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Abstract

Recent years have seen an explosion in the availability of biodiversity data describing the
distribution, function, and evolutionary history of life on earth. Integrating these heterogeneous
data remains a challenge due to large variations in observational scales, collection
purposes, and terminologies. Here, we conceptualize widely used biodiversity data types
according to their domain (what aspect of biodiversity is described?) and informational resolution
(how specific is the description?). Applying this framework to major data providers in
biodiversity research reveals a strong focus on the disaggregated end of the data spectrum,
whereas aggregated data types remain largely underutilized. We discuss the implications of
this imbalance for the scope and representativeness of current macroecological research
and highlight the synergies arising from a tighter integration of biodiversity data across
domains and resolutions. We lay out effective strategies for data collection, mobilization,
imputation, and sharing and summarize existing frameworks for scalable and integrative
biodiversity research. Finally, we use two case studies to demonstrate how the explicit consideration
of data domain and resolution helps to identify biases and gaps in global data
sets and achieve unprecedented taxonomic and geographical data coverage in macroecological analyses.