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Aim: Recent unprecedented efforts to digitise and mobilise biodiversity data have resulted in the generation of 'biodiversity big data', enabling ecological research at scales previously not possible. However, gaps, biases and uncertainties in these data influence analytical outcomes and the validity of scientific research and conservation actions. Here, we estimated tree species inventory completeness globally and identified where future surveys should focus to maximise regional inventories. Location: Global. Methods: We analysed spatial patterns in sampling effort of tree species occurrence records from the Global Biodiversity and Information Facility (GBIF) and estimated global tree species inventory completeness for 100 × 100 km grid cells (sampling units) and ecoregions. We also identified forested areas for future botanical exploration, by examining the spatial overlap between inventory completeness, remaining natural habitat and protected areas and degrees of forest modification by anthropogenic pressure (forest integrity). Results: Spatial patterns in sampling effort and tree species inventory completeness were unevenly distributed around the world. Only 35% of ecoregions and 18% of sampling units can be considered well surveyed, most of which were concentrated in the Global North, including Europe, North America and Australia. Large areas in species‐rich tropical regions, especially in Southeast Asia, remained poorly documented. Moreover, our results showed that many areas with low inventory completeness overlapped with ecoregions retaining less than 50% of natural habitat and protected land area, as well as sampling units with low forest integrity. Main Conclusions: Due to limitations in biodiversity data, simply sampling more will not necessarily lead to increasing knowledge. We illustrated how gaps in these data can be used to improve existing knowledge by identifying priority areas for future surveys. With ongoing anthropogenic impacts and escalating rates of biodiversity loss, limited resources should be allocated to strategically survey regions likely to yield new knowledge and improve biodiversity representativeness. [ABSTRACT FROM AUTHOR]