Sims 247 information visualization and presentation jeffrey heer
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SIMS 247: Information Visualization and Presentation jeffrey heer. Network Visualization Oct 31, 2005. today. design review graph visualization specifically graph layout case study: vizster online social network visualization happy halloween. design review. Each group, come up and share

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Sims 247 information visualization and presentation jeffrey heer

SIMS 247: Information Visualization and Presentationjeffrey heer

Network Visualization

Oct 31, 2005


Today

today

  • design review

  • graph visualization

    • specifically graph layout

  • case study: vizster

    • online social network visualization

  • happy halloween


Design review

design review

  • Each group, come up and share

    • What aspect(s) where you trying communicate?

    • What visual mappings did you consider?


Graphs and trees

Graphs and Trees

  • Graphs:

    • Representations of structured, connected data

    • Consist of a set of nodes (data) and a set of edges (relations)

    • Edges can be directed or undirected

  • Trees:

    • Graphs with a specific structure

      • connected graph with n-1 edges

    • Representations of data with natural hierarchy

    • Nodes are either parents or children


When is graph visualization applicable

When is Graph Visualization Applicable?

  • Ask the question: is there an inherent relation among the data elements to be visualized?

    • If YES – then the data can be represented by nodes of a graph, with edges representing the relations.

    • If NO – then the data elements are “unstructured” and goal is to use visualization to analyze and discover relationships among data.

      Source: Herman, Graph Visualization and Navigation in Information Visualization: a Survey


Common applications

Common Applications

  • Process Visualization (e.g., Visio)

  • Dependency Graphs

  • Biological Interactions (Genes, Proteins)

  • Computer Networks

  • Social Networks

  • Simulation and Modeling


Graph layout

Graph Layout

  • How to position the nodes and edges?

  • The primary concern with networks

    • while inheriting other issues such as color, size, etc

  • The topic of the Graph Drawing conference (as well as numerous InfoVis papers) and even multiple books.


The billion application

The Billion $$ Application

Integrated Circuits


Traditional graph drawing

Traditional Graph Drawing

poly-line graphs (includes bends)

orthogonal drawing

planar, straight-line drawing

upward drawing of DAGs


Traditional graph drawing1

Traditional Graph Drawing

  • Optimization based on a set of criteria

  • (mathematical aesthetics)

    • Minimize edge crossings

    • Minimize area

    • Maximize smallest angle

    • Maximize symmetry

    • BUT, can’t do all at once

  • Often unsuitable for interactive visualization

    • Many optimizations are NP-Hard (runs ~forever)

      • Approximation algorithms very complex

    • Unless you only need to compute layout once

      • Precompute layout, or compute once at the beginning of an application then support interaction


Layout approaches

Layout Approaches

  • Tree-ify the graph - then use tree layout

  • Hierarchical graph layout

  • Optimization-based techniques

  • Adjacency matrices

  • Structurally-independent layout

  • (this list is not meant to be exhaustive)


Tree based graph layout

Tree-based graph layout

  • Select a tree-structure out of the graph

    • Breadth-first-search tree

    • Minimum spanning tree

    • Other domain-specific structures

  • Use a tree layout algorithm

  • Benefits

    • Fast, supports interaction and refinement

  • Drawbacks

    • Limited range of layouts


Tree ify the graph

Tree-ify the graph


Hierarchical graph layout

Hierarchical graph layout

  • Use directed structure of graph to inform layout

  • Order the graph into distinct levels

    • this determines one dimension

  • Now optimize within levels

    • determines the second dimension

    • minimize edge crossings, etc

  • The method used in graphviz’s “dot” algorithm

  • Great for directed acyclic graphs, but often misleading in the case of cycles


Hierarchical graph layout1

Hierarchical Graph Layout

  • Evolution of the UNIX operating system

  • Hierarchical layering based on descent


Hierarchical graph layout2

Hierarchical graph layout

Gnutella network


Optimization based layout

Optimization-based layout

  • Specify constraints for layout

    • Series of mathematical equations

    • Hand to “solver” which tries to optimize the constraints

  • Examples

    • Minimize edge crossings, line bends, etc

    • Multi-dimensional scaling (preserve multi-dim distance)

    • Force-directed placement (use physics metaphor)

  • Benefits

    • General applicability

    • Often customizable by adding new constraints

  • Drawbacks

    • Approximate constraint satisfaction

    • Running time; “organic” look not always desired


Example force directed layout

Example: Force-Directed Layout

Uses physics model to layout graph

Nodes repel each other, edges act as springs, and some amount of friction or drag force is used

visual thesaurus - plumbdesign


Hybrid approaches also possible

Hybrid approaches also possible

  • Dig-CoLa algorithm

    • “Directed Graph Constraint Optimization Layout”?

    • Determines hierarchy levels

    • Then uses this as additional constraints to an optimization-based layout

    • InfoVis 2005 Best Paper


Sims 247 information visualization and presentation jeffrey heer

Typical Sugiyama layout (dot)

- preserves tree structure

Our method

- preserves edge lengths

slide borrowed from Tim Dwyer


Examples

slide borrowed from Tim Dwyer

Examples


Adjacency matrices

Adjacency Matrices

  • So far, only looked at node-link diagrams

  • Often doesn’t scale well due to edge-crossings, occlusion, etc. --> hard to read

  • One solution: adjacency matrix

    • show graph as table

    • nodes as rows/columns

    • edges as table cells

  • (We’ll read a study of this approach later on…)


Structurally independent layout

Structurally-Independent Layout

  • Simple. Just ignore the graph structure.

  • Base the layout on other attributes of the data

  • Examples:

    • Geography

    • Time

  • Benefits

    • Often very quick layout

    • Optimizes communication of particular features

  • Drawbacks

    • May or may not present structure well


Structurally independent layout1

Structurally Independent Layout

  • The “Skitter” Layout

    • Internet Connectivity

  • Angle = Longitude

    • geography

  • Radius = Degree

    • # of connections

Skitter, www.caida.org


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