Data quality assessment

{
  "id": "MLC-T-ENV-007323",
  "term": "Data quality assessment",
  "field": "Environment",
  "term_source": "Data Quality Assessment",
  "definition": "1. The scientific and statistical evaluation of data to determine if data obtained from environmental operations are of the right type, quality, and quantity to support their intended use.\n\n2. A statistical and scientific evaluation of a data set to determine the validity and performance of the data collection design and statistical test, and to determine the adequacy of the data set for its intended use.\n\n3. A statistical and scientific evaluation of the data set to determine the validity and performance of the data collection design and statistical test, and to determine the adequacy of the data set for its intended use.\n\n4. The evaluation of environmental data to determine if they meet the quality criteria required for a specific application.\n\n5. Evaluation of environmental data to determine if they meet the quality criteria required for a specific application.\n\n6. Statistical and scientific evaluation of the data set to determine the validity and performance of the data collection design and statistical test, and to determine the adequacy of the data set for its intended use.",
  "abbreviation": "DQA",
  "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",
    "QA Glossary",
    "QA Glossary; Environmental Sampling and Analytical Methods (ESAM) Program Glossary",
    "EPA Quality Manual 5360"
  ],
  "url": "https://mlchart.com/terminology/environment/data-quality-assessment/"
}