CheckEM : An open‐source toolkit for standardising, cleaning and visualising stereo‐video fish survey data

Abstract Effective research and monitoring requires accurate, interoperable and representative data. Stereo‐video based methods are commonly used to survey fish and are rapidly expanding globally due to their cost‐effectiveness, ability to provide accurate body size measurements, non‐destructive approach and capacity to create permanent data records. However, the representativeness of both stereo and mono‐video derived data depends on standardised approaches to provide quality assurance of reliable, reproducible and error‐free data. A national synthesis of both stereo and mono‐video fish survey datasets identified numerous errors in data collection and annotation, many of which are also relevant to other survey methods. To develop an open‐source toolkit, CheckEM , for quality control checks on fish survey data. The CheckEM web application and R package identifies errors in metadata and cross‐checks annotations of fish with taxonomic databases, expected spatial distributions, and, in the case of stereo‐video, maximum body sizes, and works with the outputs of a range of annotation tools (including EventMeasure and other annotation software). CheckEM flags species observed beyond their known range, outdated scientific names and body size outliers. CheckEM standardises, cleans and visualises datasets, offering interactive plots and tables in a user‐friendly interface. Downloadable summary data and error reports support iterative checks and improvement of data quality. We demonstrate that CheckEM enhances data accuracy, confidence, interoperability and reusability, improving collaboration and cross‐dataset comparisons to support robust analyses and informed marine monitoring and management.