Lecture 2 Flashcards
What(Data)-Why(task)-How(idiom)
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)
We have four looped levels of visualization design
The first level is domain
The second level is abstraction
The third level is idiom
The fourth level is algorithm
Domain in visualization refers to to a particular field of interest like e-commerce , education,
True
Group target people can be scientific research people , public people , specific group of people
True
User centered design or human centered design
We are doing four nested levels of design
Working with a specific target audience to iteratively refine a design
The outcome of the design process is to ensure that the designer reaches the needs of the user
true
Data/ task abstraction
Abstracting tasks and data from the domain
tasks: I want to compare, visualize, summarize
Data: data needed (raw or processed)
Many visualization idioms (اساليب) are specific to a particular data type
true
like tables are specific for quantities and number
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
true
Visual encoding/interaction idiom is choosing a specific way to create and manipulate the visual representation of the abstracted data and tasks
True
Visual encoding/ interaction idiom has two main concerns
visual encoding (what users see) interaction (how users change and what they see)
Algorithms : The goal at this level is to efficiently handle the visual encoding and interaction idioms
true
Features that promote and algorithm over other are :
Computational speed
How much computer memory is required
True
Approaches we can have
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
Slide 25 see them and see how to validate first and after
true
There are three major dataset types
1- Tables
2- Networks
3- Spatial
In tables, the attributes (properties) are columns, the items are rows, and the cell contains the value
True
In networks we have nodes and links
True
In spatial we have fields and gematry
True
Semantics of data is the underlying meaning of data
True
The two main aspects of data are the semantics of the data and the type of data
True
metadata
data about data
Five main data types
Item Attribute Link Grid Position
Item
Discrete individual entity (row in a simple table or a node in a network)
