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http://dx.doi.org/10.9708/jksci.2017.22.06.057

Analyzing RDF Data in Linked Open Data Cloud using Formal Concept Analysis  

Hwang, Suk-Hyung (Dept. of Global Software Engineering, SunMoon University)
Cho, Dong-Heon (College of General Studies, SunMoon University)
Abstract
The Linked Open Data(LOD) cloud is quickly becoming one of the largest collections of interlinked datasets and the de facto standard for publishing, sharing and connecting pieces of data on the Web. Data publishers from diverse domains publish their data using Resource Description Framework(RDF) data model and provide SPARQL endpoints to enable querying their data, which enables creating a global, distributed and interconnected dataspace on the LOD cloud. Although it is possible to extract structured data as query results by using SPARQL, users have very poor in analysis and visualization of RDF data from SPARQL query results. Therefore, to tackle this issue, based on Formal Concept Analysis, we propose a novel approach for analyzing and visualizing useful information from the LOD cloud. The RDF data analysis and visualization technique proposed in this paper can be utilized in the field of semantic web data mining by extracting and analyzing the information and knowledge inherent in LOD and supporting classification and visualization.
Keywords
Linked Open Data; Resource Description Framework; SPARQL; Formal Concept Analysis;
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