Skip to main content

During 2021 we will continue to support students who need to study remotely due to the ongoing impacts of COVID-19 and travel restrictions. Make sure you check the location code when selecting a unit outline or choosing your units of study in Sydney Student. Find out more about what these codes mean. Both remote and on-campus locations have the same learning activities and assessments, however teaching staff may vary. More information about face-to-face teaching and assessment arrangements for each unit will be provided on Canvas.

Unit of study_

DECO3100: Information Visualisation Design Studio

The field of information visualisation focuses on how data can be effectively represented and meaningfully communicated to people, in interactive and automated ways. The unit of study introduces the principles of information visualisation design, with special attention to aesthetic communication of data, data analytics, and user engagement. Key concepts covered in this unit include: abstract data visualisation; data acquisition; and parsing and processing of data. Using a combination of vector graphics software tools and programming languages for processing data, students will develop information visualisations of real-world datasets that are both communicative and engaging. The unit will equip students with the skills to produce static as well as web-ready interactive data visualisations.


Academic unit Design Lab
Unit code DECO3100
Unit name Information Visualisation Design Studio
Session, year
Semester 1, 2021
Attendance mode Normal day
Location Camperdown/Darlington, Sydney
Credit points 12

Enrolment rules

DECO1016 and DECO2014
Available to study abroad and exchange students


Teaching staff and contact details

Coordinator Kazjon Simes Grace,
Type Description Weight Due Length
Assignment A3: Intelligent Interactive Twitter Visualisation
Design and develop an interactive visualisation that tells a story.
40% STUVAC 56 hours
Outcomes assessed: LO1 LO2 LO3 LO4
Assignment A1: Infographic Design
Design a compelling and effective infographic from the provided dataset.
30% Week 05 42 hours
Outcomes assessed: LO1 LO2 LO4
Assignment A2: Predictive Visualisation Design
Design a predictive visualisation from data you prepare yourself.
30% Week 10 42 hours
Outcomes assessed: LO1 LO2 LO3

See Canvas for an in-depth description of all assessible tasks. All assessments for this subject will be due at midnight the day before class. 

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a High distinction indicates work of an exceptional standard, a Distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range


High distinction

85 - 100

Work of outstanding quality, demonstrating mastery of the learning outcomes
assessed. The work shows significant innovation, experimentation, critical
analysis, synthesis, insight, creativity, and/or exceptional skill.


75 - 84

Work of excellent quality, demonstrating a sound grasp of the learning outcomes
assessed. The work shows innovation, experimentation, critical analysis,
synthesis, insight, creativity, and/or superior skill.


65 - 74

Work of good quality, demonstrating more than satisfactory achievement of the
learning outcomes assessed, or work of excellent quality for a majority of the
learning outcomes assessed.


50 - 64

Work demonstrating satisfactory achievement of the learning outcomes


0 - 49

Work that does not demonstrate satisfactory achievement of one or more of the
learning outcomes assessed.

For more information see

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Special consideration

If you experience short-term circumstances beyond your control, such as illness, injury or misadventure or if you have essential commitments which impact your preparation or performance in an assessment, you may be eligible for special consideration or special arrangements.

Academic integrity

The Current Student website provides information on academic honesty, academic dishonesty, and the resources available to all students.

The University expects students and staff to act ethically and honestly and will treat all allegations of academic dishonesty or plagiarism seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic dishonesty. If such matches indicate evidence of plagiarism or other forms of dishonesty, your teacher is required to report your work for further investigation.

WK Topic Learning activity Learning outcomes
Week 01 Designing with Data (3 hr)  
Design Studio (2 hr)  
Week 02 Storytelling with Data (3 hr)  
Design Studio (2 hr)  
Week 03 Data-driven Experiences (3 hr)  
Design Studio (2 hr)  
Week 04 Time & Relative Dimensions in Space (3 hr)  
Design Studio (2 hr)  
Week 05 Data Science for Designers (3 hr)  
Design Studio (2 hr)  
Week 06 Correlation, Causality & Data Science Casualties (3 hr)  
Design Studio (2 hr)  
Week 07 Artificial Intelligence for Designers (3 hr)  
Design Studio (2 hr)  
Week 08 Neural Networks & Deep Learning (3 hr)  
Design Studio (2 hr)  
Week 09 Data for Good: Education, Journalism & Accountability (3 hr)  
Design Studio (2 hr)  
Week 10 Designing Visual Analytics (3 hr)  
Design Studio (2 hr)  
Week 11 Visualising Connections (3 hr)  
Design Studio (2 hr)  
Week 12 From Tool to Team-member: Human–AI Collaboration (3 hr)  
Design Studio (2 hr)  
Week 13 Entirely Inaccurate Predictions about the Future of AI (3 hr)  
Design Studio (2 hr)  

Attendance and class requirements

Please refer to the Resolutions of the University School:

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 12 credit point unit, this equates to roughly 240-300 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University’s graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. To design compelling visual narratives using data, including the ability to develop and justify data mappings appropriate for the context.
  • LO2. To recognise, demonstrate and implement aesthetic and human-centred design qualities, including the ability to devise and justify an appropriate design solutions based on a brief.
  • LO3. To manipulate, transform and synthesise data into representations that can be used for visualisation, including the ability to recognise and incorporate artificial intelligence principles.
  • LO4. To hypothesise, evaluate and revise data visualisations based on rigorous qualitative and quantitative user-centred evaluation.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
The technical parts of the unit that the students found challenging have been made more detailed and development occurs at a pace suitable to the learning rate of design students.


The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.