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    IDENTIFICATION OF DATA QUALITY METRICS FOR TAGGING DATA SELECTION

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    Document Number:
    WG-SAM-09/19
    Author(s):
    D.A.J. Middleton and A. Dunn (New Zealand)
    Abstract

    The suite of data quality metrics introduced by Middleton & Dunn (2008) is examined to identify those metrics that are most informative with respect to the identification of good tagging data. Trips considered to have “known” good tagging data are identified, based on above-median rates of recapture of tags released by the trip, and above-median tag recapture rates by the trip.A bootstrap analysis indicates that the range of data quality metrics associated with known good tagging data is sensitive to the set of trips considered to have good data. However, a restricted set of data quality metrics may be most powerful in distinguishing the trips considered to have good tagging data. These include metrics for taxonomic resolution in the observer data, goodness of fit of catch data to Benford's Law, and the variation in toothfish catch rates.This reduced set of data quality metrics could be helpful in the identification of trips which have similar data quality to the known “good data” trips, but where, due to heterogeneity in the stock and in the spatial and temporal distribution of fishing effort, it is not possible to establish this directly from tag recaptures.

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