PGV - Revision history

Leon at 16:42, 13 April 2009

2009-04-13T16:42:43Z

Leon at 16:42, 13 April 2009

2009-04-13T16:42:25Z

Leon at 16:41, 13 April 2009

2009-04-13T16:41:38Z

Leon at 16:37, 13 April 2009

2009-04-13T16:37:29Z

Leon at 16:36, 13 April 2009

2009-04-13T16:36:16Z

Leon at 16:35, 13 April 2009

2009-04-13T16:35:12Z

Leon at 16:33, 13 April 2009

2009-04-13T16:33:48Z

Leon: New page: Paper: [http://knoesis.wright.edu/library/resource.php?id=00330 RDF data exploration and visualization]

2009-04-13T16:32:22Z

New page: Paper: [http://knoesis.wright.edu/library/resource.php?id=00330 RDF data exploration and visualization] </LI>

New page

Paper: [http://knoesis.wright.edu/library/resource.php?id=00330 RDF data exploration and visualization] </LI>

← Older revision		Revision as of 16:42, 13 April 2009
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−	<table><tr><td> [[Image:PGV2_LOGO.png]] </td>	+	<table width="770"><tr><td> [[Image:PGV2_LOGO.png]] </td>

	<td> <P>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 visual-ize 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 re-sponse 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.</P></td></tr></table>		<td> <P>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 visual-ize 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 re-sponse 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.</P></td></tr></table>

@@ Line 1: / Line 1: @@
-[[Image:PGV2_LOGO.png]]
+<table><tr><td> [[Image:PGV2_LOGO.png]] </td>
-<table><tr><td>
-<P>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 visual-ize 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 re-sponse 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.</P>
+<td> <P>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 visual-ize 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 re-sponse 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.</P></td></tr></table>
 </td>
-<td> [[Image:Snap1.png]] </td></tr></table>
+[[Image:Snap1.png]]
 <UL>
 <LI> Paper: [http://knoesis.wright.edu/library/resource.php?id=00330 RDF data exploration and visualization] </LI>

@@ Line 1: / Line 1: @@
 [[Image:PGV2_LOGO.png]]
 <P>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 visual-ize 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 re-sponse 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.</P>
-[[Image:Snap1.png]]
+</td>
 <UL>
 <LI> Paper: [http://knoesis.wright.edu/library/resource.php?id=00330 RDF data exploration and visualization] </LI>

@@ Line 1: / Line 1: @@
 [[Image:PGV2_LOGO.png]]
 <P>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 visual-ize 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 re-sponse 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.</P>
+[[Image:Snap1.png]]
 <UL>
 <LI> Paper: [http://knoesis.wright.edu/library/resource.php?id=00330 RDF data exploration and visualization] </LI>

← Older revision		Revision as of 16:36, 13 April 2009
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		+	[[Image:PGV2_LOGO.png]]
	<P>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 visual-ize 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 re-sponse 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.</P>		<P>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 visual-ize 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 re-sponse 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.</P>

← Older revision		Revision as of 16:35, 13 April 2009
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	<P>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 visual-ize 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 re-sponse 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.</P>		<P>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 visual-ize 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 re-sponse 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.</P>

−	Paper: [http://knoesis.wright.edu/library/resource.php?id=00330 RDF data exploration and visualization] </LI>	+	<UL>
		+	<LI> Paper: [http://knoesis.wright.edu/library/resource.php?id=00330 RDF data exploration and visualization] </LI>
		+	<LI> [http://www.cs.uga.edu/~ldeligia/PUBLIC/PROJECTS/PGV/ More information on this project]</LI>
		+	</UL>
		+	Contact Information: Dr. Leon Deligiannidis (leon AT knoesis.org)

← Older revision		Revision as of 16:33, 13 April 2009
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		+	<P>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 visual-ize 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 re-sponse 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.</P>
		+
	Paper: [http://knoesis.wright.edu/library/resource.php?id=00330 RDF data exploration and visualization] </LI>		Paper: [http://knoesis.wright.edu/library/resource.php?id=00330 RDF data exploration and visualization] </LI>