• Visualization
• data type
  • item
  • attribute
    • attribute type
  • link
  • position
  • grid
  • structured data
  • unstructured data
• symbolic display
  • graph
  • mark
  • channel
    • characteristic of channel
• analysis framework
  • user task
• graph theory
  • centrality
    • degree of vertex
    • betweeness of vertex
    • closeness of vertex
      • geodesic distance between vertex
    • eigenvector of vertex
    • clustering coefficient
• time

Visualization

data type

item

discrete entry

attribute

measured property

attribute type

• nominal (categorical)

  with equality relationship

• ordinal

  with order

• quantitative (numerical)

  with algebra

  • ratio: with meaningful $0$
  • interval

link

relationship between item

position

spatial location

grid

sampling strategy for continuous data

structured data

• table: item & attribute
  • flat
  • multi-dimensional
• network: item & attribute & link
• field: grid & attribute
• geometry: position

unstructured data

text, audio, graphics…

symbolic display

• parallel coordinate
• treemap
• field
• choropleth map
• star plot

graph

• framework
  • scale
• content
  • mark
• label
  • title
  • axis

mark

represent item, link

• point
• line
• area

channel

represent attribute

• position
• color
  • hue
  • saturation
  • luminance
• shape
  • glyph
• tilt
• size
• area
• texture

characteristic of channel

• selective
• associative
• quantitative
• order
• length

analysis framework

four level

• domain situation
• data/task abstraction
• visual encoding/interaction idiom
• algorithm

three question

• what
• why
• how

user task

• query
  • retrieve value
  • find extremum
  • determine range
• search
  • sort
  • filter
• consume
  • compute derived value
  • characterize distribution
  • find anomaly
  • cluster
  • correlate

graph theory

$G(V,E)$

• independent set: no edge
• clique: all possible edge
• path: all edge can be consecutively traversed
• tree: no cycle
• network
• unconnected graph
• biconnected graph: no articulation point
  • articulation point: break the graph if deleted
• bipartite graph: edge between only vertex for two set

centrality

quantity to measure vertex importance

degree of vertex

number of connected node

• in-degree/ out degree for directed graph

betweeness of vertex

sum of number of shortest path through the vertex divided by number of shortest path between each pair of vertex

$$B(i)=\sum _{a,b}\frac{g_{aib}}{g_{ab}}$$

closeness of vertex

sum of geodesic distance between the vertex and every other

$$C(i)=\sum _{j}d(i,j)$$

geodesic distance between vertex

number of edge between them on the shortest path

eigenvector of vertex

adjacency matrix dot vector of degree

clustering coefficient

time