The data in this deposit were collected as part of the B@SEBALL project (Biodiversity at School Environments - Benefits for All). The project investigated how biodiversity in the school environment can positively affect children’s health and mental well-being. B@SEBALL also investigated the opportunities for reducing health inequalities among children via biodiversity at school environments. The data are organized according to the Frictionless Data Package standard. All child-level and school-level data have been anonymized. Each data package is a collection of csv files and a json file. The json file holds descriptive information for all variables in all csv files. The zip file contains two frictionless data packages. The data packages contain information on 37 primary schools and 513 children. The data package, data_package_an_zenodo_cleaned_data, contains the original data in a tidied and cleaned format. It consists of 46 csv files. The files relate to the following contents: contents filename metadata ... : As a service to users of the R statistical programming language, we provide an R script that can be used as a start to use the data contained in this deposit: library(inborutils)library(frictionless) # download the zenodo depositinborutils::download_zenodo( doi = "10.5281/zenodo.10527033", path = ".") # unziputils::unzip("data_packages.zip") # read the json filecleaned_data <- read_package( file = file.path("datapackage_an_zenodo_cleaned_data", "datapackage.json"))derived_data <- read_package( file = file.path("datapackage_an_zenodo_derived_data", "datapackage.json")) # list available resourcesresources(package = cleaned_data)resources(package = derived_data) # example how to read a resource from the data packagelandscape_data <- read_resource( package = cleaned_data, resource_name = "wp1_landscape_level_data") str(landscape_data)class(landscape_data)summary(landscape_data) # read associated descriptions and other metadata from json filelandscape_metadata <- get_schema( package = cleaned_data, ...