  CoCoE stands for Complexity, Coherence and Entropy, and presents an
extensible methodology for empirical analysis of Linked Open Data (i.e., RDF
graphs). CoCoE can offer answers to questions like: Is dataset A better than B
for knowledge discovery since it is more complex and informative?, Is dataset X
better than Y for simple value lookups due its flatter structure?, etc. In
order to address such questions, we introduce a set of well-founded measures
based on complementary notions from distributional semantics, network analysis
and information theory. These measures are part of a specific implementation of
the CoCoE methodology that is available for download. Last but not least, we
illustrate CoCoE by its application to selected biomedical RDF datasets.
