Module 1 - Intro to Nested Model + Data/Task Abstraction

Question 1

Define Visualisation

Answer 1

Technique for data exploration and !making the unseen visible!. Based on
- human visual perception
- exploit pattern recognition capabilities

Question 2

Information Visualisation

Answer 2

Use of computer supported, interactive, visual representations of abstract data to amplify cognition

Question 3

Visualisation Pipeline

Answer 3

Data -> Filter -> Map -> Project -> User
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what data to show, how to show data, what view(s) on data?

Question 4

Visualisation Goals

Answer 4

1. Explore Data
2. Analyse
3. Present Findings

Question 5

Designing Visualisations

Answer 5

• Huge space of design alternatives
• Many possibilities are known to be ineffective, 1. avoid random walk 2. avoid known mistakes 3. extensive experimentation
• Guidelines continue to evolve, iterative refinement is usually wise

Question 6

empt

Answer 6

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Question 7

Nested Model

Answer 7

Domain Situation
Data/Task Abstraction Design
Visual Encoding/Interaction Idiom
Algorithm

• Iterative refinement process
• Mistakes at higher level cannot be fixed at lower levels

Question 8

Domain Situation

Answer 8

understand the data. task and users. use domain specific vocabulary
- users
-> what are their needs/wants/limitations/skills
-> what is their workflow?
-> how to provide actionable knowledge
-> how to make users satisfied?
- data & task
-> produce a set of tasks/questions for target users on data. info obtained through interviews, observations, readings, etc

Question 9

Data/Task Abstraction Design

Answer 9

*what is the user being shown?
Data described in general visualisation terms (table, hierarchy, sets, etc)

*why is the user looking at it?
Tasks described in general visualisation terms (search, compare, see trend, etc)

Question 10

Visual Encoding/Interaction Idiom

Answer 10

*how is it shown?
- Explore design space
- Creative approach (sketching)
- Engineering/Systematic Approach

Question 11

Algorithm

Answer 11

Implementing design, render design, etc

Question 12

Encoding Designs - Data Types

Answer 12

1. Items
2. Attributes
3. Links
4. Positions
5. Grids

Question 13

Encoding Designs (Datasets and Data Types)

Answer 13

Dataset Items Attributes Links Positions Grids
Tables X X
Networks X X X
Geometry/Spatia X X X
Fields X X X
Cluster Lists X

Question 14

Attribute Types

Answer 14

1. Categorical (no order)
2. Ordered (has order, has “meaning” as a number)
   2a. Ordinal 2b. Quantitative
   - not continuous - continuous

Question 15

Ordering directions

Answer 15

1. Sequential
2. Diverging
3. Cyclic

Question 16

empty

Answer 16

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Question 17

Users,Data,Task Triangle

Answer 17

User - Effectiveness - Data
Data - Expressiveness - Task
Task - Appropriateness - User

Question 18

Task Abstraction

Answer 18

• Abstract design, and actions/workflow of users
• Translate domain language -> abstract structures
• (reflect on differences and similarities, reason on encoding)
• tasks provide constraint on design. design depends on goal of visualisation

Question 19

Design

Answer 19

For every visualisation design, ask:
- What information can i extract out of this representation
- What is the problem I’m trying to solve?
- What questions do I want my user to be able to answer looking at this?
- How much effort is needed?
- Can we design in a structured way?

Question 20

Actions

Answer 20

1. Analyse
   a) consume
   - discover
   - present
   - enjoy
   b) produce
   - annotate
   - record
   - derive
2. Search
   - lookup, browse, explore, locate
3. Query
   - identify
   - compare
   - summarise

Question 21

Tasks

Answer 21

1. All Data
   - Trends
   - Outliers
   - Features
2. Attributes
   a) One
   - Distribution
   - Extremes
   b) Many
   - Dependency
   - Correlation
   - Similarity
3. Network Data
   - Topology -> Paths
4. Spatial Data
   - Shape