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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 - PowerPoint PPT Presentation
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Data Sharing Across Agencies:A guide to getting on the same page
Bruce SchmidtPacific States Marine Fisheries Commission
Presentation to
Oregon Chapter, AFSFebruary, 2010
www.streamnet.org
CrossJurisdictions
Legal: Remand, US v. OR, PST,
etc.
ESARecoveryPlanning
Coordinated Monitoring
PopulationAssessments
(VSP)
Inter-jurisdictionalManagement
Co-management
High Level Indicators,
SOTR
Increasing Wide-scale Programs
BiOpCompliance
NeedShared
Data
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
2002Council Contract
with SAIC
Talk of a Comprehensive Regional Data Delivery System…
2000 BiOpRPA 198
CBCIS/ NED
2008 BiOpRPA 72
2006Col. Basin
Data CenterFish and Wildlife
Program
So why isn’t there one?NOAA
Guidance
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
…Multiple types of data from multiple sources, standardized by data type
Fish Habitat Water
db db db db db db db db db db db db
OutputTool
RegionalData
Access
Standards Standards Standards
Others
Use Regional Data Projects
db
…Multiple types of data from multiple sources, standardized by data type
WaterHabitatFish
db db db db db db
db
db
OutputTool
RegionalData
Access
dd
dbdbdbdbdb
Others
Pacific Northwest Water Quality Data ExchangeStreamNet
But, Current Reality is more like this:
db
Data sources: field offices, research projects, etc.
DatabaseProject
AgencyDatabase
2 6 95 3 18 7 4
2 6 95 3 18 7 4
2 6 95 3 18 7 4
Consolidated v. Individual Offices Approach
Most Expedient
db
…Multiple types of data from multiple sources, standardized by data type
WaterHabitatFish
db db db db db db
db
db
OutputTool
RegionalData
Access
dd
dbdbdbdbdb
Others
The Essential Driver of a Comprehensive Data Delivery System
db
…Multiple types of data from multiple sources, standardized by data type
WaterHabitatFish
db db db db db db
db
db
OutputTool
RegionalData
Access
dd
dbdbdbdbdb
Data flow can be automated
Others
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??
…Multiple types of data from multiple sources, standardized by data type
Water Habitat Fish
db db db db db db db db db db db db
Others
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
Field data creation (local office/project)
Regional data application
Regional standards
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
GOAL
Steps in Data Flow
Post data on the Web
Data interoperability
Data Flow
Field data creation (local office/project)
Regional data application
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
GOAL
Steps in Data Flow
Regional standards
Data interoperability
Data Flow
Field data creation (local office/project)
Regional data application
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
GOAL
Steps in Data Flow
Regional standards
Data interoperabilityAny missed step can prevent data flow!
Significant effort to bridge the gaps!
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)
X . Y .238 51375 28265 44
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
XMLSQL
DatabaseSpreadsheet
ASCII
Word Processing
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
SamplingCrews
SamplingAgencies
FundingEntities
RegionalData Users
DatabaseProjects
PolicyMakers
RolesCreate the dataData EntryQADescribe the dataMaintain the data
Establish proceduresSet standards, codesAgency data systemsPost data / metadataBiological & data mgt. responsibilities
Negotiate key issues Metrics Methods Data dispositionContract languageSupport data automation
Set prioritiesPolicies to remove obstacles to data sharingAgency support
Technical assistanceSystem developmentData tasks for agenciesPost data & metadataFeed regional data tools
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?
Funded by: Through:
Fish and Wildlife Program
Administered by:
www.streamnet.org
Photographs courtesy of CalFish
