  Semantic information is often represented as the entities and the
relationships among them with conventional semantic models. This approach is
straightforward but is not suitable for many posteriori requests in semantic
data modeling. In this paper, we propose a meaning-oriented approach to
modeling semantic data and establish a graph-based semantic data model. In this
approach we use the meanings, i.e., the subjective views of the entities and
relationships, to describe the semantic information, and use the semantic
graphs containing the meaning nodes and the meta-meaning relations to specify
the taxonomy and the compound construction of the semantic concepts. We
demonstrate how this meaning-oriented approach can address many important
semantic representation issues, including dynamic specialization and natural
join.
