INFORMATION VISUALIZATION
CSE5INV
2021
Credit points: 15
Subject outline
Information Visualization is the study of presenting information in a graphical format to facilitate effective decision making. In this subject, you will learn the theories and methodologies to visualize abstract data (numerical or non-numerical) for human cognition. Topics covered include histograms, scatter plots, hierarchical data visualization, surface plots, tree maps and parallel coordinate plots etc. In particular, you will learn the representation of temporal and spatial data, networks and trees, and textual data. You will also learn the principles and techniques on visualization design and evaluation.
SchoolEngineering and Mathematical Sciences
Credit points15
Subject Co-ordinatorFei Liu
Available to Study Abroad/Exchange StudentsYes
Subject year levelYear Level 5 - Masters
Available as ElectiveNo
Learning ActivitiesN/A
Capstone subjectNo
Subject particulars
Subject rules
PrerequisitesN/A
Co-requisitesN/A
Incompatible subjectsN/A
Equivalent subjectsN/A
Quota Management StrategyN/A
Quota-conditions or rulesN/A
Special conditionsN/A
Minimum credit point requirementN/A
Assumed knowledgeN/A
Readings
Information Visualization
Resource TypeRecommended
Resource RequirementN/A
AuthorSpence, R.
Year2014
Edition/Volume3rd ed
PublisherSpringer
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Introduction to Information Visualization
Resource TypeRecommended
Resource RequirementN/A
AuthorBenoit, G.
Year2019
Edition/VolumeN/A
PublisherRowman & Littlefield Publishers
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Career Ready
Career-focusedNo
Work-based learningNo
Self sourced or Uni sourcedN/A
Entire subject or partial subjectN/A
Total hours/days requiredN/A
Location of WBL activity (region)N/A
WBL addtional requirementsN/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Subject options
Select to view your study options…
Melbourne (Bundoora), 2021, Semester 2, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorFei Liu
Class requirements
Computer LaboratoryWeek: 32 - 43
One 2.00 h computer laboratory per week on weekdays during the day from week 32 to week 43 and delivered via face-to-face.
LectureWeek: 30 - 42
One 2.00 h lecture per week on weekdays during the day from week 30 to week 42 and delivered via face-to-face.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | ILO* |
|---|---|---|---|---|---|
Assignment 1 Visualization project for numerical data sets (1500-word equivalent) | N/A | N/A | No | 25 | SILO1, SILO3, SILO4 |
Assignment 2 Visualization project for textual data sets (1500-word equivalent) | N/A | N/A | No | 25 | SILO2, SILO3, SILO4 |
One 2-hour Examination (2000 words equivalent) | N/A | N/A | No | 50 | SILO1, SILO2, SILO3, SILO4 |