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D3.js代写 | FIT5147 Narrative Visualisation Project

这个作业是用D3.js创建一个交互式的叙事可视化文件
FIT5147 Narrative Visualisation Project
In this project, you are asked to create an interactive narrative visualisation that communicates
some of your findings from the Data Exploration Project.
It is an individual assignment and worth 40% of your total mark for FIT5147.
Relevant learning outcome
• Choose appropriate data visualisations.
• Implement interactive data visualisations using R (Shiny) or JavaScript and D3.
Overview of the tasks
1. Identify which findings from the Data Exploration Project you wish to communicate. You do
not need to use everything you have found, be selective. At least you should try to answer
your research questions.
2. Clearly define the intended audience. The audience might be your classmates, the general
public, politicians or whoever you like.
3. Design an interactive narrative visualisation using the five design sheet methodology.
4. Prepare a short presentation based on your five design sheets. (i.e., One sheet per slide).
More information about the presentation will be provided later on Moodle.
5. Implement your visualisation as a web-based presentation using R (shiny) or JavaScript and
D3. The use of other tools/visualisation library/visualisation software is subject to approval
by your tutor. (You are not allowed to use R markdown)
6. Write a report and export it to PDF.
7. Submit the report and source codes.
Report structure
Write a 15-pages (excluding bibliography, table of content, cover page, appendix) report consists of
the following sections:
1. Project title
Title of the narrative visualisation. This can be included in the cover page.
2. Your identity.
Your full name, student ID, Lab number, and tutor name. This can be included in the cover
page.
3. Introduction
A precise description of what messages you wanted your narrative visualisation to convey
and who the intended audience is.
4. Design
This section contains a description of the visualisation design process. This summarises the
five design sheets, details alternatives designs you considered, and justifies your final design.
5. Implementation
This section contains a high-level description of the implementation, including libraries used
and reasons for the implementation decisions. You are not expected to explain the codes in
detail.
6. User guide
This section contains instructions for viewing and exploring your narrative visualisation.
7. Conclusion
Summarise your finding and what you have achieved. Reflect on what you have learnt in this
project, including what in hindsight you might have done differently to improve the result.
8. Bibliography
Appropriate references. Refer to this page to see appropriate referencing styles.
9. Appendix
Place your five design sheets in the appendix. Make sure you provide clear images.
Your report should contain high-quality images of the visualisation. You could also briefly explain any
reasons why your project was challenging (e.g. extensive data set, use of D3, etc.) in your report.
Marking Criteria
1. Design [15%]
a. Appropriate use of five design sheet methodology and evaluation of alternatives
[5%].
b. Quality of final design: clear signposting of messages and intended narrative,
provision of appropriate context for the reader, good use of colour, references to
data sources and appropriateness for the intended audience [7%].
c. Justification of final design in terms of the human perceptual system and human
communication assumptions [3%].
2. Implementation [7%]
a. Correctness and robustness, speed, accessibility [5%].
b. Comments and code quality [2%].
3. Difficulty [10%]
Degree of difficulty, e.g. use of non-tabular data, large dataset, D3 programming,
sophisticated user interaction.
4. Presentation [3%]
a. Quality of oral presentation (confidence, speed, voice) and quality of slides
(legibility, design, images) [1%].
b. Logical structure [1%].
c. Choice of content (completeness, appropriate level, discussion of design and
implementation alternatives) [1%].
5. Report [5%]
a. Quality of writing, referencing, images, logical structure [1.5%].
b. Completeness [3.5%].
Submission due dates
• Submit presentation slides to Moodle by 11:55 pm Sunday 7 June 2020 (Presentations will
be done in Week 12, During your lab.)
• Submit a PDF report and a zip file to Moodle by 4:00 pm Thursday 18 June 2020.
NOTE: Times are expressed in Aust/Melbourne local time
How to submit
Once you have completed your work, The following files are to be submitted:
• Presentation slides containing your five design sheets. Name the file
StudentName_StudentID_Presentation.pdf and submitted via Moodle (i.e.,
Assessments/Presentation)
• A PDF report (max 15 pages) and a zipped file containing your visualisation source code and
any data files that are needed to run your code. Please ensure you name the file correctly
using the following format:
o StudentName_StudentID_Report.pdf
o StudentName_StudentID_Code.zip
These two files (i.e., .pdf and .zip) must be submitted via Moodle (i.e., Assessments/
Visualisation Project Code). Do not zip these files into one zip archive, submit two
independent PDF file and zip file.
Please note we cannot mark any work submitted via email or sharing via GDrive. Please ensure that
you submit correctly via Moodle since it is only in this process that you complete the required
student declaration without which work cannot be assessed.
It is your responsibility to ENSURE that the files you submit are the correct files – we strongly
recommend after uploading a submission, and prior to actually submitting in Moodle, that you
download the submission and double-check its contents.
Your assignment MUST show a status of “Submitted for grading” before it will be marked.
If your submission shows a status of “Draft (not submitted)” it will not be assessed and will incur
late penalties if submitted after the due date/time.
Note that you DO NOT need to publish your app on the web.
Late submissions and special consideration
Submission must be made by the due date otherwise penalties will be enforced.
You must negotiate any extensions formally with your campus unit lecturer via the in-semester
special consideration process: http://www.monash.edu.au/exams/special-consideration.html
Penalty of 7% per day for late submissions including weekends & public holidays. Submissions will
not be accepted more than one week after the due date.


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