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2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)
Visualizing large-scale RDF data using Subsets, Summaries, and Sampling in Oracle
Long Beach, CA, USA
March 01-March 06
ISBN: 978-1-4244-5445-7
Seema Sundara, Oracle, One Oracle Drive, Nashua, NH 03062, USA
Medha Atre, Oracle, One Oracle Drive, Nashua, NH 03062, USA
Vladimir Kolovski, Oracle, One Oracle Drive, Nashua, NH 03062, USA
Souripriya Das, Oracle, One Oracle Drive, Nashua, NH 03062, USA
Zhe Wu, Oracle, One Oracle Drive, Nashua, NH 03062, USA
Eugene Inseok Chong, Oracle, One Oracle Drive, Nashua, NH 03062, USA
Jagannathan Srinivasan, Oracle, One Oracle Drive, Nashua, NH 03062, USA
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.
Citation:
Seema Sundara, Medha Atre, Vladimir Kolovski, Souripriya Das, Zhe Wu, Eugene Inseok Chong, Jagannathan Srinivasan, "Visualizing large-scale RDF data using Subsets, Summaries, and Sampling in Oracle," icde, pp.1048-1059, 2010 IEEE 26th International Conference on Data Engineering (ICDE 2010), 2010
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