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+ CPSC 100 > Data Visualization > Flashcards

Data Visualization Flashcards

1
Q

What are visualizations?

A

combine and integrate visual marks into more complex structural forms to encode information

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2
Q

What do visualizations help do?

A
  • illustrate relations
  • discover trends, patterns, and outliers
  • get and keep the attention of recipients
  • support remembrance and recall
  • facilitate learning
  • motivate people and establish a mutual story and initiate actions by illustrating options to act
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3
Q

What are the 9 Gestalt Principles?

A
  • proximity
  • similarity
  • enclosure
  • connection
  • continuity
  • symmetry
  • figure and ground
  • closure
  • common fate
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4
Q

Gestalt Principle

What is proximity?

A

how close elements are to one another – similar things should be close to each other

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5
Q

Gestalt Principle

What is similarity?

A

people tend to see things that physically resemble each other as part of the same object

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6
Q

Gestalt Principle

What is enclosure?

A

we group elements that are in the same closed region

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7
Q

Gestalt Principle

What is connection?

A

grouping effect – we perceive elements as connected to each other thanks to colors, lines, frames, or other shapes

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8
Q

Gestalt Principle

What is continuity?

A

objects that create a continuous pattern or are seen as being connected appear to be grouped together

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9
Q

Gestalt Principle

What is symmetry?

A

elements that are symmetrical tend to be perceived as a unified group

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10
Q

Gestalt Principle

What is figure and ground?

A

your brain distinguishes foreground and background

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11
Q

Gestalt Principle

What is closure?

A

our eyes tend to add any missing pieces of a familiar shape

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12
Q

Gestalt Principle

What is common fate?

A

people will group together things that point to or are moving in the same direction

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13
Q

What are the 4 data presentation principles?

A
  • understand the purpose – exploratory vs. explanatory
  • understand what is to be communicated – most important message you are trying to convey
  • choose appropriate visual representation
  • quality of presentation – put more emphasis on (from higher to lower): location, size, colour
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14
Q

What are the 5 principles for creating infographics?

A
  • simplicity
  • consistency
  • visibility
  • navigability
  • suitablity
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15
Q

Principles for Creating Infographics

What is simplicity?

A

minimal text
clear message
avoid clutter

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16
Q

Principles for Creating Infographics

What is consistency?

A

layout and design elements should be consistent

  • 2-3 font sizes
  • color scheme
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17
Q

Principles for Creating Infographics

What is visibility?

A

appropriate font sizes

colors that contrast

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18
Q

Principles for Creating Infographics

What is navigability?

A

(structure)
clear order to follow

use scale/proportion to emphasize key points/headings

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19
Q

Principles for Creating Infographics

What is suitability?

A

right data for message

right graphic for the message

right metaphors for the audience

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20
Q

Common Patterns – Visualization vs. Infographic

A

visualization

  • exploratory
  • lots of data
  • informs
  • little text

infographic:

  • explanatory
  • little data
  • persuades
  • more text
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21
Q

Scales for Comparing Values – More Accurate to Less Accurate

A 
position common scale
position non-aligned scale
length
direction
angle
area
volume
curvature
shading
color saturation
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22
Q

What are the visualization formats for comparing categories?

A

bar chart:

  • bar chart
  • stacked bar chart
  • grouped bar chart

pie chart

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23
Q

What scale does bar chart use?

A

position common scale

24
Q

What are bar charts good for?

A
  • comparisons

- bar chart’s discrete data is categorical data, therefore answers the question of “how many” in each category

25
Q

What is stacked bar chart good for?

What are limitations?

A

proportions, parts to a whole, comparisons

limitations:

  • more segments per bar = harder to read
  • hard to compare segments to each other, as they’re not aligned on a common baseline
26
Q

What are grouped bar charts good for?

What are limitations?

A

distribution, relationships, comparisons

limitation:
- harder to read the more bars you have in one group

27
Q

What are pie charts used for?

A

comparison, parts to a whole, proportions

28
Q

What are limitations of pie charts?

A
  • can only show few values
  • takes up more space than alternatives
  • not good for accurate comparisons
29
Q

What scale does pie chart use?

A

area

30
Q

When is it good to use pie chart?

A

very rare occasions – ie. in interactive situations, looking to see if exactly two things are equal

31
Q

What is an area chart?

A

line graphs but with area below the line filled in

used to show trends rather than convey specific values, distribution

32
Q

What is a stacked area chart similar to?

A

bar chart, but the focus is trend over time

good for: comparisons, trend over time

33
Q

What are visualization formats for multiple attributes?

A
  • bubble chart
  • parallel coordinates
  • radar chart
34
Q

What are parallel coordinate charts?

A
  • common way of representing multivariate numerical data

- each variable is given its own axis

35
Q

What are parallel coordinate charts good for?

What are limitations?

A

good for: comparisons, relationships

limitations: over-cluttered, use interaction to address this

36
Q

What are radar charts?

A
  • used for comparing multiple quantitative variables
  • useful for seeing which variables are scoring high or low
  • relationships
37
Q

What are limitations of radar charts?

A
  • cluttered when we have multiple polygons or variables

- not good for comparing values across each variable

38
Q

What are bubble charts?

A
  • multivariable graph – cross between scatter plot and area chart
  • uses Cartesian coordinate system to plot points on grid
  • X and Y are separate variables
  • uses size to represent another variable
  • can use colour
  • 4 variables
39
Q

What are bubble charts good for?

What are limitations?

A

good for: comparisons, trends over time, distribution, proportions, relationships

limitations: area for comparison is not good

40
Q

What are visualization formats for relationships and hierarchies?

A
  • tree map
  • scatterplot
  • tree diagram
  • network graph
41
Q

What is a tree map?

A
  • alternative way to representing hierarchical structure

- displays quantities for each category

42
Q

What is a scatterplot good for?

A

relationships (ie. correlation), paired numerical data

can be 3D

43
Q

What are tree diagrams?

A

often used to show relations and descent

44
Q

What are network graphs?

A

shows how things are interconnected through use of nodes/vertices, and link lines to represent their connections and help illuminate the type of relationships between a group of entities

45
Q

What are limitations of network graphs?

A
  • limited data capacity

- starts to become hard to read when there are too many nodes (resemble ‘hairballs’)

46
Q

What are visualization formats for visualizing spatial data?

A
  • map with embedded charts

- chloropleth map

47
Q

What is a chloropleth map?

A

display divided geographical areas or regions that are colored, shaded or patterned in relation to a data variable

provides a way to visualize values over a geographical area, which can show variation or patterns across the displayed location

requires legend

48
Q

What are chloropleth maps food for?

What are limitations?

A

good for: comparisons, location

downside:
- use of colour – can’t accurately read/compare values from map
- larger regions appear more emphasized than smaller ones, so viewer’s perception of shaded values are affected

49
Q

What are elaborate visualization formats?

A
  • word cloud
  • stream graph
  • alluvial or sankey diagram
50
Q

What is a word cloud?

A

displays how frequently words appear in a given body of text, by making size of each word proportional to its frequency

51
Q

What is a word cloud good for?

What are limitations?

A

good for: proportions, text analysis, distribution

limitations:
- long words are emphasized over short words
- not great for analytical accuracy – used more for aesthetic purposes

52
Q

What are limitations of static visualizations?

A
  • difficult to represent large amounts of data

- inability to properly support the question and answer process involved in data analysis

53
Q

What do interactions allow us to do?

A
  • control flow of data
  • be active participants in the analysis of data
  • adjust features of the tool to suit the user’s needs
54
Q

What are ethical considerations of visualizations?

A
  • not fact

- accuracy depends on quality of data used, representation of data, objective of the creator

55
Q

What is bad quality data?

A
  • incorrect data
  • missing data
  • insufficient data
  • GIGO
56
Q

How can data representation be misleading?

A
  • truncated graphs
  • exaggerated scaling
  • improper extraction
  • misusing metaphors (ie. is green good or bad, is red good or bad)
  • flawed representations

+ CPSC 100 (9 decks)

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