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Sharing of information between multiple tiers of government is a major focus in digital government research. Law enforcement agencies in particular can greatly benefit from information sharing. Information on known criminals can be analyzed using criminal activity networks that link people and vehicles based on data found in law enforcement databases. We analyze the topological characteristics of criminal activity networks of individuals in a multiple jurisdictional scenario. We find that large narcotics networks are small-world with short average path lengths ranging from 4.5-8.5 and have scale-free degree distributions with power law exponents of 0.85–1.3. In addition we find that utilizing information from multiple jurisdictions provides higher quality leads by reducing average shortest path lengths of the networks.