1 / 25

SIMS 247: Information Visualization and Presentation jeffrey heer

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

azra
Download Presentation

SIMS 247: Information Visualization and Presentation jeffrey heer

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. SIMS 247: Information Visualization and Presentationjeffrey heer Network Visualization Oct 31, 2005

  2. today • design review • graph visualization • specifically graph layout • case study: vizster • online social network visualization • happy halloween

  3. design review • Each group, come up and share • What aspect(s) where you trying communicate? • What visual mappings did you consider?

  4. 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

  5. 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

  6. Common Applications • Process Visualization (e.g., Visio) • Dependency Graphs • Biological Interactions (Genes, Proteins) • Computer Networks • Social Networks • Simulation and Modeling

  7. 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.

  8. The Billion $$ Application Integrated Circuits

  9. Traditional Graph Drawing poly-line graphs (includes bends) orthogonal drawing planar, straight-line drawing upward drawing of DAGs

  10. 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

  11. 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)

  12. 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

  13. Tree-ify the graph

  14. 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

  15. Hierarchical Graph Layout • Evolution of the UNIX operating system • Hierarchical layering based on descent

  16. Hierarchical graph layout Gnutella network

  17. 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

  18. 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

  19. 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

  20. Typical Sugiyama layout (dot) - preserves tree structure Our method - preserves edge lengths slide borrowed from Tim Dwyer

  21. slide borrowed from Tim Dwyer Examples

  22. 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…)

  23. 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

  24. Structurally Independent Layout • The “Skitter” Layout • Internet Connectivity • Angle = Longitude • geography • Radius = Degree • # of connections Skitter, www.caida.org

More Related