DocumentCode :
1655557
Title :
Visualizing Linked Data with JavaScript
Author :
Lixian Ni ; Zhuoming Xu ; Ting Wu ; Wenjie He
Author_Institution :
Coll. of Comput. & Inf., Hohai Univ., Nanjing, China
fYear :
2013
Firstpage :
211
Lastpage :
216
Abstract :
Despite the wealth of information contained in the Web of Linked Data, the current limitations and entry barriers of the Semantic Web technologies hinder the users from taking advantage of these information resources. Linked Data visualization can alleviate this problem. In this paper, we adopt a proper Linked Data visualization model, design Linked Data visualization algorithms, and develop a lightweight, easy-to-use prototype tool, LOD Viewer, using the platform independent JavaScript language. LOD Viewer can visualize different sources of RDF data including SPARQL endpoints for Linked Open Data (LOD) sources, and display the data in different graphic illustrations. Our case studies have verified the effectiveness and realizability of the proposed method. The time complexity analysis and experimental test show that the run-time of the proposed algorithms approximately exhibits a linear growth rate as the visualized RDF triples size increases.
Keywords :
Java; computational complexity; data structures; data visualisation; information resources; prototypes; semantic Web; JavaScript language; LOD sources; LODViewer; RDF data sources; SPARQL endpoints; Web of linked data; easy-to-use prototype tool; entry barriers; information resources; linked data visualization algorithms; linked data visualization model; linked open data sources; semantic Web technologies; time complexity analysis; visualized RDF triples; Algorithm design and analysis; Data models; Data visualization; Resource description framework; Shape; Time complexity; Visualization; JavaScript; Linked Data; Linked Data visualization; Linked Data visualization tool; algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Information System and Application Conference (WISA), 2013 10th
Conference_Location :
Yangzhou
Print_ISBN :
978-1-4799-3218-4
Type :
conf
DOI :
10.1109/WISA.2013.48
Filename :
6778639
Link To Document :
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