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Scalable Visualization of DBpedia Ontology Using Hadoop

  • Sung-min Kim
  • Seong-hun Park
  • Young-guk Ha
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8210)

Abstract

Existing visualizing methods for big ontology data have many problems. To solve the problems and visualize big ontology data efficiently, we used Hadoop framework, which is for distributed processing across clusters for handling large dataset. The system that we devised is made up of three parts-a data server, a visualization server, and user devices. First of all, The data server preprocesses big data, and the visualization server processes the outputs for visualizing them and transform the outputs to match web standard. The data server and the visualization server use Hadoop framework. User devices have web browsers. Through web browsers, users can be provided with the visualization results by the visualization server We processed DBpedia ontology and visualized the data. In this paper, we will introduce a method for processing and visualizing DBPedia ontology. And we will show the performance of the method by measuring execution time and the experimental results of the visualizing process.

Keywords

Ontology visualization RDF visualization Big data visualization Hadoop DBpedia Ontology 

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References

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    The ApacheTM Hadoop, http://hadoop.apache.org
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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Sung-min Kim
    • 1
  • Seong-hun Park
    • 1
  • Young-guk Ha
    • 1
  1. 1.Department of Computer Science and EngineeringKonkuk UniversitySeoulRepublic of Korea

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