Lecture 2

Question 1

What(Data)-Why(task)-How(idiom)

Answer 1

What Data does the user see; (Data)
Why does the user intend to use the visualization tool; (Task)
How are the visual encoding constructed in terms of design choices (Idiom)

Question 2

We have four looped levels of visualization design

Answer 2

The first level is domain
The second level is abstraction
The third level is idiom
The fourth level is algorithm

Question 3

Domain in visualization refers to to a particular field of interest like e-commerce , education,

Answer 3

True

Question 4

Group target people can be scientific research people , public people , specific group of people

Answer 4

True

Question 5

User centered design or human centered design

We are doing four nested levels of design

Answer 5

Working with a specific target audience to iteratively refine a design

Question 6

The outcome of the design process is to ensure that the designer reaches the needs of the user

Answer 6

true

Question 7

Data/ task abstraction

Answer 7

Abstracting tasks and data from the domain
tasks: I want to compare, visualize, summarize
Data: data needed (raw or processed)

Question 8

Many visualization idioms (اساليب) are specific to a particular data type

Answer 8

true

like tables are specific for quantities and number

Question 9

Human abilities such as perception and memory need to be taken into account when we are doing the visual encoding/interaction idiom (2sloob) in the four looped visual design

Answer 9

true

Question 10

Visual encoding/interaction idiom is choosing a specific way to create and manipulate the visual representation of the abstracted data and tasks

Answer 10

True

Question 11

Visual encoding/ interaction idiom has two main concerns

Answer 11

visual encoding (what users see)
interaction (how users change and what they see)

Question 12

Algorithms : The goal at this level is to efficiently handle the visual encoding and interaction idioms

Answer 12

true

Question 13

Features that promote and algorithm over other are :
Computational speed
How much computer memory is required

Answer 13

True

Question 14

Approaches we can have

Answer 14

Problem driven approach (top down):
Start by domain situation then move to data /task abstraction then move to visual encoding /interaction idiom then move to algorithm

Technique driven approach (down top):
We start at algorithm level or idiom level in order to create better idioms or algorithm to better support existing abstraction

Question 15

Slide 25 see them and see how to validate first and after

Answer 15

true

Question 16

There are three major dataset types

Answer 16

1- Tables
2- Networks
3- Spatial

Question 17

In tables, the attributes (properties) are columns, the items are rows, and the cell contains the value

Answer 17

True

Question 18

In networks we have nodes and links

Answer 18

True

Question 19

In spatial we have fields and gematry

Answer 19

True

Question 20

Semantics of data is the underlying meaning of data

Answer 20

True

Question 21

The two main aspects of data are the semantics of the data and the type of data

Answer 21

True

Question 22

metadata

Answer 22

data about data

Question 23

Five main data types

Answer 23

Item
Attribute 
Link
Grid 
Position

Question 24

Item

Answer 24

Discrete individual entity (row in a simple table or a node in a network)

Question 25

Attribute

Answer 25

also called variable or dimension ( specific property that can be measured, observed ,or logged)

Question 26

Link

Answer 26

relationship between two items, typically an edge in a network

Question 27

Grid

Answer 27

strategy for sampling continuous terms of geometric and topological relationships between its cells

Question 28

Position

Answer 28

spatial data (location in 2D or 3D space)

Question 29

Review from 40 to 53

Answer 29

True

Question 30

Dataset Availability

Answer 30

1- Static (The entire dataset is available all at one to visualize)
2- Dynamic (The dataset information change over the course of the visualization process)

Question 31

There are two attributes types

Answer 31

Categorical ( small Box, large box)

Ordered (Ordinal and Quantitative)

Question 32

Key attribute

Answer 32

index that could be use to look up value attributes ( like weight is a key , 28 kg is an attribute, ID is a key )

Question 33

Multidimensional tables have multiple keys

Answer 33

true

Question 34

Unlike tables, fields contain continuous rather than discrete data

Answer 34

true

Question 35

Each cell in a field refer to a unique range of continuous domain

Answer 35

true

Question 36

n contrast with tables, attribute values in

fields are returned for locations throughout the sampled range and not just the exact points where data was recorde

Answer 36

True

Question 37

In context of fields, independent variables refers to key and dependent variable refer to value.

Answer 37

true

Question 38

We have 3 types of fields

Answer 38

Scalar fields
Vector fields
Tensor fields

Question 39

Properties of scalar fields

Answer 39

-Univariate (single value attribute at each point in space.

If no connection between points in space, then we will have multiple separate scalar fields.

Question 40

Properties of vector fields

Answer 40

Multivariate, with multiple attributes at each point.

Each point has a direction and a magnitude.

Question 41

Tensor fields

Answer 41

array of attributes at each point

Question 42

A dataset is said to have time-varying semantics when one of its “key” attributes is time

Answer 42

true

Question 43

Data abstraction operation

Answer 43

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