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Crowd-sourced biodiversity databases provide easy access to data and images for ecological education research. One concern with using publicly sourced databases; however, is the quality of their images, taxonomic descriptions, geographical metadata. The method presented in this paper attempts address a suite pipelines evaluate consistency, how well geo-tagging fits known distributions, image crowd-sourced acquired from iNaturalist, database. Additionally, it provides researchers that use these datasets report quantifiable assessment consistency. pipeline allows users analyze multiple iNaturalist associated metadata; determine level identification (family, genera, species) each occurrence; whether taxonomy label an matches accepted nesting families, species; geo-tags match distribution taxon described occurrence Global Biodiversity Infrastructure Facility (GBIF) as reference. assessed BRISQUE, algorithm evaluation without reference photo. Entries order Araneae (spiders) are used case study. Overall, results suggest can large metadata sets Given inevitability some low-quality observations, valuable resource educators other data.