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In this paper, we measure and analyze the graph features of semantic Web (SW) schemas with focus on power-law degree distributions. Our main finding is that the majority of SW schemas with a significant number of properties (respectively, classes) approximate a power law for total-degree (respectively, the number of subsumed classes) distribution. Moreover, our analysis revealed some emerging conceptual modeling practices of SW schema developers: (1) each schema has a few focal classes that have been analyzed in detail (that is, they have numerous properties and subclasses), which are further connected with focal classes defined in other schemas, (2) class subsumption hierarchies are mostly unbalanced (that is, some branches are deep and heavy, while others are shallow and light), (3) most properties have as domain/range classes that are located high at the class subsumption hierarchies, and (4) the number of recursive/multiple properties is significant. The knowledge of these features is essential for guiding synthetic SW schema generation, which is an important step toward benchmarking SW repositories and query language implementations.
Knowledge and Data Engineering, IEEE Transactions on (Volume:20 , Issue: 5 )
Date of Publication: May 2008