Fig. 1

(a) General scheme on how data is structured in the database following the Observation-Measurement scheme⁶¹ and Madin et al.²¹. (b) Example of an observation. Each observation contains data for the data enterer, the species of interest, the scientific source, the type of access (i.e., optional variable that data enterers can control to keep data private before publication) and the location. In addition, each observation binds one or various measurements that apart from specifying the name of the measured trait (e.g., height of the colony), include information about: the standard used to measure it (e.g., m, cm…etc), the method used (e.g., ruler), the actual value measured, and the value type (e.g., raw data for a single measurement, expert/group opinion for single/consensus view of experts, mean, median, range, maximum, or minimum…). The number of replicates and estimates of precision (e.g., standard error, standard deviation…) can also be specified when applicable. Finally, one or multiple contextual traits (e.g., water depth, habitat type…), that might be relevant for explaining intra-specific variation in the trait/s of interest can also be associated to the observation.