Accurate, interoperable, and representative data are fundamental to effective marine research and monitoring. Stereo-video methods are increasingly used in fish surveys worldwide due to their cost-effectiveness, non-destructive nature, and ability to produce permanent records and precise body size measurements. However, the reliability of both stereo- and mono-video data depends on standardised workflows and robust quality assurance processes. A national synthesis of fish survey datasets revealed widespread errors in metadata and species annotations, highlighting a critical need for improved data validation tools.
We present CheckEM, an open-source web application and R package designed to perform automated quality control checks on fish survey data. CheckEM identifies inconsistencies in metadata and cross-validates species annotations against taxonomic databases, known spatial distributions, and where applicable, maximum body size thresholds. The toolkit flags issues such as out-of-range observations, outdated nomenclature, and size outliers, and is compatible with outputs from multiple annotation platforms. It provides data standardisation, cleaning, and interactive visualisation through an accessible user interface, alongside downloadable error reports to support iterative data improvement.
By enhancing data accuracy, consistency, and transparency, CheckEM facilitates interoperability and reuse across datasets, strengthening collaborative research and enabling more robust ecological analyses. This tool supports improved decision-making in marine monitoring and management by ensuring higher confidence in underlying data.