In the Semantic Web, vocabularies are defined and shared among knowledge workers to describe linked data for scientific, industrial or daily life usage. With the rapid growth of online vocabularies, there is an emergent need for approaches helping users understand vocabularies quickly. In this paper, we study the summarization of vocabularies to help users understand vocabularies. Vocabulary summarization is based on the structural analysis and pragmatics statistics in the global Semantic Web. Local Bipartite Model and Expanded Bipartite Model of a vocabulary are proposed to characterize the structure in a vocabulary and links between vocabularies. A structural importance for each RDF sentence in the vocabulary is assessed using link analysis. Meanwhile, pragmatics importance of each RDF sentence is assessed using the statistics of instantiation of its terms in the Semantic Web. Summaries are produced by extracting important RDF sentences in vocabularies under a re-ranking strategy. Preliminary experiments show that it is feasible to help users understand a vocabulary through its summary.

Abstract. Lots of RDF data have been published in the Semantic Web. The RDF data model, together with the decentralized linkage nature of the Semantic Web, brings object link structure to the worldwide scope. Object links are critical to the Semantic Web and the macroscopic properties of object links are helpful for better understanding the current Data Web. In this paper, we propose a notion of object link graph (OLG) in the Semantic Web, and analyze the complex network structure of an OLG constructed from the latest dataset (FC09) collected by the Falcons search engine. We find that the OLG has the scale-free nature and the approximate effective diameter of the graph is small compared to its scale, which are also consistent with the experimental result based on our last year's dataset (FC08). The amount of RDF documents and objects by Falcons both doubled during the past year, but the object link graph remains the same density while the diameter is getting shrinking. We also repeat the complex network analysis on the two largest domainspecific subsets of FC09, namely Bio2RDF(FC09) and DBpedia(FC09). The results show that both Bio2RDF(FC09) and DBpedia(FC09) have low density in object links, which contribute to the low density of object links in FC09.

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The electrocatalytic urea oxidation reaction (UOR) emerged as one of the promising half-reactions for energy conversion and storage devices due to its low thermodynamic potential (-0.46 V vs. SHE). However,...

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