Title :
Have Green - A Visual Analytics Framework for Large Semantic Graphs
Author :
Wong, Pak Chung ; Chin, George, Jr. ; Foote, Harlan ; Mackey, Patrick ; Thomas, Jim
Author_Institution :
Pacific Northwest Nat. Lab., Richland, WA
fDate :
Oct. 31 2006-Nov. 2 2006
Abstract :
A semantic graph is a network of heterogeneous nodes and links annotated with a domain ontology. In intelligence analysis, investigators use semantic graphs to organize concepts and relationships as graph nodes and links in hopes of discovering key trends, patterns, and insights. However, as new information continues to arrive from a multitude of sources, the size and complexity of the semantic graphs will soon overwhelm an investigator´s cognitive capacity to carry out significant analyses. We introduce a powerful visual analytics framework designed to enhance investigators´ natural analytical capabilities to comprehend and analyze large semantic graphs. The paper describes the overall framework design, presents major development accomplishments to date, and discusses future directions of a new visual analytics system known as Have Green
Keywords :
data visualisation; semantic networks; Have Green; graph visualization; information analytics; information visualization; network visualization; semantic graph; visual analytics framework; Computer displays; Fuses; Information analysis; Laboratories; Ontologies; Pattern analysis; Performance analysis; Software systems; Visual analytics; Visualization; 1.6.9 [Visualization] - Information Visualization, Visualization Systems and Software, Visualization Techniques Methodologies; Graph and Network Visualization; Information Analytics; Information Visualization; Visual Analytics;
Conference_Titel :
Visual Analytics Science And Technology, 2006 IEEE Symposium On
Conference_Location :
Baltimore, MD
Print_ISBN :
1-4244-0591-2
Electronic_ISBN :
1-4244-0592-0
DOI :
10.1109/VAST.2006.261432
