- Class Number 7509
- Term Code 3260
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- Prof Mitchell Whitelaw
- Prof Mitchell Whitelaw
- Class Dates
- Class Start Date 25/07/2022
- Class End Date 28/10/2022
- Census Date 31/08/2022
- Last Date to Enrol 01/08/2022
Digital data is ubiquitous in contemporary culture: it documents environment, health, communication, government, arts, professional and private realms. For designers and practitioners data offers a profound opportunity to investigate, reveal and creatively represent this increasingly significant layer of our society.
This practical course grounds students in data as a key element in contemporary design practice, and in the design and production of data visualisations. Through a series of hands-on exercises students will develop static, dynamic and interactive representations of data for screen-based and tangible forms, and come to understand the functional and poetic dimensions of visualisation as a creative practice. The course introduces students to the cultures and contexts of data visualisation and design, and the analysis and interpretation of visualisations. It also introduces critical perspectives on the questions of representation and interpretation that are central to the field. This course will be of interest to students from a wide range of fields including design, fine arts, digital humanities and information technology, where the visual representation of data offers both immediate challenges and creative opportunities.
Upon successful completion, students will have the knowledge and skills to:
- source, handle and manage data for applications in visualisation;
- create static, dynamic and interactive data visualisations using established techniques;
- research and analyse data visualisation artefacts and cultures of practice;
- respond to the cultural and technological contexts of data and visualisation design; and
- critically reflect on practice and substantiate design outcomes with research and rationale.
Additional Course Costs
Student may incur costs in the course of producing creative work assessed for this class. Students will always be provided with low- or no-cost options for production.
Staff FeedbackStudents will be given feedback in the following forms in this course:
- Written comments
- Verbal comments
- Feedback to the whole class, to groups, to individuals, focus groups
Student FeedbackANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.
|Week/Session||Summary of Activities||Assessment|
|1||Data Visualisation: key concepts and foundations|
|2||Graphs and Charts|
|3||Data Wrangling & Visualisation Case Studies presentations||Visualisation Case Studies due Friday|
|5||Visualisation on the Street - production and review|
|6||Visualisation on the Street - presentations, feedback and review||Visualisation on the Street due Friday|
|7||Creative Data Vis - Introduction and Context||CDV Project proposals (non-assessable)|
|8||CDV Concept Development - data, form, audience and engagement|
|9||CDV Project Development||CDV Project Plans (non-assessable)|
|10||CDV Project Development - techniques, workflows, toolsets|
|11||CDV Project Production||CDV work in progress presentations (non-assessable)|
|12||CDV Project Production||CDV final presentations (non-assessable)|
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Visualisation Case Studies||20 %||12/08/2022||25/08/2020||3,4,5|
|Visualisation On The Street||30 %||02/09/2022||16/09/2022||1,2,4|
|Creative Data Visualisation||50 %||28/10/2022||11/11/2020||1,2,3,4,5|
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
PoliciesANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:
Assessment RequirementsThe ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.
Moderation of AssessmentMarks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.
Assessment Task 1
Learning Outcomes: 3,4,5
Visualisation Case Studies
Select and analyse three examples of data visualisation. Examples may be interactive or static must be readily accessible online. Each analysis should be 300-350 words in length. Ensure you include a link to each case study. Your analysis of these examples should demonstrate your understanding of key concepts in data visualisation, as covered in class.
For each example, analyse and discuss:
- Data: what are the types of data involved; what is the granularity of the data; what is the source of the data, is the data accessible? Can you see how the data has been manipulated?
- How are the data represented visually? What visualisation conventions are used (eg scatter plot, bar chart, pie graph)?
- Visual mapping: are the chosen representations appropriate for the data? Why or why not?
- What information or insight can you gain from the visualisation? What role does the design of the visualisation play in this?
- Interaction: if the visualisation uses interaction, what role does it play?
Present draft case studies to the class in Week 3. This presentation is an opportunity to improve your work through formative feedback from staff and peers
Your submission will be assessed on its demonstration of your ability to
- Demonstrate an understanding of key concepts in data visualisation
- Critically analyse data visualisations according to key principles
- Structure and present written communication
Assessment Task 2
Learning Outcomes: 1,2,4
Visualisation On The Street
A modern city is made of data, as well as people, buildings, roads and parks. In this project you will produce an animated visualisation of data related to the city of Canberra. Select and acquire data about any aspect of the city - population, transport, economics, culture, tourism, environment, energy, and so on. You may either look at data that is specific to Canberra, or create a visualisation that compares some aspect of Canberra with other cities within Australia or the world. Learn about what your data represents, and use this to inform your visualisation.
Design your visualisations for public display on the STORYBOX plinth screens, which will be installed around City West between July and September. These screens are portrait format (1080x1920px). Create your animated visualisation as a web page using SVG.js. Selected visualisations from this project will be shown on the STORYBOX plinths during September 2022
Create visualisations that are legible, informative and aesthetically engaging for a public audience, and that respond to the urban context of Canberra and City West. Include titles, introductory text, labels, keys and other information necessary for the audience to interpret the data in full. Provide attribution for your source data.
The three visualisations should demonstrate your ability to source, manage and combine appropriate data, your understanding of visualisation techniques and approaches, and your ability to creatively apply and adapt appropriate techniques for your chosen datasets.
As well as your final animated visualisation, submit a pdf with two formative sketches that show the development of the design, along with brief comments rationalising your design decisions and analysing your sketches.
Your visualisations will be assessed on their demonstration of your ability to:
- Source, manage and effectively present data in visual form
- Design engaging data visualisations using established techniques
- Effectively apply and adapt modern visualisation technologies
Assessment Task 3
Learning Outcomes: 1,2,3,4,5
Creative Data Visualisation
In this project you will work in groups of 2-3 to develop a creative visualisation of a selected dataset. The form of your visualisation is open; it may be a web-based visualisation, an animation or video; a tangible visualisation or 'physicalisation'. You may create a participatory craft project, an audiovisual performance, or a cocktail recipe. Depending on the scope and complexity of your proposal, your project may involve multiple visualisations or datasets. Select a form that draws on your existing creative expertise and technical knowledge, and that can be realised using resources available under current restrictions.
Before you commence work in groups, prepare individually for the project by developing a project proposal. Present your proposal to the class in Week 7. Teams and final project concepts will be formed by negotiation based on these proposals. Proposals should include a data source and a concept for realisation in a creative form.
Source and investigate data that interests you. There are no restrictions on the choice of data, but consider factors including:
- Data source and significance - where is the data from? What does it show? Is it important and if so, to who? What can we learn from it?
- Data granularity and volume - how much data is there? How detailed or fine-grained is the data? Has the data been averaged or aggregated?
- Data format and accessibility - what format is the data in? Can you access and work with it effectively?
You may combine data from multiple sources, but be careful to ensure your data is consistent and comparable.
Pay special attention to the relationship between the data, the chosen form, and the intended audience. Why is your chosen form appropriate, interesting or innovative?
Consider the balance between functional utility, aesthetics and cultural engagement.
Research and Rationale
Length: 1000 words
Document your Creative Data Visualisation work with a Research and Rationale document that includes:
- Visual and technical documentation - include image or video documentation of your work, and links to any code and data sources used.
- Research: Document 2-3 examples of visualisations relevant to your project. Choose examples that use similar visualisation techniques, tackle similar datasets, work in a similar context or application, or use similar approaches to form and medium. Include an image and citation of each example, and explain its relevance to your own work.
- Rationale: explain how your visualisation design relates to its chosen data and context - why represent this data, in this way? Document your understanding and interpretation of the source and significance of your chosen data. Explain your design choices, and show how they balance effective data representation with poetic, aesthetic, cultural and contextual factors. Reflect on and evaluate your design and production process. What were its strengths and weaknesses; what did you learn from this process?
Presentation and Formative Feedback
Present your project to the class in Week 12. This informal ten-minute presentation should include your final object/s, discussion of process and design rationale. You will receive formative feedback based on this presentation from staff and peers.
Submission and Documentation
Submit your completed visualisation, as well as documentation including:
- All code and data used to generate the outcome.
- Documentation of any data processing and manipulation (including code if necessary).
- Document any other processes involved in realising the form (eg hand making or manipulation).
- Documentation of group roles and contributions to the project
Submit documentation as a digital document (pdf).
Your submission will be assessed on its demonstration of your ability to:
- Source, manage and effectively present data in a creative form
- Create aesthetically engaging data representations that engage with a specific cultural context
- Successfully apply and adapt technologies for creative visualisation
- Effectively research and analyse data visualisation artefacts
- Critically reflect on practice and substantiate design outcomes
Academic IntegrityAcademic integrity is a core part of our culture as a community of scholars. At its heart, academic integrity is about behaving ethically. This means that all members of the community commit to honest and responsible scholarly practice and to upholding these values with respect and fairness. The Australian National University commits to embedding the values of academic integrity in our teaching and learning. We ensure that all members of our community understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with. The University has policies and procedures in place to promote academic integrity and manage academic misconduct. Visit the following Academic honesty & plagiarism website for more information about academic integrity and what the ANU considers academic misconduct. The ANU offers a number of services to assist students with their assignments, examinations, and other learning activities. The Academic Skills and Learning Centre offers a number of workshops and seminars that you may find useful for your studies.
Online SubmissionThe ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Hardcopy SubmissionFor some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.
Late SubmissionNo submission of assessment tasks without an extension after the due date will be permitted. If an assessment task is not submitted by the due date, a mark of 0 will be awarded. OR Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.
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