1. 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

2. Presentation Outline  SWAMP Database Goals  Start Up Principles  Data Elements  Database Systems  Questions

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

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

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

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

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

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

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

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

11. Example SWAMP Data Sheet

12. SWAMP Data Entry Forms

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

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

15. SWAMP Data Systems SOPs

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

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

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

19. DMT Data/QA Process Overview E x p o r t t o C E D E N Temporary Side Permanent Side Data available to the public (Web) Transfer to Export to CEDEN

20. DMT Data/QA Process Overview E x p o r t t o C E D E N Temporary Side Permanent Side Data available to the public (Web) Transfer to Export to CEDEN Contractual Project Completeness Verify MQOs Compliance Codes Global Checks Verify Export Verify Transfer

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

22. SWAMP Data Comparability Examples Analytes, Matrices and Units

23. SWAMP Business Rules Examples

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

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

26.  Data access on temporary and permanent side  User has ability to build new queries Data Accessibility

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

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