Transcription
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionNetwork visualization techniques andevaluationMohammad G HONIEMThe Charlotte Visualization CenterUniversity of North Carolina, CharlotteMarch 15th 2007Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionOutline1Definition and motivation of Infovis2Visualization of structured dataVisualization of hierarchical dataVisualization of network data3Visualization of dense and dynamic networksThe matrix-based representation of graphsApplication to constraint-oriented programming graphs4ConclusionMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionOutline1Definition and motivation of Infovis2Visualization of structured dataVisualization of hierarchical dataVisualization of network data3Visualization of dense and dynamic networksThe matrix-based representation of graphsApplication to constraint-oriented programming graphs4ConclusionMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionOutline1Definition and motivation of Infovis2Visualization of structured dataVisualization of hierarchical dataVisualization of network data3Visualization of dense and dynamic networksThe matrix-based representation of graphsApplication to constraint-oriented programming graphs4ConclusionMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionOutline1Definition and motivation of Infovis2Visualization of structured dataVisualization of hierarchical dataVisualization of network data3Visualization of dense and dynamic networksThe matrix-based representation of graphsApplication to constraint-oriented programming graphs4ConclusionMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionInformation VisualizationDefinitionA compact graphical representationA graphical user interfaceFor the visualization and interaction with large numbers ofitemsthat may be a subset of an even larger dataset.Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionInformation VisualizationScope and usefulnessBears on data that are:abstract, multi-dimensional, structured or unstructured.in order to:Make discoveries, decisions, find explanations, orcommunicate aboutvisual patterns(trends, clusters, outliers, . . .)groups of items,individual items.Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionInformation VisualizationHistorical backgroundConsiderable leap in hardware technology and capabilitiesProduction and storage of large volumes of data;Increased processing capabilities;Improved display capabilities.Birth of data miningMathematical and statistical data analysis;Visual information exploration.Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionInformation VisualizationPrinciples and roleMake the best use of human visiondetect patterns,sense correlations,confirm an intuition or formulate hypotheses.Make the best use of user’s expertiseinteractive exploration,interactive construction of views.Precedes but does not replace classical data mining.Provides robust solutions for the most frequent datastructures.Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataOrganisation1Definition and motivation of Infovis2Visualization of structured dataVisualization of hierarchical dataVisualization of network data3Visualization of dense and dynamic networksThe matrix-based representation of graphsApplication to constraint-oriented programming graphs4ConclusionMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataTree Visualization Techniques2D representationsNode-link diagrams (cartesian / circular)Space-filling techniques (treemaps, icicle trees, circular)Non-euclidian space (hyperbolic trees)3D representationsNode-link diagrams (cone trees)Non-euclidian space (hyperbolic trees)Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataOverview of Tree VisualizationsMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataOverview of Tree VisualizationsMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataOverview of Tree VisualizationsMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataOverview of Tree VisualizationsMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataOverview of Tree VisualizationsMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataOverview of Tree VisualizationsMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataOverview of Tree VisualizationsMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataOverview of Tree VisualizationsMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataOrganisation1Definition and motivation of Infovis2Visualization of structured dataVisualization of hierarchical dataVisualization of network data3Visualization of dense and dynamic networksThe matrix-based representation of graphsApplication to constraint-oriented programming graphs4ConclusionMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataGraph theory basicsDefinitionsG (V, E),E {(u, v )}, where (u, v ) V V,two vertices are adjacent if they are connected by an edge,an edge is directed if an order is defined on its extremities,a graph is directed if its edges are directed,a directed path is a sequence of vertices (v1 , · · · , vk )where (vi , vi 1 ) E i k,a directed path is a cycle if (vk , v1 ) E,a directed graph is acyclic if it is cycle free,a graph is planar if it has an intersection free 2D drawing.Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataGraphs are ubiquitousExamplesInfrastructure networks (telecommunications, power,roads).Social networks (acquaintances, crime networks).Co-citation network, etc.Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataGraphs and representationsDefinitiona graph is an abstract entity 6 its representations.LayoutMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataGraph visualization techniquesVisualization techniquesNode-link diagrams,Adjacency matrices.Aesthetic rules and drawing conventionsDrawing conventions: polyline drawing, grid drawing,upward/downward etc.Aesthetic rules: min. intersections, min. edge length, min.area etc.Some rules are conflicting.Some user studies and experiments (H. Purchase, C.Ware).Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataGraph visualization techniquesGraph drawing approachesMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataGraph visualization techniquesGraph drawing approachesMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataGraph visualization techniquesGraph drawing approachesMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataGraph visualization techniquesGraph drawing approachesMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataGraph visualization overviewMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataGraph visualization frameworksExisting frameworksTulip (University of Bordeaux – France),Pajek (University of Ljubljani – Slovenia),GraphViz (AT&T),JUNG (University of California, Irvine).Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataGraph visualization techniquesNode-link diagramsWidespread and well studied wrt sparse graphs.Cluttered views when link density increases.Instable layout algorithmsUnusable for dynamic graphs.Begs for an alternate representation.Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataMonitoring co-activity graphsVariables ConstraintsXYZMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataMonitoring co-activity graphsVariables ConstraintsXc1YZMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataMonitoring co-activity graphsVariables ConstraintsXc2c1Yc3ZMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataMonitoring co-activity graphsVariables ConstraintsVariablesXXc2YZc1Yc3ZMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataMonitoring co-activity graphsVariables mad G HONIEMc1c2Network visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataMonitoring co-activity graphsVariables ConstraintsVariablesXc2c1X 2XYZX 3YContraintesc3c3ZMohammad G HONIEMc1c2Network visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataMonitoring co-activity graphsVariables ConstraintsVariablesXc2c1X 2XYZX 3YContraintesc3c3ZMohammad G HONIEMc1c2Network visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataMonitoring co-activity graphsVariables ConstraintsVariablesXc2c1X 2XYZX 3YContraintesX 3c3c3ZMohammad G HONIEMX 2c1c2Network visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataCo-activity graphsThe 8 queen problemMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionVisualization of hierarchical dataVisualization of network dataCo-activity graphsThe 8 queen problemMohammad G HONIEMCo-activity graphNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionThe matrix-based representation of graphsApplication to constraint-oriented programming graphsOrganisation1Definition and motivation of Infovis2Visualization of structured dataVisualization of hierarchical dataVisualization of network data3Visualization of dense and dynamic networksThe matrix-based representation of graphsApplication to constraint-oriented programming graphs4ConclusionMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionThe matrix-based representation of graphsApplication to constraint-oriented programming graphsMatrix-based representation of graphsMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionThe matrix-based representation of graphsApplication to constraint-oriented programming graphsMatrix-based representation of graphsStrengthsRelies on a well-known mathematical representation.No clutter nor occlusion.Orderable, predictible for most common order relations.Displays existing and missing links.ShortcomingsUnfamiliar visualization.Not effective for path related tasks.Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionThe matrix-based representation of graphsApplication to constraint-oriented programming graphsMatrix-based representation of graphsStrengthsRelies on a well-known mathematical representation.No clutter nor occlusion.Orderable, predictible for most common order relations.Displays existing and missing links.ShortcomingsUnfamiliar visualization.Not effective for path related tasks.Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionThe matrix-based representation of graphsApplication to constraint-oriented programming graphsMatrix-based representation of graphsStrengthsRelies on a well-known mathematical representation.No clutter nor occlusion.Orderable, predictible for most common order relations.Displays existing and missing links.ShortcomingsUnfamiliar visualization.Not effective for path related tasks.Mohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionThe matrix-based representation of graphsApplication to constraint-oriented programming graphsThe matrix of BertinMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionThe matrix-based representation of graphsApplication to constraint-oriented programming graphsCluster revelation through permutationsOrderability magicMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionThe matrix-based representation of graphsApplication to constraint-oriented programming graphsCluster revelation through permutationsOrderability magicMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionThe matrix-based representation of graphsApplication to constraint-oriented programming graphsMatrix-based representation of graphsProperties of matricesMohammad G HONIEMNetwork visualization techniques and evaluation
Definition and motivation of InfovisVisualization of structured dataVisualization of dense and dynamic networksConclusionThe matrix-ba
Visualization of hierarchical data Visualization of network data Graph visualization techniques Node-link diagrams Widespread and well studied wrt sparse graphs. Cluttered views when link density increases. Instable layout algorithms Unusable
