NETWORK DATA VISUAL ADJACENCY LISTS FOR DYNAMIC GRAPHS Authors: - - PowerPoint PPT Presentation

network data visual adjacency lists for dynamic graphs
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NETWORK DATA VISUAL ADJACENCY LISTS FOR DYNAMIC GRAPHS Authors: - - PowerPoint PPT Presentation

NETWORK DATA VISUAL ADJACENCY LISTS FOR DYNAMIC GRAPHS Authors: Marcel Hlawatsch, Michael Burch, and Daniel Weiskopf Presented by: Arash Saghafi Overview Idiom Visual Adjacency Lists What: Data Network: Static and Dynamic Graphs Derived a


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NETWORK DATA VISUAL ADJACENCY LISTS FOR DYNAMIC GRAPHS

Authors: Marcel Hlawatsch, Michael Burch, and Daniel Weiskopf Presented by: Arash Saghafi

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Overview

Overview

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Idiom Visual Adjacency Lists What: Data Network: Static and Dynamic Graphs What: Derived Derived a list: Vertical axis for all the nodes, horizontal for corresponding target nodes Why: Tasks Detecting link distributions (static graphs) and node traffic over time (dynamic graphs) How: Encode Nodes ordered by certain properties (e.g. summed weight of outgoing links), coded with colour, size reflects weight Scale Good scalability with respect to the number of nodes. Cluster structures have lower resolution.

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Overview

Adjacency Lists for Static Graphs

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Overview

Adjacency Lists for Dynamic Graphs

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Gantt Layout:

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Overview

Advantages and Disadvantages of Adjacency Lists

  • Advantage: Pattern Detection
  • Normal Layout:
  • Gantt Layout:

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  • Disadvantage: Cluster Detection
  • Disadvantage: Following a Path
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Overview

User Study and Tasks

  • 24 university student subjects
  • Independent variables:
  • Visualization technique
  • Size (Small: 8 nodes, 22-40 links; Large: 20 nodes, 147-264 links)
  • 1x4 within subjects design. Tasks were presented in order:
  • Task 1: Decide if a link exists between the two marked nodes.
  • Task 2: Decide if incoming or outgoing links are more equally

distributed over the nodes.

  • Task 3: Select the node, where the weights of its incoming links cover

the largest value range.

  • Task 4: Select the node, where the weights of all incoming links have a

large increase between two subsequent time steps.

  • Dependent variables:
  • Error rate
  • Time

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Overview

User Study Results

  • Task 1:

Links between two nodes.

  • Task 2:

Distribution of incoming and outgoing links.

  • Task 3:

Weights of incoming covers largest value.

  • Task 4:

Weight of incoming increases over time.

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Overview

Summary

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Idiom Visual Adjacency Lists What: Data Network: Static and Dynamic Graphs What: Derived Derived a list: Vertical axis for all the nodes, horizontal for corresponding target nodes Why: Tasks Detecting link distributions (static graphs) and node traffic over time (dynamic graphs) How: Encode Nodes ordered by certain properties (e.g. summed weight of outgoing links), coded with colour, size reflects weight Scale Good scalability with respect to the number of nodes. Cluster structures have lower resolution.

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QUESTIONS?