The age of digitization has led to a deluge in openly accessible digital biodiversity data, which includes datasets that consist of interactions between species (e.g., predator-prey). Our proposed visualization approach tackles the problem of identifying suspicious interactions for researchers such that possible data errors or unexpected claims can be detected in a quick manner. By using a heat map at different taxonomic levels to indicate commonality of interactions between two taxons, users

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... GloBI can easily visualize the trustworthiness of a record. The resulting visualization shows that this approach is a viable option to aid in the identification of suspicious ecological interactions. Looking forward, the results of this study could be used as a tool to help GloBI users understand the shortcomings of a dataset, and to be able to identify cross-referenced and non-cross-referenced records more systematically