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
- Sampling Designs
- Software for Estimating Sample Sizes and Locations
Designing a New Data Collection
- Chapter 2 of the Guidance for Quality Assurance Project Plans (G-5) 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) 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
- 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.