Biodiversity citizen science data are being collected at unprecedented scales, and are key for informing conservation and research. Species‐level data typically provide the most valuable information, but recognition of specimens to species level from photographs varies among taxa. We examined a large dataset of Australian photographic observations of terrestrial invertebrates uploaded to iNaturalist to quantify recognition to species across different taxa. We also quantified the proportion of Australian species that have been uploaded to iNaturalist. Across 1,013,171 observations covering 14,663 species (17.8% completeness), 617,045 (60.9%) were recognized to species. Dragonflies/damselflies and butterflies were the best‐recognized and most complete taxa, and therefore represent the best groups for researchers and managers intending to use existing iNaturalist data at large spatial and temporal scales. The recruitment of additional experts to identify records, and enhanced support for accessible resources for hard‐to‐identify taxa, will likely increase recognition for other taxa.

One way to improve the value of citizen science data for a specific aim is through promoting adaptive sampling, where the marginal value of a citizen science observation is dependent on existing data collected to address a specific question. Adaptive sampling could increase sampling at places or times—using a dynamic and updateable framework—where data are expected to be most informative for a given ecological question or conservation goal. We used an experimental approach to test whether the participants in a popular Australian citizen science project—FrogID—would follow an adaptive sampling protocol aiming to maximize understanding of frog diversity. After a year, our results demonstrated that these citizen science participants were willing to adopt an adaptive sampling protocol, improving the sampling of biodiversity consistent with a specific aim. Such adaptive sampling can increase the value of citizen science data for biodiversity research and open up new avenues for citizen science project design.