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  1. Proceedings of the ACM first workshop on CyberInfrastructure: information management in eScience (CIMS '07)
  2. RDF data exploration and visualization
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A volcano erupts: semantically mediated integration of heterogeneous volcanic and atmospheric data
A conceptual modeling and execution framework for process based scientific applications
SLOQUE: slot-based query expansion for complex questions
Measuring referential integrity in distributed databases
ChemXSeer: a digital library and data repository for chemical kinetics
Metadata management for federated databases
Effective ranked conceptual retrieval
Perfect hash functions for large dictionaries
Towards a SOA infrastructure for statistically analysing public health data
RDF data exploration and visualization
Management and preservation of research data with iRODS

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RDF data exploration and visualization

Content Provider ACM Digital Library
Author Deligiannidis, Leonidas Sheth, Amit P. Kochut, Krys J.
Abstract We present Paged Graph Visualization (PGV), a new semi-autonomous tool for RDF data exploration and visualization. PGV consists of two main components: a) the "PGV explorer" and b) the "RDF pager" module utilizing BRAHMS, our high per-formance main-memory RDF storage system. Unlike existing graph visualization techniques which attempt to display the entire graph and then filter out irrelevant data, PGV begins with a small graph and provides the tools to incrementally explore and visualize relevant data of very large RDF ontologies. We implemented several techniques to visualize and explore hot spots in the graph, i.e. nodes with large numbers of immediate neighbors. In response to the user-controlled, semantics-driven direction of the exploration, the PGV explorer obtains the necessary sub-graphs from the RDF pager and enables their incremental visualization leaving the previously laid out sub-graphs intact. We outline the problem of visualizing large RDF data sets, discuss our interface and its implementation, and through a controlled experiment we show the benefits of PGV.
Starting Page 39
Ending Page 46
Page Count 8
File Format PDF
ISBN 9781595938312
DOI 10.1145/1317353.1317362
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2007-11-09
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Ontology visualization Incremental data exploration
Content Type Text
Resource Type Article
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