+ CPSC 100 > Data Visualization > Flashcards

Data Visualization Flashcards

(56 cards)

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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?

Study These Flashcards
A

position common scale

24
Q

What are bar charts good for?

Study These Flashcards
A
  • comparisons

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

25
What is stacked bar chart good for? What are limitations?
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
What are grouped bar charts good for? What are limitations?
distribution, relationships, comparisons limitation: - harder to read the more bars you have in one group
27
What are pie charts used for?
comparison, parts to a whole, proportions
28
What are limitations of pie charts?
- can only show few values - takes up more space than alternatives - not good for accurate comparisons
29
What scale does pie chart use?
area
30
When is it good to use pie chart?
very rare occasions – ie. in interactive situations, looking to see if exactly two things are equal
31
What is an area chart?
line graphs but with area below the line filled in used to show trends rather than convey specific values, distribution
32
What is a stacked area chart similar to?
bar chart, but the focus is trend over time good for: comparisons, trend over time
33
What are visualization formats for multiple attributes?
- bubble chart - parallel coordinates - radar chart
34
What are parallel coordinate charts?
- common way of representing multivariate numerical data | - each variable is given its own axis
35
What are parallel coordinate charts good for? What are limitations?
good for: comparisons, relationships limitations: over-cluttered, use interaction to address this
36
What are radar charts?
- used for comparing multiple quantitative variables - useful for seeing which variables are scoring high or low - relationships
37
What are limitations of radar charts?
- cluttered when we have multiple polygons or variables | - not good for comparing values across each variable
38
What are bubble charts?
- 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
What are bubble charts good for? What are limitations?
good for: comparisons, trends over time, distribution, proportions, relationships limitations: area for comparison is not good
40
What are visualization formats for relationships and hierarchies?
- tree map - scatterplot - tree diagram - network graph
41
What is a tree map?
- alternative way to representing hierarchical structure | - displays quantities for each category
42
What is a scatterplot good for?
relationships (ie. correlation), paired numerical data can be 3D
43
What are tree diagrams?
often used to show relations and descent
44
What are network graphs?
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
What are limitations of network graphs?
- limited data capacity | - starts to become hard to read when there are too many nodes (resemble ‘hairballs’)
46
What are visualization formats for visualizing spatial data?
- map with embedded charts | - chloropleth map
47
What is a chloropleth map?
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
What are chloropleth maps food for? What are limitations?
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
What are elaborate visualization formats?
- word cloud - stream graph - alluvial or sankey diagram
50
What is a word cloud?
displays how frequently words appear in a given body of text, by making size of each word proportional to its frequency
51
What is a word cloud good for? What are limitations?
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
What are limitations of static visualizations?
- difficult to represent large amounts of data | - inability to properly support the question and answer process involved in data analysis
53
What do interactions allow us to do?
- control flow of data - be active participants in the analysis of data - adjust features of the tool to suit the user’s needs
54
What are ethical considerations of visualizations?
- not fact | - accuracy depends on quality of data used, representation of data, objective of the creator
55
What is bad quality data?
- incorrect data - missing data - insufficient data - GIGO
56
How can data representation be misleading?
- truncated graphs - exaggerated scaling - improper extraction - misusing metaphors (ie. is green good or bad, is red good or bad) - flawed representations
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