The GovCamp wiki has a long list of tools surrounding linked data that may be of use - Svgvizler (for SPARQL graphing), RelFinder (for RDF visual exploration), and SPARQL Editor (for interactive SPARQL query building) are useful too. If you haven't run across the term before (or have, but still don't understand what it means) check out Linked Data – for the enlightened non-geek reader (or dummies) (or managers) and A dummy’s introduction to linked data (me being the dummy). Tangent Alert!! While we're talking about networks and relationships we should introduce the concept of "linked data". If you have a problem where you need to quickly and efficiently know how X is connected to Y and via whom, than graph databases are worth a look. One of the more obvious uses for graph databases are to store and analyse the relationships between people - think Facebook, Twitter, or any web property with a concept of followers or memberships. Whereas in more traditional databases we would have used a from of link table to represent the relationships between entities, that relationship is implicit in a graph database with every entity containing direct pointers to its adjacent entities without the need to expensively compute indexes. Graph databases were conceived of as a means to make the task of exploring the connections and networks between entities much easier.
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