Data Usability Part 1: Data Validation Needs To Be More Than Just A Checklist
Oral Presentation
Prepared by P. Newbold1, J. McAteer2
1 - ddms, inc., 186 Center St., Suite 290, Clinton, NJ, 08809, United States
2 - QA/QC Solutions, LLC , 7532 Champion Hill Rd. SE, Salem, OR, 97306, United States
Contact Information: pnewbold@ddmsinc.com; 908-479-1975
ABSTRACT
Environmental data are generated to support decision-making that is supportive of ecological and human health. These decisions are based on the quality of the data. If the overall quality and usability of data is not well documented and defined, is not known, and/or the limitations of the data are not identified, then subsequent end-use(s) may not be met and decision(s) made may be incorrect. It is critical that the data are scientifically meaningful, valid, usable, and legally defensible.
Reducing the level of data review has been gaining traction among both government and non-government sectors as, in part, a cost-cutting measure. Automated data review/screening is being used more frequently as a substitution for the hands-on review of an experienced chemist. As a result, the overall potential of uncertainty with the data increases. Part 1 of this 2-part presentation will address how data validation is an integral part of the systematic planning process and how data could be impacted and additional uncertainty introduced as a result of the reduced effort of data review and validation, as well as the inherent uncertainty in any sampling and analysis program.
Oral Presentation
Prepared by P. Newbold1, J. McAteer2
1 - ddms, inc., 186 Center St., Suite 290, Clinton, NJ, 08809, United States
2 - QA/QC Solutions, LLC , 7532 Champion Hill Rd. SE, Salem, OR, 97306, United States
Contact Information: pnewbold@ddmsinc.com; 908-479-1975
ABSTRACT
Environmental data are generated to support decision-making that is supportive of ecological and human health. These decisions are based on the quality of the data. If the overall quality and usability of data is not well documented and defined, is not known, and/or the limitations of the data are not identified, then subsequent end-use(s) may not be met and decision(s) made may be incorrect. It is critical that the data are scientifically meaningful, valid, usable, and legally defensible.
Reducing the level of data review has been gaining traction among both government and non-government sectors as, in part, a cost-cutting measure. Automated data review/screening is being used more frequently as a substitution for the hands-on review of an experienced chemist. As a result, the overall potential of uncertainty with the data increases. Part 1 of this 2-part presentation will address how data validation is an integral part of the systematic planning process and how data could be impacted and additional uncertainty introduced as a result of the reduced effort of data review and validation, as well as the inherent uncertainty in any sampling and analysis program.
