Resources for Planning New Data Collections
When planning for new data collections, there are many factors to consider including:
- Purpose of project and data collection
- Potential secondary use of the data
- Distributions of contaminant
- Sources of variability
- Chemical/physical properties
- Information about the area/process (size/breadth of area, temporal components, geography)
- Tolerance for potential decision errors and/or precision requirements
- Sampling/analysis constraints (instrument performance, analytical methods, sample's physical size and shape)
- Regulatory requirements
The following are some additional resources specific to new data collections that supplement the resources described on Systematic Planning page.
Designing a New Data Collection
- Chapter 2 of the Guidance for Quality Assurance Project Plans (G-5) (PDF 111pp, 401K About PDF) identifies elements to consider when designing new data collection.
- Quick Guide to Selecting Sampling Design
- Guidance on Choosing a Sampling
Design for Environmental Data Collection (G-5S) (PDF 178pp,
1.0MB About PDF) contains
guidance on applying standard statistical sampling designs (such as
simple random sampling) and more advanced sampling designs (such as
ranked set sampling, adaptive cluster sampling) to environmental applications.
- Using Professional Judgment to Develop a Sampling Design
Software for Estimating Sample Sizes and Locations
- Decision Error Feasibility Trials (DEFT) Software (G-4D) User's
Guide (PDF 59pp, 275K About
PDF) and Software (EXE 436K
About EXE files) is PC-based
software for determining the feasibility of design objectives defined
using the Data Quality Objectives Process.
- Visual Sample Plan (VSP) is a simple, defensible tool for defining an optimal, technically defensible sampling scheme for site characterization. VSP is applicable for any two-dimensional sampling plan including surface soil, building surfaces, water bodies, or other similar applications.
- Introduction to Data Quality Objectives
- This course teaches participants the basic elements of the Data Quality
Objectives Process. Participants learn the elements of this process,
how the process applies to a regulatory program at EPA, and how to interpret
the consequences of potential decision errors. Then the participants
work together as teams to apply the process to some real-life examples.
- Introduction to Quality Assurance Project Plans - This course is designed for individuals who write, review, and/or approve Quality Assurance Project Plans and is designed with a "how-to" approach. Participants are expected to have some basic grounding in quality assurance principles.