Data from: The complexity of social complexity: a quantitative multidimensional approach for studies on social organisation

The rapid increase in “big data” of the post-genomic era makes it crucial
to appropriately measure the level of social complexity in comparative
studies. We argue that commonly-used qualitative classifications lump
together species showing a broad range of social complexity, and falsely
imply that social evolution always progresses along a single linear
stepwise trajectory that can be deduced from comparing extant species. To
illustrate this point, we compared widely-used social complexity measures
in "primitively eusocial" bumble bees with “advanced eusocial”
stingless bees, honey bees, and attine ants. We find that a single species
can have both higher and lower levels of complexity compared to other
taxa, depending on the social trait measured. We propose that measuring
the complexity of individual social traits switches focus from semantic
discussions and offers several directions for progress. Firstly,
quantitative social traits can be correlated with molecular,
developmental, and physiological processes within and across lineages of
social animals. This approach is particularly promising for identifying
processes that influence or have been affected by social evolution.
Secondly, key social complexity traits can be combined into
multidimensional lineage-specific quantitative indices enabling fine scale
comparison across species that are currently bundled within the same level
of social complexity.