Ocean Data Evaluation

After, or sometimes during, the data integration process, researchers must evaluate the integrated data-set to facilitate inclusion/exclusion decisions and to report quality and descriptive measures upon publication. The evaluation process address the issues of quality detection and coverage and bias correction.

 

QualityDetecting data errors is often done using non-specific numerical and statistical tools; for example, by excluding all outliers, defined as values over two standard deviations from the mean.

Coverage BiasAn important tool in the evaluation of result validity and relevance is the analysis of coverage and bias. Data are collected in different geographical regions, depths, and seasons, and using different instruments. When presenting results, one must either correct them for inherent biases, exclude under-represented partitions, or provide a list of caveats and analyses regarding the coverage and bias with respect to the general distribution over each dimension.