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-ordinatorZhen He

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 5 - Masters

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules



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

Learning resources

Introduction to Information Visualization

Resource TypeBook

Resource RequirementRecommended

AuthorBenoit, G.



PublisherRowman & Littlefield Publishers


Chapter/article titleN/A



Other descriptionN/A

Source locationN/A

Information Visualization

Resource TypeBook

Resource RequirementRecommended

AuthorSpence, R.


Edition/Volume3rd ed



Chapter/article titleN/A



Other descriptionN/A

Source locationN/A

Career Ready


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

01. Design and create the visual representation for numerical data sets using various visualization tools and techniques.
02. Identify and critique techniques and practices in non-numerical data representation.
03. Critique and evaluate the suitability of a specific technique for specific types of data sets.
04. Critically assess a visualization representation and make justified recommendations

Subject options

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Start date between: and    Key dates

Melbourne (Bundoora), 2021, Semester 2, Day


Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorZhen He

Class requirements

Computer LaboratoryWeek: 32 - 43
One 2.00 hours 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 hours lecture per week on weekdays during the day from week 30 to week 42 and delivered via face-to-face.


Assessment elementCommentsCategoryContributionHurdle% ILO*

Assignment 1 Visualization project for numerical data sets (1500-word equivalent)

N/AAssignmentIndividualNo25 SILO1, SILO3, SILO4

Assignment 2 Visualization project for textual data sets (1500-word equivalent)

N/AAssignmentIndividualNo25 SILO2, SILO3, SILO4

One 2-hour Examination (2000 words equivalent)

N/ACentral examIndividualNo50 SILO1, SILO2, SILO3, SILO4