PERCEPTION

Virtual properties: the different ways of encoding data, such as shape, color, orientation, and so forth

Pre-attentive properties :No attention is required to notice them

Groups

color

Position

Form

Motion

Has attributes like:
Orientation, Line length, Line width,Size,Shape and Enclosure

Has attributes like: Hue and Intensity

Has attributes like: 2D location

Mackinlay criterion

Effectiveness: A visualization is more effective than another visualization if the information conveyed by one visualization is more readily perceived than the information in the other visualization.

Expressiveness: A set of facts is expressible in a visual language if the sentences in the language express all the facts in the set of data, and only the facts in the data.

GRAPH DESIGN PRINCIPLES

Distinct attributes: If you have to display multiple data dimensions in the same graph, make sure not to exceed five distinct attributes to encode them.

Gestalt principles: set of visual characteristics. They can be used to highlight data, tie data together, or separate it

Emphasize exceptions

Annotate data.: with

  • legends
  • axis labels
  • figure caption
  • text bubble

Reduce non-data ink, The data-ink ratio is defined by the amount of ink that is used to display the data in a graph, divided by the total amount of ink that was used to plot the entire graph. Ex,bounding box,grid lines,unnecessary tick marks,three-dimensional bars and background images. want to be near 1

Show causality:

  • Make sure that the viewers have a way to identify the root cause through the graph.
  • This is not always possible in a single graph.In those cases,it might make sense to show a second graph that can be used to identify the root cause

Show comparisons.

  • Instead of just showing the graph with the data to be analyzed,also show a graph that shows “normal”behavior or shows the same data,but from a different time.
  • The viewer can then compare the two graphs to immediately identify anomalies,exceptions,or simply differences.

Connection

Proximity

Continuity

Similarity

Closure

Enclosure:

Humans tend to perceive objects that are almost a closed form as the full form. Ex:eliminate bounding boxes around graphs

Elements that are aligned are perceived as a unit, grid lines are not necessary

Connecting elements groups them together. to display the relationships in data

Objects grouped together in close proximity are perceived as a unit. outliers can be identified

color, shape, orientation, or size, we tend to group similar-looking elements together. use this principle to encode the same data dimensions across multiple displays

Enclosing data points with a bounding box, or putting them inside some shape, groups those elements together. use this principle to highlight data elements in our graphs. Not means bounding boxes

Information Seeking Mantra

  • Overview first
  • zoom and filter
  • details on-demand