Data Defensibility

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The data user's guide to producing legally defensible environmental data.

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Data Defensibility

  1. 1. Data Defensibility The Data User’s Guide to Producing Legally Defensible Environmental Data By Christina Hiegel, P.E. Civil/Environmental Engineer
  2. 2. Introduction Christina has over 11 years’ experience in the environmental industry. She is a registered Civil/Environmental Engineer and manages the chemistry group at Trihydro. Her primary responsibilities include providing technical support for projects in data defensibility, data quality, and leading data quality efforts. Christina Hiegel
  3. 3. Overview Define Plan Prepare Execute Review Manage
  4. 4. Definition of Defensible Data Define Plan Prepare Execute Review Manage
  5. 5. What is Your Final Goal? Short Term To reach your “Final Goal”, the supporting data will have to be measured in both extent and quality. Long Term
  6. 6. Developing Data Quality Objectives Step 1: State the Problem Step 2: Identify the Decision Step 3: Identify Information Inputs Step 4: Define the Boundaries of the Study Step 5: Develop the Analytical Approach Step 6: Specify the Performance or Acceptance Criteria Step 7: Develop the Plan for Obtaining Data USEPA. 2006a.  Guidance on Systematic Planning Using the Data Quality Objectives Process (EPA QA/G‐4).  (EPA/240/B‐06/001).  Available from:  http://www.epa.gov/QUALITY/qs‐docs/g4‐final.pdf
  7. 7. Planning Defensible Data Define Plan Prepare Execute Review Bad Idea – Spending money without a plan Manage
  8. 8. Choose Your Resources Wisely
  9. 9. Organizational Chart
  10. 10. Contracting with the Laboratory - Certifications Capabilities Capacities Methodology Reporting Limits
  11. 11. Plans for the Future – Looking Ahead      QAPP DMP SAP SMP DQO
  12. 12. Preparing Define Plan Prepare Execute Review Manage
  13. 13. Collecting Defensible Data Define Plan Prepare Execute Review Manage BAD DATA Bad Idea – Collecting data that is not usable
  14. 14. Laboratory Preparation
  15. 15. Field Preparation • • • • • • • Collection Methods Collection Order Decontamination Quality Assurance Samples Documentation Sample Custody Packing/Shipping
  16. 16. Quality Assurance Samples HOW MANY SHOULD I COLLECT?? Check your sample plans! RULE OF THUMB QA Sample How Many Percentage Field Duplicate 1 per 10 10% Field Blank 1 per day -- Equipment Blank 1 per day -- Trip Blank 1 per cooler with VOCs -- MS/MSD 1 per 20 5%
  17. 17. Chain-of-Custody Trihydro and laboratories have tools to help you make your data defensible. Trihydro’s Generic CoC
  18. 18. Why Validate Data? Define Plan Prepare Execute Review Manage
  19. 19. Choosing Validation Levels
  20. 20. Tiered Validation TIER IV TIER III TIER II TIER I
  21. 21. Tiered Validation TIER IV TIER III TIER II Data  Verification
  22. 22. Data Verification
  23. 23. Tiered Validation TIER IV TIER III TIER II Data  Verification
  24. 24. Tiered Validation TIER IV TIER III TIER II Data  Verification
  25. 25. Data Validation
  26. 26. Maintaining Defensible Data Define        Plan Prepare Execute Use a database to manage your data Complete validations Check produced reports, limits, and constituents Understand what data are qualified and why Check against previous data Work with laboratory and your team to make changes, as needed Read your data reports and validation reports and ask questions Review Manage
  27. 27. I Messed Up! What Do I Do?   Don’t panic Don’t cover-up or hide your mistake
  28. 28. Defensible Data Define Plan Prepare Execute Review Manage

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