代做DTS204TC、代写Java编程语言

日期：2024-05-15 08:44

XJTLU Entrepreneur College (Taicang) Cover Sheet

Module code and Title DTS204TC Data Visualisation

School Title School of AI and Advanced Computing

Assignment Title Coursework

Submission Deadline

Final Word Count N/A

If you agree to let the university use your work anonymously for teaching

and learning purposes, please type “yes” here.

I certify that I have read and understood the University’s Policy for dealing with Plagiarism,

Collusion and the Fabrication of Data (available on Learning Mall Online). With reference to this

policy I certify that:

• My work does not contain any instances of plagiarism and/or collusion.

My work does not contain any fabricated data.

By uploading my assignment onto Learning Mall Online, I formally declare

that all of the above information is true to the best of my knowledge and

belief.

Scoring – For Tutor Use

Student ID

Stage of

Marking

Marker

Code

Learning Outcomes Achieved （F/P/M/D）

(please modify as appropriate)

Final

Score

A B C

1st Marker – red

pen

Moderation

– green pen

IM

Initials

The original mark has been accepted by the moderator

(please circle as appropriate):

Y / N

Data entry and score calculation have been checked by

another tutor (please circle):

Y

2nd Marker if

needed – green

pen

For Academic Office Use Possible Academic Infringement (please tick as appropriate)

Date

Received

Days

late

Late

Penalty

☐ Category A

Total Academic Infringement Penalty

(A,B, C, D, E, Please modify where

necessary) _____________________

☐ Category B

☐ Category C

☐ Category D

☐ Category E

DTS204TC Data Visualisation

Final Coursework

Submission deadline: 23:59 Beijing Time, May 23rd, 2024

Percentage in final mark: 100%

Learning outcomes assessed: A, B, C, D, E, F, G

Late policy: 5% of the total marks available for the assessment shall be deducted from the assessment mark for each

working day after the submission date, up to a maximum of five working days

Risks:

• Please read the coursework instructions and requirements carefully. Not following these instructions and

requirements may result in loss of marks.

• Plagiarism results in award of ZERO mark.

• The formal procedure for submitting coursework at XJTLU is strictly followed. Submission link on

Learning Mall will be provided in due course. The submission timestamp on Learning Mall will be used to

check late submission.

Overview

In this coursework, you are expected to complete two tasks. For task 1, you need to complete a data visualisation

and submit a dataset, an HTML file, a video that can show your visualisation and other potential materials. For Task

2, you need to submit a form (PDF).

Task 1 (60 marks)

You are given a public dataset of The BWF Badminton Rankings – Men’s Single. Based on this dataset, please

design and create a data visualisation to illustrate the distribution of the top 20 by country and region. Here are task

specifications:

• Target: You are asked to use D3.js to create one visualisation that presents the following information:

o In the main visualization results, you need to present the number of players from different

countries or regions in the top 20 and the sum of points for players from each country or region

within the top 20."

o The highest ranking of each country or region within the top 20 should be presented by the

interaction.

o The names and corresponding scores of players from each country or region within the top 20

should be presented by the interaction.

• Basic Requirements:

o Get necessary data from the dataset correctly.

o Choose the type of the visualisation

o Design marks and channels.

o Complete a basic visualisation with suitable designs (scale, axes, text, colour designs etc).

o Interactions are necessary. When the user moves the mouse in your visualisation, the

corresponding mark should be highlighted and show the highest ranking, names and

corresponding scores of athletes. For example, if you move the mouse to the mark of China, it

will show a tooltip that contains the highest ranking, names and corresponding scores of

athletes in China within the top 20.

o Animations are necessary to show how the visualisation is generated.

• Submissions (a zip file (ID_Name_DTS204TC_CW.zip) which contains following documents):

o The original dataset.

o HTML file with your codes.

o Videos (mp4) or Screenshot that can show all elements in your visualisation.

o *If you write your JS codes and CSS outside the HTML file, you need to provide your JS and

CSS files.

o *If you set up the D3 environment by local route, you need to submit the “d3.min.js”

• Additional Notes:

o You can only use D3.js, JavaScript and HTML. You will get marks deducted if you use additional

libraries to complete this task.

o Your submitted dataset should be the original one, which means you cannot change the data in the

dataset.

o Suitable comments are necessary for your codes. It also affects your marks.

o The screenshot is acceptable only if your visualisation does not contain any animation and

interaction.

o The way you choose for writing your JS and CSS codes will not affect your final marks.

o Please make sure you upload the CW to the LMO correctly.

o Your report can only consist following contents:

§ If your codes do not work, explain what you have done.

§ If you use other libraries, list your libraries in the report.

§ If you use 3D marks in your visualisation, describe your 3D design and explain why you

choose 3D marks.

Task 2 (40 marks)

Here are two data visualisations of the World Population by Tereza Iofciu and Agustin.

https://observablehq.com/@terezaif/world-population-density-by-country

https://observablehq.com/@aguformoso/world-population

• Target: Please analyse and compare these two visualisations. Then please complete the attached form

“Task2.docx”, which contains following contents:

o Dataset types, Data Types, Attributes and Corresponding Types, Actions.

o List Marks and Channels of each visualisation. Describe the design of Channels.

o Describe Potential interaction view of each visualisation.

o Limitations of each visualisation (marks, channels, interactions …).

o Compare these two visualisations, choose the one you think is better and explain reasons.

• Submission: You should submit a PDF file that converted from the completed “Task2.docx”.

Generic Marking Criteria

Grade Point Scale Criteria to be satisfied

A 81+ First Ø Outstanding work that is at the upper limit of

performance.

Ø Work would be worthy of dissemination under

appropriate conditions.

Ø Mastery of advanced methods and techniques at a level

beyond that explicitly taught.

Ø Ability to synthesise and employ in an original way ideas

from across the subject.

Ø In group work, there is evidence of an outstanding

individual contribution.

Ø Excellent presentation.

Ø Outstanding command of critical analysis and judgment.

B 70 - 80 First Ø Excellent range and depth of attainment of intended

learning outcomes.

Ø Mastery of a wide range of methods and techniques.

Ø Evidence of study and originality clearly beyond the

bounds of what has been taught.

Ø In group work, there is evidence of an excellent individual

contribution.

Ø Excellent presentation.

Ø Able to display a command of critical thinking, analysis

and judgment.

C 60 - 69 Upper Second Ø Attained all the intended learning outcomes for a module

or assessment.

Ø Able to use well a range of methods and techniques to

come to conclusions.

Ø Evidence of study, comprehension, and synthesis beyond

the bounds of what has been explicitly taught.

Ø Very good presentation of material.

Ø Able to employ critical analysis and judgement.

Ø Where group work is involved there is evidence of a

productive individual contribution

D 50- 59 Lower Second Ø Some limitations in attainment of learning objectives but

has managed to grasp most of them.

Ø Able to use most of the methods and techniques taught.

Ø Evidence of study and comprehension of what has been

taught

Ø Adequate presentation of material.

Ø Some grasp of issues and concepts underlying the

techniques and material taught.

Ø Where group work is involved, there is evidence of a

positive individual contribution.

E 40 - 49 Third Ø Limited attainment of intended learning outcomes.

Ø Able to use a proportion of the basic methods and

techniques taught.

Ø Evidence of study and comprehension of what has been

taught but grasp insecure.

Ø Poorly presented. Ø Some grasp of the issues and concepts underlying the

techniques and material taught, but weak and

incomplete.

F 0

- 39 Fail

Ø Attainment of only a minority of the learning outcomes. Ø Able to demonstrate a clear but limited use of some of

the basic methods and techniques taught.

Ø Weak and incomplete grasp of what has been taught. Ø Deficient understanding of the issues and concepts

underlying the techniques and material taught.

Ø Attainment of nearly all the intended learning outcomes

deficient.

Ø Lack of ability to use at all or the right methods and

techniques taught.

Ø Inadequately and incoherently presented. Ø Wholly deficient grasp of what has been taught. Ø Lack of understanding of the issues and concepts

underlying the techniques and material taught.

Ø Incoherence in presentation of information that hinders

understanding.

G

0 Fail

Ø No significant assessable material, absent, or assessment

missing a "must pass" component.

Rubric

Tasks 100 Components Description Maximum

Credit Mark

Task 1 60

Basic Elements

Implementation

[34 marks]

Data loading & deriving 8

Scales with current domain and range

for both axes 4

Axes with suitable position and length 8

Methods that show all attributes in one

visualisation 7

Text that clearly presents the axes 5

Chart title and axes title 2

Visualisation Design

[7 marks]

Marks design 2

Channels design 2

Colour choice 3

Interaction and Animation

[12 marks]

Interaction 8

Animation 4

Code Quality

[7 marks]

Only use required libraries to achieve

requirements 2

Add clear comments with basic

explanations before every part of codes 3

Well-documented 2

Task 2 40

Data & Task Abstraction

[10 marks]

Dataset types 2

Data types 3

Attributes and their types 3

Actions 2

Visualisation Analysis

[20 marks]

Marks and channels 9

Interactions 6

Limitations 5

Comparison

[10 marks]

Clearly present the result of the

comparison 2

Explain reasons 8

Late Submission? £ Yes

£ No

Days

late

Final Marks