What are Data Quality Objectives

To facilitate systematic planning, EPA developed the DQO process, a seven-step planning approach for data collection designs, which enables us to collect relevant and valid data for project decision-making. 

The EPA first introduced the DQO process in 1986 (EPA, 1986) and finalized it in 2000 (EPA, 2000a). The purpose of the DQO process is to provide a planning tool for determining the type, quality, and quantity of data collected in support of the EPA s decisions. Although developed specifically for projects under the EPA s oversight, the DQO process, being a systematic planning tool, is applicable to any projects that require environmental chemical data collection. 

Depending on the project scope and objectives, the DQO process may need the input from an extensive team of environmental professionals and scientists. For small projects, it can be conducted by a single, well-informed individual. Organizations that use the DQO process for their planning, observed the following improvements in the execution of their projects (EPA, 2000a)  

Although intended for projects that use probabilistic (statistically based) sampling designs, the logic of the DQO process may be adapted to all types of environmental 

The DQO process sounds very complicated and even intimidating, however when explained in plain terms, it becomes understandable and clear. Basically, it is a process that consists of asking questions and finding the answers. It can be simply described by using Rudyard Kipling s parable from Just So Stories  

---