Californias Surface Water Ambient Monitoring Program Data Management

California’s Surface Water Ambient Monitoring Program Data Management Systems Cassandra Lamerdin SWAMP Data Management Team Marine Pollution Studies Laboratory Moss Landing Marine Laboratories Moss Landing, California

Presentation Outline Ø SWAMP Database Goals Ø Start Up Principles Ø Data Elements Ø Database Systems Ø Questions

SWAMP Data Management Vision and Goals Ø Provide data of known & documented quality Ø Create & document systems which ensure data comparability Ø Make information available to all stakeholders in a timely manner Ø Facilitate the use of data for decision making processes

Guiding Principles Ø Capture analytical QC information in the SWAMP database Ø Do not store calculated values where possible Ø All samples will have unique geo-references and information about how samples were collected Ø Data enters database as “draft” and becomes public after SWAMP procedures are completed

Challenges We Faced Ø Varied study designs Ø Varied waterbody types Ø Multiple external sources of data Ø Analytical laboratories use performance-based methods Ø Multiple end-user groups and purposes

SWAMP Data Elements Discrete Field Measures Time Series Chemistry “SWAMP” Tissue Toxicity Biological Assessment

Responsibilities of SWAMP Database Management Team Ø Data Entry Training/Facilitation Ø Field data Ø Analytical data Ø Database Management/Quality Assurance Ø Work with each Regional Board individually Ø Comparability checking Ø Verification of Data Quality Indicators (QAMP) Ø Compliance Coding Ø Transfer data from Temporary to Permanent Ø Data Training/Accessibility Ø Regional boards Ø State board Ø Outside SWAMP groups

Data Facilitation Logistics Coordination Contracts/Work Orders Data Management Regional Water Boards State Water Boards Reporting/QC Analyte/Stations Maintenance Laboratories Sampling Crews DFG/Contractors Regional Water Boards

Data Flow Overview Samples Created in Field Lab Field Data Submission Lab Analytical Data Submission Lab Toxicity Data Submission Batch Loaded Data Entry Forms Batch Loaded Database (Temp side)

SWAMP Field Methods Course For Copies Contact George Nichol 916 -341 -5504 or gnichol@waterboards. ca. gov

Example SWAMP Data Sheet

SWAMP Data Entry Forms

Analytical Data Facilitation Ø Use Standard Formats/Training Manual Ø Lab Liaison develops a rapport with labs Ø Results in data being reported more efficiently Ø Ongoing training Ø Many labs do not have LIMS systems Ø Provide converters to assist with formatting SWAMP data Ø Upload to Database using Data Loading Program Ø Data Checkers (Batch Level and Global level) Ø More Automation of SWAMP Systems

Online Templates and Documentation http: //mpsl. mlml. calstate. edu/swamp. htm

SWAMP Data Systems SOPs

Data Flow Overview Samples Created in Field Lab Field Data Submission Lab Analytical Data Submission Data Verification by Lab Toxicity Data Submission Batch Loaded Data Entry Forms Data Verification by Field Crew Batch Loaded Database (Temp side) Preliminary Verification by DMT

Responsibilities of SWAMP Database Management Team Ø Training/Facilitate Data Entry Ø Field Data Ø Analytical Data Ø Database Management/Quality Assurance Ø Work with each Regional Board individually Ø Comparability checking Ø Verification of Data Quality Indicators (QAMP) Ø Compliance Coding Ø Transfer data from Temporary to Permanent Ø Data Training/Accessibility Ø Regional boards Ø State board Ø Groups outside of SWAMP

Regional Board Liaisons Ø Consult on integration of sampling designs into information management Ø Modify field data sheets Ø Assist with data entry training Ø Completeness checking Ø Follow-up/track down any missing data Ø Coordinate database distribution Ø Data access training Ø Status of data reporting

DMT Data/QA Process Overview Temporary Side Transfer to Permanent Side Export to CEDEN Data available to the public (Web)

DMT Data/QA Process Overview Temporary Side Transfer to Verify Transfer Global Checks Verify Export to CEDEN Contractual Project Completeness Verify MQOs Compliance Codes Permanent Side Data available to the public (Web)

SWAMP Data Verification Process Ø Verification against project MQO’s per batch per Project Ø Analytical data Ø Toxicity data Ø Field data Ø Verification of QA codes applied on both a batch and result level Ø Original codes applied appropriately Ø Apply any additional codes if necessary Ø Compliance codes applied based on QA code combinations Ø Compliant, Estimated, Historical, Rejected Ø Global verification performed on both permanent and temporary side Ø Business rules Ø Completeness Ø Consistency Ø Verified batches transferred from temporary side to permanent side

SWAMP Data Comparability Examples Analytes, Matrices and Units

SWAMP Business Rules Examples

Responsibilities of SWAMP Database Management Team Ø Data Entry Training/Facilitation Ø Field data Ø Analytical data Ø Database Management/Quality Assurance Ø Work with each Regional Board individually Ø Comparability checking Ø Verification of Data Quality Indicators (QAMP) Ø Compliance Coding Ø Transfer data from Temporary to Permanent Ø Data Training/Accessibility Ø Regional boards Ø State board Ø Groups outside of SWAMP

Data Training / Communication 1. Creation and maintenance of documentation 1. Field crews 2. Laboratories 3. Data users 4. Agencies required to be SWAMP comparable 2. Initial and ongoing training 1. 1 st Priority: SWAMP Participants 2. 2 nd “Non-SWAMP” parties required to be comparable Ø SWAMP User Group Ø Information exchange Ø Maintain comparability in data reporting

Data Accessibility Data access on temporary and permanent side Ø User has ability to build new queries Ø

Data Distribution on WWW http: //baydelta. ca. gov/

Successes Ø SWAMP has created information management standards and documented processes to meet our goals Ø All 9 Regional Boards are using SWAMP Database, although RB use varies: simple data access to data loading Ø Continue to collaborate with other agencies (SCCWRP, Bay Foundation, DWR) for system automation Ø Partnership with DWR allows more time and effort spent on science and less time on technology development Questions?