Matches in ScholarlyData for { ?s ?p A growing number of ontologies have been published on the Semantic Web by various parties, to be shared for describing things. Because of the decentralized nature of the Web, there often exist different but similar ontologies from overlapped domains, or even within the same domain. In this paper, we collect more than four thousand ontologies and perform a large-scale pairwise matching based on an ontology matching tool. We create about 3.1 million mappings between the concepts (classes and properties) from these ontologies, and build a complex concept mapping graph (CMG) with concepts as nodes and mappings as edges. We analyze the macroscopic properties of the CMG as well as the induced ontology mapping graph (OMG), which characterize the global ontology matchability in many aspects, including the degree distribution, connectivity and reachability. We further establish a pay-level-domain mapping graph (PMG) to understand the common interests between different ontology publishers. Besides, we publish these generated mappings online based on the R2R mapping language. These mappings and our observations are believed to be useful for the Linked Data community in ontology creation, integration and maintenance.. }
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- 11 abstract "A growing number of ontologies have been published on the Semantic Web by various parties, to be shared for describing things. Because of the decentralized nature of the Web, there often exist different but similar ontologies from overlapped domains, or even within the same domain. In this paper, we collect more than four thousand ontologies and perform a large-scale pairwise matching based on an ontology matching tool. We create about 3.1 million mappings between the concepts (classes and properties) from these ontologies, and build a complex concept mapping graph (CMG) with concepts as nodes and mappings as edges. We analyze the macroscopic properties of the CMG as well as the induced ontology mapping graph (OMG), which characterize the global ontology matchability in many aspects, including the degree distribution, connectivity and reachability. We further establish a pay-level-domain mapping graph (PMG) to understand the common interests between different ontology publishers. Besides, we publish these generated mappings online based on the R2R mapping language. These mappings and our observations are believed to be useful for the Linked Data community in ontology creation, integration and maintenance.".