A blank node is an unnamed node, whose name is set by the underlying RDF software and cannot be guaranteed to have the same name for different sessions. Within a graph, it is guaranteed to resolve to the same thing (not a resource/URI but a separate way to represent a node), and between graphs, “it would be incorrect to assume that blank nodes from different graphs having the same blank node identifiers are the same” (see RDF Primer). If you want multiple independent graphs to refer to the same resource, you have to give it an explicit URI.
The most authoritative source for named graphs (being a W3C Recommendation) is SPARQL. Serialization syntaxes, such as RDF/XML or Turtle, allow you to assign an explicit name (a “blank node identifier”) to a blank node, but this is only to distinguish between different blank nodes or to refer to the same blank node from different triples within the same graph. If you give the same blank node identifier to blank nodes in different graphs, these blank nodes are still different from each other; in fact, there will be no relationship or interaction between them at all.
Named Graphs is the idea that having multiple RDF graphs in a single document/repository and naming them with URIs provides useful additional functionality built on top of the RDF Recommendations.
Named Graphs turn the RDF triple model into a quad model by extending a triple to include an additional item of information. This extra piece of information takes the form of a URI which provides some additional context to the triple with which it is associated, providing an extra degree of freedom when it comes to managing RDF data. The ability to group triples around a URI underlies features such as: Tracking provenance of RDF data, Access Control and Versioning.
There’s some useful background available on Named Graph Provenance and Trust, on Named Graphs in general in a paper about NG4J, and specifically on their use in OpenAnzo.
Named Graphs are an important part of the overall technical framework for managing, publishing and querying RDF and Linked Data, and its important to understand the trade-offs in different approaches to using them.