代写FIT3179 Data Visualisation 1 Semester 2, 2024调试Haskell程序

FIT3179 Data Visualisation

DATA VISUALISATION 1

Semester 2, 2024. Version 2.0.2 Version history

●   1.0 (22 July 2024): Initial release

●   2.0 (29 July 2024): Corrected proposal due date. Added separate submission of  Five Design Sheets (5DS) at the end of week 4. Improved marking rubric for Five Design Sheets.

●   2.0.1 (30 July 2024): Removed duplicate text in introduction.

●   2.0.2 (31 July 2024): Fixed the due date for the proposal in “Task Description”.

Submission

Three submissions are required for this assignment:

1. Proposal: Brainstorm your project topic and find a suitable dataset. Then, submit a proposal by Sunday 4 August 11:55 PM. Discuss your visualisation project proposal with your tutor in the week 3 studio. The proposal is not marked, but is a hurdle requirement for this assignment.

2. Five Design Sheets: Submit your Five Design Sheets by the end of week 4. Show your Five Design Sheets to your tutor in the week 5 studio. In the studio, your tutor will provide feedback.

3. Visualisation due 30 August (Friday of week 6), at 11:55 pm. Publish your visualisation with Tableau Public and submit your work on Moodle.

Introduction

In this assignment, you will design and build an effective data visualization for a specific domain. This will require you to critically evaluate information in a domain of your choice, develop your own visualization, and tell a story. The domain can be broad or specific, depending on the availability of datasets and your interests.

The aim of the assignment is to apply the data visualization methods and techniques discussed during the first six weeks of the semester and demonstrate their use in an  innovative context. As such, the visualization should satisfy the following criteria:

●   Why? The visualization addresses a particular need within a specific domain of

your choosing. It must be targeted to users with specific information needs in this domain or be useful and relevant to individuals interested in the chosen domain.

●   What? It visualises data relevant to the domain. Data can be of any kind.

●   Who? Design your visualisation for the average Australian or Malaysian,

depending on whether you are a student at the Clayton or Malaysia campus.

●   The visualisation must transform. data into meaningful information and provide insight that would otherwise be difficult or impossible to obtain without it.

●   It must provide an appropriate level of interactive exploration.

●   It needs to show some innovation. While it does not have to be wholly original, it cannot be a replica of an existing visualisation. It could include an innovative visualisation idiom, or an innovative exploration of an interesting dataset.

●   Your submission must demonstrate the use of the Five Design Sheet methodology for sketching and planning the design of your visualisation.

●   Your submission must demonstrate the use of Munzer’s What/Why/How framework discussed in lectures.

●   It must apply design principles discussed throughout the unit, such as data-ink  ratio, storytelling, layout, typography and visualisation idioms with appropriate use of marks and channels.

Task Description

1.   Choose a domain that you would like to explore.

2.   Find relevant data that is publicly available.

3.   Prepare a proposal with a summary of your domain, dataset, and possible design ideas and submit it to Moodle by the end of Week 2. Present your proposal to your tutor in the Week 3 studio to obtain approval. You may amend your proposal after discussion with your tutor, and the proposal will serve as a record of what has been agreed upon. The approval and proposal are not graded but are a hurdle requirement for this assignment: you must obtain formal approval from  your tutor before submitting the report.

4.   Design a narrative visualisation using the Five Design Sheet Methodology using analogue pen and paper. Sketches designed with tablet apps or other digital tools are not accepted. By the end of week 4, submit your Five Design Sheets, and discuss them with your tutor in the week 5 studio. Failure to do so will result in 0 marks for the five design sheets.

5.   Implement your design with Tableau and publish the visualisation on the Tableau Public server.

6.   Submit the following on Moodle:

a.   The public URL to your visualisation

b.   Information about your visualisation via a form on Moodle:

i.   The domain,the why and the who of the visualisation.

ii.   What: The data (sources, authors, relevance, creation process, etc.).

iii.   How: Give a rationale for choosing the specific idioms and explain how they help users to achieve their tasks. Describe any special features of your visualisation, such as custom-built elements.

Expectations

Data: The visualization must use accurate and reliable real-world data; it must not use

fabricated or tampered data. The most recent available dataset should be used. Kaggle datasets must be combined with an additional source. Use existing and reasonably clean data; creating datasets or performing data wrangling are not topics covered in this unit and are not included in the marking rubric.

Topic: The following visualization topics are not allowed: World happiness, COVID-19, Airbnb, crime in Victoria, road accidents in Victoria, data science salaries, house prices in Melbourne, university rankings, car sales, and electric vehicle sales. In general, the topic must be related to Australia (for students in Australia) or Malaysia (for students in Malaysia). For example, tobacco consumption in the US is not an acceptable topic, but tobacco consumption in Australia or Malaysia is acceptable. Exceptions are possible, particularly if you have a specific area of interest. If in doubt, discuss your topic with your tutor.

Format: The entire visualization must be accessible from a single URL on the Tableau Public server. It must be viewable on a single web page that can be scrolled, and the full width of the visualization must be visible on a small laptop screen without horizontal scrolling. There should be no buttons (or other weblinks) that swap major sections of the web page, though you may use buttons to show and hide visualization elements.

Presentation not exploration: The goal of this assignment is to create a visualisation that communicates interesting information in an easily accessible and graphically engaging way using storytelling elements, layout principles, typography, and graphical design. The goal is not to create an expert tool for exploring and analysing a dataset.

Audience: The topic must be relevant to and easily understandable by an audience in Malaysia (for students in Malaysia) or Australia (for students in Australia). Avoid jargon and technical terms when possible. If specialized terminology is necessary, introduce and explain these terms. Avoid visualizations that require knowledge of statistics (e.g., understanding standard deviation or confidence intervals), as the general audience is not expected to have such expertise. If statistical concepts are necessary, introduce and explain them.

Quality, not quantity: Your visualization will likely contain between three and ten charts or diagrams. There is no set minimum or maximum number of charts. Instead, we are looking for carefully designed and annotated charts that, in combination with text, icons, and pictures, guide the user through an interesting story using layout principles, typography, and graphic design principles. Avoid pixelated images, non-informative graphical elements, or trivial text. Complement your visualization with concise, informative, and grammatically correct narrative text that tells a story.

Interactivity: Interactive features are easy to add in Tableau. Integrate interactivity where it makes sense, but avoid adding interactive elements merely for their own sake.