ABSTRACT
Assessments of Data Quality As is true of pioneering efforts, many priorities must be addressed and users learn along the way. When faced with huge data collection efforts, achieving results is vital. Naturally, work is conducted with high levels of quality. Now, it is even more important to document the quality of data and assure their collection using standard procedures. The procedures to accomplish data quality assurance (QA) and data quality control (QC) in data management collection are well known in laboratory science.
