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Data Defensibility
The Data User’s Guide to Producing
Legally Defensible Environmental Data
By Christina Hiegel, P.E.
Civil/Environmental Engineer
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
Overview

Define

Plan

Prepare

Execute

Review

Manage
Definition of Defensible Data
Define

Plan

Prepare

Execute

Review

Manage
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
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
Planning Defensible Data
Define

Plan

Prepare

Execute

Review

Bad Idea – Spending money without a plan

Manage
Choose Your Resources Wisely
Organizational Chart
Contracting with the Laboratory
-

Certifications
Capabilities
Capacities
Methodology
Reporting
Limits
Plans for the Future – Looking Ahead






QAPP
DMP
SAP
SMP
DQO
Preparing
Define

Plan

Prepare

Execute

Review

Manage
Collecting Defensible Data
Define

Plan

Prepare

Execute

Review

Manage

BAD DATA
Bad Idea – Collecting
data that is not usable
Laboratory Preparation
Field Preparation
•
•
•
•
•
•
•

Collection Methods
Collection Order
Decontamination
Quality Assurance
Samples
Documentation
Sample Custody
Packing/Shipping
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%
Chain-of-Custody
Trihydro and
laboratories
have tools to
help you make
your data
defensible.

Trihydro’s
Generic CoC
Why Validate Data?
Define

Plan

Prepare

Execute

Review

Manage
Choosing Validation Levels
Tiered Validation
TIER IV

TIER III

TIER II
TIER I
Tiered Validation
TIER IV

TIER III

TIER II
Data 
Verification
Data Verification
Tiered Validation
TIER IV

TIER III

TIER II
Data 
Verification
Tiered Validation
TIER IV

TIER III

TIER II
Data 
Verification
Data Validation
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
I Messed Up! What Do I Do?



Don’t panic
Don’t cover-up or
hide your mistake
Defensible Data
Define

Plan

Prepare

Execute

Review

Manage
Data Defensibility

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Data Defensibility