Course Title: Data Visualisation

Part A: Course Overview

Course Title: Data Visualisation

Credit Points: 12

Course Code




Learning Mode

Teaching Period(s)


City Campus


620H Business Info Technology


Sem 2 2006,
Sem 1 2007,
Sem 2 2007


City Campus


620H Business Info Technology


Sem 2 2007

Course Coordinator: Barry McIntyre

Course Coordinator Phone: +61 3 9925 5819

Course Coordinator

Course Coordinator Location: Level 17 Building 108

Course Coordinator Availability: Send queries by email or voice mail

Pre-requisite Courses and Assumed Knowledge and Capabilities


Course Description

In the age of information overload it is important to get back to first principles. Whether information is used to convince an audience of a point of view, or whether you wish to support your own need to make a decision, Data Visualisation is a tool that fulfils both these roles.

It is a course designed to debunk the myth that in business reports there are only “ lies, damned lies and statistics” and it certainly not a course about statistics.

The course aims to prove that it is possible to convince a sceptical audience of your point of view using truthful, selective and simplified data visualisations. The theoretical material covered includes interpretation of graphics, relationships between statistics and knowledge, and successful summarisation of data through visualisation.

The course uses a hands-on approach and contains illustrative practical workshops. New-found understanding will be immediately applicable to problems in the workplace.

Students in the past have commented that they expect that the skills learnt in Data Visualisation will be able to be applied for the rest of their lives.

Objectives/Learning Outcomes/Capability Development

This course aims to provide you with an opportunity to develop enhanced visualisation of data. In so doing, your visualisations should strive towards the following goals:
• Appropriate Content focus
• Comparison rather than mere description
• Ethical/honest visualisation
• High data resolution
• Emphasis on the persuasive value of visualisation
• Utilisation of classic designs and concepts proven by time that persuasively demonstrate relationships.

At the conclusion of this course, you should be able to demonstrate an understanding and/or skills in the following areas.
• The history of Data Visualisation, its triumphs and failures.
• How to utilise classic designs including: small multiples, time series, and micro macro composition
• An understanding of design and usability guidelines including data-ink ratio, clutter, layering, separation, and colour.
• Identification of the key elements for creating effective visual explanations.
• An ability to critically evaluate data visualisations employed in business.
• Ability to enhance existing data visualisations
• Design of new visualisations that can be applied in business.

Overview of Learning Activities

The course will be taught in a series of laboratories that concentrate on topical issues surrounding data visualisation. These sessions will consist of a mix of lectures, class exercises and case studies.

These studies are both powerful and emotionally challenging as they discuss life and death issues. Laboratories will harness common graphics software available in business to manipulate data sets.

The course will culminate in a design studio where students exhibit their ’works’ and present an interesting and topical business theme. These activities will be supported by related readings. At the conclusion of the course, you will not be an expert in Data Visualisation, but you will be an authority and, most importantly, you will be equipped with another skill from which to draw upon for effective performance in business.

Overview of Learning Resources

Tufte, Edward. (1983) The Visual Display of Quantitative Information. Cheshire, CT, Graphics Press.

Online Resources: The course is supported by a collection of online examples and exercises. These are supplied through RMIT’s Online Learning Hub. Students can access to this resource once they enrol in Data Visualisation.

The following sources have relevance to various aspects of the courses’s content.

Cleveland, William S. (1994) The Elements of Graphing Data. Van Nostrand Reinhold.

MacEachren, Alan M. (1995) How Maps Work : Representation, Visualization, and Design.Guildford Press.

Mullet, Kevin. and Sano, Darrell. (1995) Designing Visual Interfaces : Communication Oriented Techniques. Englewood Cliffs, NJ, Prentice-Hall.

Tufte, Edward. (1990) Envisioning Information. Cheshire, CT, Graphics Press.

Tufte, Edward. (1997) Visual Explanations. Cheshire, CT, Graphics Press.

Tukey, John (1977) Exploratory Data Analysis. Addison-Wesley.

Wurman, Saul. & Bradford, Peter (Eds.) Information Architects. Watson-Guptil Press, 1997.

These items represent only a starting point. Students should also be ready to search the RMIT Library Collections and the Internet for relevant sources. Such searching will be vital when students come to tackle each of the assignments. In particular, careful searching will be needed to locate sample visualisations as well relevant data sets.

Style Manual
On matters of style and presentation you should use Turabian, Kate L. 1996. A manual for writers of term papers, theses, and dissertations. 6th ed. Chicago: University of Chicago Press. Please employ the parenthetical style of footnoting and the matching format for reference lists. Follow the same style format for materials cited from the WWW.

Overview of Assessment

To pass a student must successfully:
• Submit a portfolio consisting of the best two examples culled from a review of at least 10 business reports. These selections will serve as examples both good and bad (one of each) which emphasise effective explanation. These reports will serve to demonstrate your understanding of what Edward Tufte espouses are the tenets of good data visualisation. These can be chosen from any field of business. (30% of assessment)

• Produce a report on the exploration of a topic of relevance to business and the student’ s interests. The area of interest must be confirmed by the lecturer prior to commencement of the assignment. (50% of assessment). Concisely (< 10 min) present a series of Powerpoint slides to the class that clearly summarises the chosen topic (20% of assessment) (Total- 70% of assessment).

Due dates
Assignment 1 will be nominated during class time.

Assignment 2 is due by 5:00pm on the Friday following the final class for the semester.

This is the Friday following the final class at which visual presentation of the assignment material will be made to the class.

Resubmission of Unsatisfactory Work
Students who fail a piece of assessment will be given the opportunity to resubmit one of the above assessment elements.
Assessment Review
In the first instance, discuss any concerns over assessment with the course leader of Data Visualisation. If the outcome is not satisfactory to you, discuss the matter with with the appropriate program coordinator.

If you require a formal assessment review of the final result in the course, you should apply in writing to the Head of School. Do this within a month of the official notification of the result. The form of the report for this course will be a written account of your performance on each segment of the assessment schedule.