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2013 IEEE 29th International Conference on Data Engineering (ICDE) (2010)
Long Beach, CA, USA
Mar. 1, 2010 to Mar. 6, 2010
ISBN: 978-1-4244-5445-7
pp: 1048-1059
Seema Sundara , Oracle, One Oracle Drive, Nashua, NH 03062, USA
Eugene Inseok Chong , Oracle, One Oracle Drive, Nashua, NH 03062, USA
Vladimir Kolovski , Oracle, One Oracle Drive, Nashua, NH 03062, USA
Zhe Wu , Oracle, One Oracle Drive, Nashua, NH 03062, USA
Medha Atre , Oracle, One Oracle Drive, Nashua, NH 03062, USA
Jagannathan Srinivasan , Oracle, One Oracle Drive, Nashua, NH 03062, USA
Souripriya Das , Oracle, One Oracle Drive, Nashua, NH 03062, USA
ABSTRACT
The paper addresses the problem of visualizing large scale RDF data via a 3-S approach, namely, by using, 1) Subsets: to present only relevant data for visualisation; both static and dynamic subsets can be specified, 2) Summaries: to capture the essence of RDF data being viewed; summarized data can be expanded on demand thereby allowing users to create hybrid (summary-detail) fisheye views of RDF data, and 3) Sampling: to further optimize visualization of large-scale data where a representative sample suffices. The visualization scheme works with both asserted and inferred triples (generated using RDF(S) and OWL semantics). This scheme is implemented in Oracle by developing a plug-in for the Cytoscape graph visualization tool, which uses functions defined in a Oracle PL/SQL package, to provide fast and optimized access to Oracle Semantic Store containing RDF data. Interactive visualization of a synthesized RDF data set (LUBM 1 million triples), two native RDF datasets (Wikipedia 47 million triples and UniProt 700 million triples), and an OWL ontology (eClassOwl with a large class hierarchy including over 25,000 OWL classes, 5,000 properties, and 400,000 class-properties) demonstrates the effectiveness of our visualization scheme.
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CITATION
Seema Sundara, Eugene Inseok Chong, Vladimir Kolovski, Zhe Wu, Medha Atre, Jagannathan Srinivasan, Souripriya Das, "Visualizing large-scale RDF data using Subsets, Summaries, and Sampling in Oracle", 2013 IEEE 29th International Conference on Data Engineering (ICDE), vol. 00, no. , pp. 1048-1059, 2010, doi:10.1109/ICDE.2010.5447795
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