn’t there one? NOAA Guidance 2008 BiOp RPA 72 2006 Col. Basin Data Center CBCIS / NED Fish and Wildlife Program
Impediments to Sharing Data • Sampling is focused • Do things differently • Data often not consolidated internally • Data not on Web • Hard for others to understand, use the data • Concerns over misuse, first use, etc. • Cost
Current Data Sharing Status: • Individual agencies (States, Tribes, Federal) • Independent • Different mandates • Sample different environments • Longstanding approaches • No mandate to share data • Little support, capability to share data
Current Data Sharing Status: • Wide scale database projects • Focused – specific data types • Not comprehensive
Current Data Sharing Status: • Proposed regional data delivery applications • Comprehensive • Never built, or not completed • Mechanisms to supply data not in place
Ideal Distributed Network Output Tool Regional Data Access Standards Standards Standards … Fish Habitat Water Others db db db db db db db db db db db db Multiple types of data from multiple sources, standardized by data type
Use Regional Data Projects But, Current Reality is more like this: Output Tool Regional Data Access Pacific Northwest Water Quality Data Exchange StreamNet db db db dd … Fish Habitat Water Others db db db db db db db db db db db db Multiple types of data from multiple sources, standardized by data type
Consolidated v. Individual Offices Approach Database Project Agency Database Data sources: field offices, research projects, etc.
Most Expedient Output Tool Regional Data Access db db dd … Fish Habitat Water Others db db db db db db db db db db db db Multiple types of data from multiple sources, standardized by data type
The Essential Driver of a Comprehensive Data Delivery System Output Tool Regional Data Access Data flow can be automated db db dd … Fish Habitat Water Others db db db db db db db db db db db db Multiple types of data from multiple sources, standardized by data type
Automation is the key! • Efficiency, Speed • Accuracy • Automatic data updates • Canned products • Translation to regional format • Essential for any data portal technology
The ultimate endpoint?? … Water Habitat Fish Others db db db db db db db db db db db db Multiple types of data from multiple sources, standardized by data type
Considerations for Regional Data Collection, Sharing and Exchange ‘The Data Sharing Guide’ A White Paper to: • Outline steps • Avoid overlooking critical steps • Describe roles entities play • Break it down: it’s not really that difficult ftp://ftp.streamnet.org/pub/streamnet/projman_files/Data_Sharing_Guide_2009-06-01.pdf
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!
The Data Sharing Guide addresses data flow from field to highest reporting need Non prescriptive Any data type Any agency Non-technical Primary focus is on infrastructure and processes to assure data accessibility
What’s Needed? 1. Uninterrupted data flow, source to output
Data Flow Steps in Data Flow Regional data application GOAL Data interoperability Regional standards Post data on the Web Post metadata on the Web Describe full data set (metadata) 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)
Data Flow Steps in Data Flow Regional data application GOAL Data interoperability Regional standards Post data on the Web Post metadata on the Web Describe full data set (metadata) 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)
Data Flow Steps in Data Flow Regional data application GOAL Any missed step can prevent data flow! Data interoperability Regional standards Post data on the Web Significant effort to bridge the gaps! Post metadata on the Web Describe full data set (metadata) 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)
What’s Needed? 1. Uninterrupted data flow, source to output 2. Data validated by agency
What’s Needed? 1. Uninterrupted data flow, source to output 2. Data validated by agency 3. Descriptive information (metadata)
What’s Needed? 1. Uninterrupted data flow, source to output 2. Data validated by agency 3. Descriptive information (metadata) 4. Data and metadata on the Internet
What’s Needed? 1. Uninterrupted data flow, source to output 2. Data validated by agency 3. Descriptive information (metadata) 4. Data and metadata on the Internet XML SQL Database Spreadsheet ASCII Word Processing PDF
What’s Needed? 1. Uninterrupted data flow, source to output 2. Data validated by agency 3. Descriptive information (metadata) 4. Data and metadata on the Internet 5. Data able to roll together Ideal: standard data collection, definition, codes Minimum: Data translate to a standard
All of this is needed for seamless data delivery to ANY regional tool
Sampling Crews Sampling Agencies Negotiate key issues Metrics Methods Data disposition Contract language Support data automation Technical assistance System development Data tasks for agencies Post data & metadata Feed regional data tools Set priorities Policies to remove obstacles to data sharing Agency support Create the data Data Entry QA Describe the data Maintain the data Establish procedures Set standards, codes Agency data systems Post data / metadata Biological & data mgt. responsibilities Roles Database Projects Funding Entities Policy Makers Regional Data Users
The Data Sharing Guide Will Help To: • Inform development of agency data systems • Inform development of a regional data system • Avoid skipping essential components • Get us started
Questions? www.streamnet.org Funded by: Through: Fish and Wildlife Program Administered by: Photographs courtesy of CalFish