Design

Question 1

Define data?

Answer 1

Information we want to examine

Question 2

Define tasks?

Answer 2

Hypotheses, interactions etc.

Question 3

Define users?

Answer 3

Perception, spare time etc.

Question 4

Explain the concept of Visualization Literacy?

Answer 4

The concept describes how familiar an individual is at reading and understanding visualizations.

Question 5

What are the four User Considerations?

Answer 5

Visualization Literacy
Colour Blindness
Patience
Training Considerations

Question 6

What is formula for the lie factor?

Answer 6

(size of effect in graphic)/(size of effect in data)

Question 7

What are the key points behind the lie factor?

Answer 7

• if you have 2 elements of your visualization (e.g. 2 lines as in the slide), they should be perceived as similar in scale to the actual numerical difference.
• the formula is looking at the difference in length of the lines vs the difference between the numbers in terms of percentage

Question 8

Define Data Ink?

Answer 8

The ink used to show data

Question 9

What is the data ink ratio?

Answer 9

data-ink/total ink used

Question 10

Do you want maximize or minimize the data ink ratio?

Answer 10

Maximize

Question 11

Why should colour blindness be considered in visualization?

Answer 11

Consider colour blindness as many people cannot see certain colours and many people have sematic meanings for specific colours.

Question 12

How are tasks often described?

Answer 12

Tasks are often described abstractly.

Question 13

Why are tasks described abstractly?

Answer 13

Tasks are described abstractly as they allows us to compare across domains.

Question 14

State the three types of tasks?

Answer 14

High Level
Mid Level
Low Level

Question 15

Why do we prefer mid-level tasks?

Answer 15

High-level has too many steps involved and low-level is too specific and doesn’t consider the big picture.
Mid-level is the middle ground between high-level and low-level tasks.

Question 16

What are Schneiderman’s mantra?

Answer 16

Overview first, zoom and filter, details on demand.

Question 17

What is the purpose of task taxonomies?

Answer 17

the idea is to come up with a small set of common tasks that we can then figure out how to design general visualization or interaction techniques to support.

Question 18

What are the two components of data?

Answer 18

Semantics

Types

Question 19

Define semantics.

Answer 19

real world meaning of the data.

Question 20

Define types.

Answer 20

Storage type in a computer.

Question 21

Provide an example of semantic and type data?

Answer 21

height(is a semantic notion) can be int, double or a tuple{int, int}.

Question 22

Attributes in a dataset are grouped into what types?

Answer 22

Quantitative-continuous numbers(10cm,75kg etc.)
Ordinal :categories with order(small, medium, large, eggs in a box)
Nominal: categories with no order(male, female, apples, oranges, etc)

Question 23

What are the four main dataset types?

Answer 23

Tables
Networks
Fields(continuous)
Geometry(spatial)

Question 24

What does a column and a row represent in a dataset?

Answer 24

Each attribute represents the column in your dataset.

Each items represents the rows in your dataset.

Question 25

How are networks are often represented?

Answer 25

Networks are often represented as 2 tables.

Question 26

What do the nodes and edges of a network consist of ?

Answer 26

The nodes and edges of the networks consist of attributes.

Question 27

Where are fields common in?

Answer 27

Common in volume, flow visualization and 3D model.

Question 28

What is Text?

Answer 28

Text is unstructured data.