代写FIT3179、代写Java编程设计

日期：2022-10-23 02:55

FIT3179 Data Visualisation

DATA VISUALISATION 2

Semester 2, 2022, version 1.1

Version history:

● 1.0 (5 September 2022): Initial release

● 1.1 (12 September 2022): Added requirement regarding download size

Submission

Due date: Monday of week 12, 17 October, 23:55. Submit a report in PDF format through a

Turnitin link on Moodle. The cover page of the report must contain a URL to a public GitHub

repository with a web page containing the visualisation.

Marking and Interview Hurdle

This assignment is worth 25% of the final unit mark. A detailed marking rubric is included at the

end of this document. A late penalty of 10% per day and a one-week cut off apply. Students are

required to pass an interview hurdle during the studio in week 12. Students who fail the interview

hurdle will get 0 marks for the Data Visualisation 2 assignment.

Introduction

Very similar to the Data Visualisation 1 assignment, you design and build an effective data

visualisation for a specific domain. The major difference is that you will use the Vega-Lite

visualisation library to create maps and diagrams.

The aim of the assignment is to apply the data visualisation techniques examined during the

entire semester and demonstrate their use in an innovative context.

Requirements

The following requirements apply specifically for this Data Visualisation 2 assignment:

● The selected domain is clearly different from the domain of your Data Visualisation 1

visualisation.

● You use the Vega-Lite library for creating maps and diagrams. You may use other libraries

for creating diagrams that are not possible with Vega-Lite, however, you must get

approval from your tutor before using other libraries.

● The final result consists of a publicly accessible web page that is hosted on your own

GitHub account. The JSON description of each Vega-Lite diagram or map must be easily

accessible in the same GitHub repository and must be in a human-readable format. You

may use the Pure.css library or any other JavaScript/CSS/HTML library or authoring

software to create your web page.

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● Your Vega-Lite visualisation must load reasonably fast. This implies that data files to

download cannot be large. Aim at a total downloadable size of less than 1 megabyte. If

this limit is too low for your visualisation (for example, if you include video files or large

zoomable raster images), then a discussion with your tutor is required before submission.

● Your web page includes at least one geographic map. If including a map does not make

sense for your domain, your tutor can give an exemption for this requirement.

The following requirements from the Data Visualisation 1 assignment also apply for this

assignment:

● Why? It should address a particular need within a specific domain of your choosing. It

must be targeted to the domain, its needs, and its users. This does not mean the

visualisation has to solve an existing problem, but it must be a visualisation that is useful

or relevant to people with an interest in the chosen domain.

● What? It should use a data source relevant to the domain. Data can be of any kind.

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

● The visualisation must turn data into something meaningful and provide insight that

would otherwise be difficult to obtain without the visualisation.

● It must provide interactive exploration.

● It needs to show some innovation. It does not have to be wholly original but cannot be a

replica of a visualisation that already exists. It could be an innovative visualisation idiom,

or an innovative exploration of an interesting dataset.

● It must demonstrate the use of the Five Design Sheet methodology for sketching and

planning the design of your visualisation.

● It must demonstrate the use of the Munzer What/Why/How framework discussed in

lectures for correctly assessing the type of data, the goals of the visualisation and the

design of the visualisation.

● 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 and Schedule

1. By the end of Week 8:

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

b. Find relevant datasets that are publicly available.

c. Discuss your domain, design ideas, and datasets with your tutor.

d. Design your visualisation using the 5 Design Sheet Methodology.

2. Visualisation: Weeks 9 to 11:

a. The homework of Weeks 9 and 10 consist of creating a map and a diagram with

Vega-Lite. You can include improved versions of the map and the diagram that

you create for these homework assignments in this Data Visualisation 2

assignment. Important: Monash University policy does not allow submitting the

same work for two assessments. Therefore, you need to clearly improve your

homework map and diagram if you include them in this Data Visualisation 2

assignment.

b. Create a web page and embed your Vega-Lite diagrams and maps. Use CSS to

style typography and design the layout of your web page. Make your visualisation

publicly viewable as a GitHub page.

3. Write a concise report with a maximum length of 1000 words (excluding the cover sheet

and the bibliographic list) covering the following (note the following requirements are

identical to those for Data Visualisation 1):

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a) A title page including the number of words and a URL of your visualisation.

b) A brief description of the domain, Why and Who.

c) What: A brief description of the data (sources, authors, relevance, creation process,

etc.).

d) Why and How: Give a rationale for choosing the specific idioms and explain how they

help the users to achieve their tasks. Include at least one screen capture of your

entire visualisation, and a description of features that are special to your

visualisation.

e) Design: Briefly explain the rationale for your choices of

o Layout: How did you structure the layout in columns and rows?

o Colour: What are the reasons for selecting the specific colours of your

visualisation, and how did you consistently apply the colours to charts, text,

and figures?

o Figure-ground: How did you vary graphical elements to create a visual

hierarchy?

o Typography: What are the reasons for selecting the specific typeface(s) and

text layout?

o Storytelling: How is the reader guided through the visualisation by using

annotations and other means.

f) Bibliography/list of references.

g) Appendix with scans or photos of the 5 Design Sheet Methodology outcome.

Expectations

Note the following is a verbatim copy from the Data Visualisation 1 assignment, except for the

first paragraph about maps.

Maps: The visualisation includes at least one map that uses an appropriate map projection and

shows data with an appropriate idiom.

Format: The entire visualisation must be accessible through a single URL. The entire visualisation

must be visible on a single web page that can be scrolled. There should be no buttons (or other

web links) that swap the major section of the web page, but you can use buttons to show and

hide individual page 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.

Quality not quantity: Your visualisation will likely contain between 3 and 10 charts or diagrams

that you create. However, there are no minimum or maximum numbers of charts. Instead, we are

looking for carefully designed and annotated charts that – in combination with text and possibly

icons and pictures – guide the user through an interesting story. Avoid pixelated or

non-informative graphical elements. Complement your visualisation with concise, informative and

grammatically correct text.

Interactivity: Integrate interactivity where it makes sense, but do not just add interactive

elements for their own sake.

Copyright: You are encouraged to use icons and other simple graphical elements where

appropriate. When using such elements, it is your responsibility to ensure you have the right to

use them. Consult with your tutor if in doubt. You need to indicate the source and URL (if

available online) in your report of any external element that you use, such as datasets, photos

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and sources of other information. There is no need to indicate the source and URL for simple

icons (emojis, coats of arms, trademark icons, etc.).

Authorship: Because your visualisation is publicly accessible, you should indicate your authorship

and the license under which you make your work accessible.

Plagiarism: We will follow up on any kind of academic misconduct. For this assignment, you

cannot integrate non-trivial graphics (such as diagrams, charts, information graphics, etc.) created

by others.

Report content: The report must not include an introduction to the visualisation topic or extra

information about the topic. The visualisation itself needs to tell the entire story. There is no need

to include a table of contents or a conclusion in the report.

References in report: Your report should include properly formatted references to the datasets,

sources of information that you used to create your visualisation, possibly similar visualisation in

the same domain, and photos, schemas, etc.) that you include in your visualisation. Your text

needs to include in-text citations, and your report needs to contain a bibliographic list. The

referencing style in this course is APA 6th [link], which is the recommended style for

undergraduate students in the Faculty of Information Technology. Note that every in-text

reference needs to be listed in the bibliographic list, and every entry in the bibliographic list needs

to be referenced in the text.

Figures in report: Figures need to be numbered and referenced in the text with the figure

number. Every figure needs to have a caption.

Marking Rubric

The mark will be an automatic 0 if one of the following conditions is met:

● The student does not pass the interview assessment in Week 12.

● The domain of Visualisation 2 is not clearly different from the domain of

Visualisation 1.

● The web page or any Vega-Lite elements are not accessible on a public GitHub

repository.

Note: Only maps and diagrams created with Vega-Lite will be marked (unless the tutor approved

an exception). If the map of homework Week 9 and the diagram of Week 10 are included in this

assignment, they will only be marked if they are substantially improved. If no map is included, the

maximum mark for “Visualisation – Idioms and Complexity” is 5% instead of 10% (unless the tutor

approved an exception). If the report does not include a working URL to your visualisation the

Visualisation a, b and c (see rubric) are marked with 0. A detailed marking rubric is on the next

page.