  As the availability and the inter-connectivity of RDF datasets grow, so does
the necessity to understand the structure of the data. Understanding the
topology of RDF graphs can guide and inform the development of, e.g. synthetic
dataset generators, sampling methods, index structures, or query optimizers. In
this work, we propose two resources: (i) a software framework able to acquire,
prepare, and perform a graph-based analysis on the topology of large RDF
graphs, and (ii) results on a graph-based analysis of 280 datasets from the LOD
Cloud with values for 28 graph measures computed with the framework. We present
a preliminary analysis based on the proposed resources and point out
implications for synthetic dataset generators. Finally, we identify a set of
measures, that can be used to characterize graphs in the Semantic Web.
