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Unit of study_

DECO3100: Information Visualisation Design Studio

Semester 1, 2024 [Normal day] - Camperdown/Darlington, Sydney

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.

Unit details and rules

Unit code DECO3100
Academic unit Design Lab
Credit points 12
Prohibitions
? 
None
Prerequisites
? 
DECO1016 and DECO2014
Corequisites
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Brittany Klaassens, brittany.klaassens@sydney.edu.au
Lecturer(s) Brittany Klaassens, brittany.klaassens@sydney.edu.au
Type Description Weight Due Length
Assignment A2: Interactive Visualisation Project
Design and develop an interactive visualisation that tells a story.
50% Formal exam period
Due date: 26 May 2024 at 23:59
70hrs (approximate expected work)
Outcomes assessed: LO1 LO2 LO3 LO4
Small continuous assessment Marked Tutorial Task 1
Expanded tutorial exercise designed to be completed in studio time.
4% Week 02
Due date: 26 Feb 2024 at 23:59
~3hrs.
Outcomes assessed: LO1 LO4 LO3 LO2
Small continuous assessment Marked Tutorial Task 2
Expanded tutorial exercise designed to be completed in studio time.
4% Week 03
Due date: 04 Mar 2024 at 23:59
~3hrs.
Outcomes assessed: LO1 LO4 LO3 LO2
Small continuous assessment Marked Tutorial Task 3
Expanded tutorial exercise designed to be completed in studio time.
4% Week 04
Due date: 11 Mar 2024 at 23:59
~3hrs.
Outcomes assessed: LO1 LO4 LO3 LO2
Small continuous assessment Marked Tutorial Task 4
Expanded tutorial exercise designed to be completed in studio time.
4% Week 05
Due date: 18 Mar 2024 at 23:59
~3hrs.
Outcomes assessed: LO1 LO4 LO3 LO2
Small continuous assessment Marked Tutorial Task 5
Expanded tutorial exercise designed to be completed in studio time.
4% Week 06
Due date: 25 Mar 2024 at 23:59
~3hrs.
Outcomes assessed: LO1 LO4 LO3 LO2
Presentation A1: Visualisation Concept Presentation
Presenting progress on the major project, concept + feasibility.
30% Week 10
Due date: 29 Apr 2024 at 23:59
42hrs (approximate expected work)
Outcomes assessed: LO1 LO3 LO2

Assessment summary

See Canvas for an in-depth description of all assessible tasks. 

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

Description

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.

Distinction

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.

Credit

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.

Pass

50 - 64

Work demonstrating satisfactory achievement of the learning outcomes
assessed.

Fail

0 - 49

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

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

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.

Academic integrity

The Current Student website  provides information on academic integrity 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 integrity breaches seriously.  

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

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy 2023 reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy 2023. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

WK Topic Learning activity Learning outcomes
Week 01 Designing with Data Lecture (1 hr) LO2
Charts Introduction Tutorial (2 hr) LO1
Chart Critique Studio (3 hr) LO1 LO2
Week 02 Storytelling with Data Lecture (1 hr) LO1
Intro to Excel Tutorial (2 hr) LO3
Tutorial Task 1 Studio (3 hr) LO1 LO2 LO3
Week 03 Data Science for Designers Lecture (1 hr) LO3
Manipulating and Charting Data Tutorial (2 hr) LO2 LO3
Tutorial Task 2 Studio (3 hr) LO1 LO3
Week 04 Evaluating Visualisations Lecture (1 hr) LO2 LO4
Refresher Course in HTML, CSS and Javascript (Plotly Prep) Tutorial (2 hr) LO1 LO3
Tutorial Task 3 Studio (3 hr) LO1 LO4
Week 05 Time & Relative Dimensions in Space Lecture (1 hr) LO2
Plotly: Going from raw data to a well-designed custom chart Tutorial (2 hr) LO1 LO3 LO4
Tutorial Task 4 Studio (3 hr) LO3 LO4
Week 06 Guest Lecture Lecture (1 hr) LO1 LO2 LO3 LO4
Advanced Plotly: Maps and Hot Tips Tutorial (2 hr) LO3 LO4
Tutorial Task 5 Studio (3 hr) LO2 LO3
Week 07 Designing Analytics: Interacting with Visualisations Lecture (1 hr) LO1 LO2 LO3 LO4
Advanced Plotly: Interactivity Tutorial (2 hr) LO1 LO2 LO3
Studio Work Studio (3 hr) LO1 LO2 LO3 LO4
Week 08 Data for Good Lecture (1 hr) LO2
Advanced Plotly: Animations Tutorial (2 hr) LO3
Studio Work Studio (3 hr) LO1 LO2 LO3 LO4
Week 09 Guest Lecture Lecture (1 hr) LO1 LO2 LO3 LO4
Advanced Plotly: Putting it all Together Tutorial (2 hr) LO3 LO4
Studio Work Studio (3 hr) LO1 LO2 LO3 LO4
Week 10 PRESENTATIONS Tutorial (2 hr) LO1 LO2 LO3 LO4
PRESENTATIONS Studio (3 hr) LO1 LO2 LO3 LO4
Week 11 Visualising Connections Lecture (1 hr) LO1 LO3
Networks Tutorial (2 hr) LO1 LO3
Studio Work Studio (3 hr) LO1 LO2 LO3 LO4
Week 12 Artificial Intelligence for Designers a + From tool to team-member: Human-machine collaboration Lecture (1 hr) LO2 LO3
Introduction to AI: The Teachable Machine Tutorial (2 hr) LO2 LO3
Studio Work Studio (3 hr) LO1 LO2 LO3 LO4
Week 13 Entirely Inaccurate Predictions About The Future of AI Lecture (1 hr) LO4
Assignment prep Tutorial (2 hr) LO1 LO2 LO3 LO4
Studio Work Studio (3 hr) LO1 LO2 LO3 LO4

Attendance and class requirements

Please refer to the Resolutions of the University School: http://sydney.edu.au/handbooks/architecture/rules/faculty_resolutions.shtml

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. design compelling visual narratives using data, including the ability to develop and justify data mappings appropriate for the context.
  • LO2. 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. manipulate, transform and synthesise data into representations that can be used for visualisation, including the ability to recognise and incorporate artificial intelligence principles.
  • LO4. 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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

The first assessment has been removed and replaced with five smaller marked tutorial exercises, each worth 5%. This is designed to increase student engagement with these critical skills exercises. They are designed to be completed in-class, although technically students can submit them up until midnight. The order of several tutorials has also changed as some students felt it would have been more helpful to have material introduced in that order.

Disclaimer

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.