Data Quality Objectives

{
  "id": "MLC-T-ENV-007329",
  "term": "Data Quality Objectives",
  "field": "Environment",
  "definition": "1. The qualitative and quantitative statements derived from the DQO Process that clarifies study's technical and quality objectives, define the appropriate type of data, and specify tolerable levels of potential decision errors that will be used as the basis for establishing the quality and quantity of data needed to support decisions.\n\n2. Qualitative and quantitative statements that clarify study objectives, define the appropriate type of data, and specify error tolerances needed to support a decision.\n\n3. Qualitative and quantitative statements derived from the DQO Process that clarify study objectives, define the appropriate type of data, and specify tolerable levels of potential decision errors that will be used as the basis for establishing the quality and quantity of data needed to support decisions.\n\n4. Qualitative and quantitative statements of the overall level of uncertainty that a decision-maker will accept in results or decisions based on environmental data. They provide the statistical framework for planning and managing environmental data operations consistent with user's needs.\n\n5. Data Quality Objectives (DQO) refers to the overall degree of data quality or uncertainty that a decision maker is willing to accept for a decision. The DQO approach should apply to the entire measurement system (e.g., sampling locations, methods of collection and handling, field analysis, etc.), not just the laboratory analytical operations.\n\n6. Qualitative and quantitative statements derived from the DQO Planning Process that clarify the purpose of the study, define the most appropriate type of information to collect, determine the most appropriate conditions from which to collect that information, and specify tolerable levels of potential decision errors. {ORD} {OW/EAD} {OPP} {OAR/OAQPS} {ORCR}\n\n7. Qualitative and quantitative statements of the overall level of uncertainty that a decision maker is willing to accept in results or decisions derived from environmental data. DQOs provide the statistical framework for planning and managing environmental data operations consistent with the data user's needs.",
  "abbreviation": "DQOs",
  "synonyms": [
    "DQO"
  ],
  "subject": "Policy and guidance",
  "references": [
    "Guidance for Quality Assurance Project Plans",
    "Great Lakes: Quality Management Training - Data Review Glossary",
    "Great Lakes: Quality Management Training - Quality Glossary; Environmental Information Quality Procedure Glossary",
    "Terms of Environment",
    "Corrective Action 101 Key Terms",
    "Forum on Environmental Measurements (FEM) Glossary",
    "EPA/240/R-02/008; EPA 240-B-06-001; QA Glossary"
  ],
  "url": "https://mlchart.com/terminology/environment/data-quality-objectives/"
}