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In community ecology, trait‐based approaches have been strongly recommended in recent years to understand the responses of community functions against environmental changes. Trait‐based approaches have been used to solve the mechanistic rules in the relationship between soil animal communities and environmental change. However, databases of functional traits of soil animals are still lacking. Collembola is one of the most abundant and diverse group in land ecosystems, with more than 400 identified species in Japan. This data set provides taxonomic information, geographic, habitat distributions and 13 morphological trait items of 407 species of Japanese Collembola: described in Japanese literature. The workshop of Japanese Collembola, supported by the Japanese Society of Soil Zoology, summarized the taxonomy for the Japanese Collembola species. The data set presented here is mainly based on their work. The spatial coverage of this data set is in the land area of Japan. Suborder, superfamily, family, subfamily, genus and species names, as well as common Japanese names, are listed in this paper. The species distributions of Japanese Collembola in each global ecozone and in each area within Japan were described. Habitat preference for soil, cave, seashore and tree trunk habitats was recorded. The 13 morphological traits of Collembola species, which are body length; body weight of adult individual; body form; antenna length; furca length; body pigmentation; pairs of ocelli (eyes); post‐antennal organ; pseudocelli; body scale; anal spine; mandible and molar plate are listed in this dataset. These 13 morphological traits in this dataset are covered the most of trait items which have been internationally used in Collembola study. Trait‐based studies of Collembola have mainly been for European species, most of which are not found in Japan or East Asia. These data sets may provide an important first step to incorporating community data from the Asian region to the trait‐based global ecology. Data files are stored in the Ecological Research Data Archives at http://db.cger.nies.go.jp/JaLTER/ER_DataPapers/archives/2019/ERDP-2019-03. [ABSTRACT FROM AUTHOR]