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Ref. No. [UMCES] CBL 2016-015
ACT VS16-06
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Data validation uses the outputs from data verification and included inspection of the
verified field and laboratory data to determine the analytical quality of the data set. A
representative set of approximately 10% of the data on core parameters was traced in detail from
raw data from field and laboratory logs and instrument readouts through data transcription or
transference through data manipulation through data reduction to summary data, data calculations,
and final reported data. Data validation established:
•
Required sampling methods were used;
•
Sampling procedures and field measurements met performance criteria;
•
Required analytical methods were used;
Data validation confirmed that ACT’s sample measurement system performed in
accordance with the performance goals specified in the ACT QAPP and the DO Test Protocols and
that the data were accumulated, transferred, reduced, calculated, summarized, and reported
correctly. There is sufficient documentation of all procedures used in the data collection and
analysis to validate that the data were collected in accordance with the verification’s quality
objectives.
A Data Quality Assessment (DQA), the third and final process of the overall data
assessment, is a scientific and statistical evaluation of validated data to determine if the data are of
the right type, quality, and quantity to support conclusions on the performance of the DO sensors.
The DQA determined that ACT’s data quality objectives, described in Section 3.4 of the ACT
QAPP, were achieved. This evidence supports conclusions that:
•
The sampling design performed very well and was very robust with respect to changing
conditions.
•
Sufficient samples were taken to enable the reviewer to see an effect if it were present.
•
Data on the performance of the DO sensors are unambiguous, and the vendors and buyers can
make informed choices about the performance of a sensor with a high level of certainty.
REFERENCES
Bittig, H.C.,Fiedler, B., Scholz, R., Krahmann, G., and Kortzinger, A. 2014. Time response of
oxygen optodes on profiling platforms and its dependence on flow speed and temperature. Limnol.
Oceanogr. Methods, 12: 617-636.
Carignan, R., Blais, A.M., and Vis, C. 1998. Measurement of primary production and community
respiration in oligotrophic lakes using the Winkler method, Canada Journal of Fisheries and
Aquatic Sciences 55:1078-1084.
Carritt, D.E., and Carpenter, J.H. 1966. Comparison and evaluation of currently employed
modifications of the Winkler method for determining dissolved oxygen in seawater; a NASCO
report. J. Mar. Res. 24: 286–318.