RDF Data Exploration and Visualization
Document Type
Conference Proceeding
Publication Date
2007
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Abstract
We present Paged Graph Visualization (PGV), a new semiautonomous 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 performance 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.
Repository Citation
Delgiannidis, L.,
Kochut, K. J.,
& Sheth, A. P.
(2007). RDF Data Exploration and Visualization. CIMS 2007 Proceedings of the ACM First Workshop on CyberInfrastructure: Information in eScience, 39-46.
https://corescholar.libraries.wright.edu/knoesis/225
DOI
10.1145/1317353.1317362
