Difference between revisions of "Lesson05"

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** R packages
 
** R packages
  
Network Visualisation and Analysis
+
Graph layouts
Network visualisation and analysis process model
+
* Node-and-link layouts
Graph layouts and visual attributes
+
* Force-directed layout
Network metrics
+
* Node-only layout
Network Data Processing, Visualisation and Analysis with R
+
* Adjacency matrix
  
 +
Visual Attributes
 +
* Key node attributes
 +
* Key edge attributes
 +
* Bundles, shapes, images, and more
  
Data Visualisation Through Their Graph Representation
+
Visual Analysis of Network Graphs
* Basic concept of graph
+
* Relationships
* Data and graph
+
* Hierarchies
* Where to find the data?
+
* Communities
 +
* Flows
 +
* Spatial networks
  
Network Graph Drawing
+
= Readings =
*  Hierarchical tress
 
*  Spanning trees
 
*  Networks
 
*  Directed graphs
 
*  Treemaps
 
  
Network Graph Layout Techniques
+
== Core readings==
*  Force-directed techniques
 
*  Multidimensional scaling
 
*  The pulling under constrains model
 
*  Bipartite graphs
 
  
Applications of Network Visualisation
+
== Other readings==
*  Organisation network
 
*  Business network [http://www.theyrule.net/2004/tr2.php]
 
*  Political network [http://www.cs.umd.edu/hcil/socialaction/]
 
*  Social network [http://hci.stanford.edu/jheer/projects/vizster/]
 
*  News network
 

Revision as of 10:50, 6 February 2020

Vaa logo.jpg ISSS608 Visual Analytics and Applications

About

Weekly Session

Assignment

Visual Analytics Project

Course Resources

 


Network Data Visualisation and Analysis

Content

Introduction to Graph Data Visualisation

  • Basic principles of network graph
  • Graph data visualisation in actions

Network Graph Data

  • Network data sets
  • Graph data format
  • Graph Database

Network Graph Visualisation Tools

  • Designer toolkit
    • Gephi
  • Programmer toolkit
    • R packages

Graph layouts

  • Node-and-link layouts
  • Force-directed layout
  • Node-only layout
  • Adjacency matrix

Visual Attributes

  • Key node attributes
  • Key edge attributes
  • Bundles, shapes, images, and more

Visual Analysis of Network Graphs

  • Relationships
  • Hierarchies
  • Communities
  • Flows
  • Spatial networks

Readings

Core readings

Other readings