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<br /> <br /> <br />11-1 <br /> <br />Section 11 <br />Data Validation and Usability <br />Requirements for data validation and methodology are summarized in the following sections. <br />11.1 Data Review, Verification, and Validation Requirements <br />Data verification and validation are integral steps in the transition between data collection and data <br />use and interpretation. The USEPA has developed a comprehensive guidance document titled <br />Guidance on Environmental Data Verification and Data Validation (USEPA, 2002). The purpose of the <br />document is to explain how to implement data verification and data validation, offer practical advice, <br />and provide references. <br />Although data verification and data validation are commonly used terms, they are defined and <br />applied differently by various organizations and quality systems. For the purposes of the project, the <br />terms are defined as follows: <br />• Data verification. Confirmation by examination and provision of objective evidence that specified <br />requirements have been fulfilled. Data verification is the process of evaluating the <br />completeness, correctness, and conformance/compliance of a specific data set against the <br />method, procedural, or contractual requirements. This confirmation is done to determine <br />whether everything that was agreed upon was actually completed. <br />• Data validation. Confirmation by examination and provision of objective evidence that the <br />particular requirements for a specific intended use are fulfilled. Data validation is an analyte- <br />and sample-specific process that extends the evaluation of data beyond method, procedural, or <br />contractual compliance (i.e., data verification) to determine the analytical quality of a specific <br />data set. In other words, what is the quality of this specific data set? <br />Data generated by project activities will be reviewed against project DQOs and flagged (qualified) if <br />the objectives are unmet. Data will also be assessed to determine whether the QC practices were in <br />place during data collection. If data were collected without the stated QC practices in place, the data <br />will be set aside until the impact of the QC failure on data quality can be evaluated. If the impact of <br />the QC failure on data quality is minimal, the data will be qualified and included within the database. <br />Data that does not meet the DQOs will be evaluated to determine the cause of the problem and <br />whether corrective actions can be implemented so that DQOs are met in the future. <br />11.2 Verification and Validation Methods <br />Laboratory data will be validated in accordance with the USEPA Contract Laboratory Program <br />National Functional Guidelines for Inorganic Superfund Data Review (USEPA, 2017). These <br />documents serve as the equivalent of an SOP for data review and validation. Level II data validation <br />will be performed on the analytical data. Specific data evaluation and qualification guidelines for <br />inorganic and general chemistry data review are included in Appendix B, including the review items, <br />method, review criteria, action criteria, and reason codes. <br />Data verification/validation will be performed by the QAO and designated reviewers/validators. Data <br />reviewers will be responsible for reviewing field data sheets, COC forms, and analytical lab reports <br />from each sampling event to determine whether collected data meets the contractual requirements. <br />The data validators will add to the data review by checking field equipment calibration records and