Global macroecological analyses of biodiversity and associated functions are geographically biased with poor representation from many unique and threatened regions, hindering truly global understanding, and effective conservation. Not all regional gaps are equal, but may be driven by biases in sampling and/or data accessibility, necessitating problem‐oriented, and regionally‐tailored strategies to address them. We examine the causes and consequences of biodiversity data gaps using tree inventories from India, a global hotspot for biodiversity and carbon sequestration, as an example. We systematically collated the India Tree Inventory metadataset, INvenTree‐meta, combining literature searches and manual data retrieval and assessed data availability, reusability, and potential for synthetic research. INvenTree‐meta is the largest meta‐dataset of peer‐reviewed. publications ( n = 465) on geolocated plot‐based tree inventories of multispecies communities from Indian ecosystems, in aggregate covering three decades, and all of its woody biomes. We show extensive sampling across biomes but poor data accessibility (73.33% of studies representing 83.43% of the sampled area after removing repeats) through descriptive analyses. However, we observe majority authorship from India; 82.8% of corresponding authors were from India and 73.33% of the studies had all authors affiliated with Indian institutions demonstrating potential for regional collaboration to fill this gap. We illustrate the potential of systematically assembled regional metadatasets to identify future sampling priorities and of a harmonized dataset to advance ecological science, promote sound management and aid education. Assessing global data gaps with a focus on equity can accelerate filling knowledge gaps, as well as informing regional management and conservation.