Are you interested in learning how to improve the quality, reliability, and usability of your ecological data? If so, then please join us as we walk through elements of systematic planning – a quality management framework promoted by the U.S. EPA to assist scientists, managers, and practitioners in the development and achievement of established data quality performance standards. This interactive course provides participants the opportunity to engage in discussion and hands-on exercises on the concepts and applications of data quality planning, implementation, and assessment, fundamental to environmental research and monitoring activities. This half-day training session has been designed to enhance competency in both career- and entry-level professionals on the practical applications of quality assurance (QA) and quality control (QC) best practices. Support to this training was funded by the Great Lakes Restoration Initiative.
Upon completion of this course, participants will be able to:
Describe the Purpose of Systematic Planning
Describe the Value of a Data Management Plan
Develop Meaningful Goals and “SMART” Project Objectives
Define Performance/Acceptance Criteria for Indicators of Data Quality (i.e., data quality indicators)
Describe the Distinction Between Implementation and Effectiveness Monitoring
Describe Why it’s Important to Incorporate “Independent” Oversight
Describe Quality Control Procedures Used During Monitoring
Describe Why it’s Important to Conduct Data Quality Review
Describe the Process Involved in Verifying and Validating Project Data
