Data quality objectives

The U.S. Environmental Protection Agency (EPA) spends about $500 million annually in collecting environmental data for scientific research and regulatory decision making. In addition, the regulated community may spend as much as ten times more each year in responding to EPA compliance requirements. Among the EPA and the regulated community there are several important common concerns: both want to make informed decisions using the right type, quality, and quantity of data. Collecting new data is very resource intensive to all parties. Neither EPA nor the regulated community can afford to collect more or open-quotes betterclose quotes data than are really needed; the Data Quality Objectives (DQO) process is a systematic planning tool for ensuring that the right data will be collected for arriving at a decision within the desired confidence constraints. Using the DQO process to plan environmental data collections can help improve their effectiveness and efficiency, and enhance the defensibility of the decisions for which the data are used