DEVELOPMENT OF A METHODOLOGY FOR DATA QUALITY ASSESSMENT

Measures are developed which aim to summarise the quality of fishing event, catch, and biological sampling data from a fishing trip. In particular these measures aim to quantify the prevalence of position or time reporting errors, the diversity of catch, the extent to which catch data follow Benford's Law for the distribution of the first significant digit, whether length-frequency data have been collected as expected, and the reliability of length-weight measurements. Individually these measures can assist in assessing which data from a trip should be used in an assessment, and can also guide how these data can best be used.The quality of tag data is hard to assess. A methodology is developed to use data quality measures for other data sets to group trips on the basis of their overall data quality. Ongoing development of this method is intended to provide a consistent basis for selecting the tagging data set that is fitted in an assessment model.The data quality measures illustrate sometimes substantial variation in the quality of particular data sets from different trips in the Ross Sea Antarctic toothfish fishery. Cluster analyses suggests two groups of trips, one of which can tentatively be considered to have better data. Tags released by trips in this latter group have been recaptured at a higher rate than tags released by the other group of trips.