程序代写案例-CMT218

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Cardiff School of Computer Science and Informatics
Coursework Assessment Pro-forma

Module Code: CMT218
Module Title: Data Visualisation

Lecturer: Dr Martin Chorley
Assessment Title: Data Analysis and Visualisation Creation
Assessment Number: 2
Date Set: 20th April 2021
Submission Date and Time: by 26th May 2021 at 9:30am
Return Date: 21st June 2021

This assignment is worth 70% of the total marks available for this module. If coursework is
submitted late (and where there are no extenuating circumstances):

1 If the assessment is submitted no later than 24 hours after the deadline,
the mark for the assessment will be capped at the minimum pass mark;
2 If the assessment is submitted more than 24 hours after the deadline, a
mark of 0 will be given for the assessment.

Your submission must include the official Coursework Submission Cover sheet, which can be
found here:

https://docs.cs.cf.ac.uk/downloads/coursework/Coversheet.pdf

Submission Instructions

The coursework submission should consist of two items: a coursework coversheet, and your
submission for the coursework in your chosen format, as explained in the next section

Description Type Name
Cover sheet Compulsory One PDF (.pdf) file [student number].pdf
Data Analysis
and
Visualisation
Compulsory One zip archive (.zip) containing all
code/outputs used to analyse and
visualise data, and the final
visualisation
DAV_[student
number].zip
Visualisation
Evaluation
Compulsory One PDF (.pdf) or Word file (.doc or
.docx)
PR_[student_number]
.pdf/.doc/.docx

Any deviation from the submission instructions above (including the number and types of
files submitted) will result a reduction in marks for that assessment or question part of 10%.

Submission will be via upload to Learning Central.

Staff reserve the right to invite students to a meeting to discuss coursework submissions


Assignment

You are asked to carry out an analysis of a dataset and to present your findings in the form
of a maximum of two (2) visualisations, along with a record and evaluation of your work.

You should find one or more freely available dataset(s) on any topic, from a reliable source.
You may wish to choose something from data.gov.uk or ons.gov.uk for example.

You should carry out an analysis of this data to determine what the data tells you about its
particular topic and should visualise this data in a way that allows a user to understand the
data and what the data shows. You should create a maximum of two visualisations of this
data that efficiently and effectively convey the key message from your chosen data.

You can use any language or tool you like to carry out both the analysis and the
visualisation, but all code used must be submitted as part of the coursework, and it must
include enough instructions/information to be able to run the code and reproduce the
analysis/visualisations. For example, you may wish to extract, transform and analyse the
data using Python, and then create visualisations using d3.js. You would submit all the
Python code, along with a link to (or copy of) the raw data source, and all the HTML, CSS
and JavaScript files necessary to produce a visualisation of the processed data, along with
instructions on how to run all code.

You should create a very short (2 page, ~800 words) evaluation of the success (or not!) of
your completed visualisation(s).

Important! It is expected that each student will choose a different dataset. Once you have
chosen your dataset(s) for analysis, you should complete the form linked below with your
selection to confirm it is a unique choice. Dataset allocation will be done on a first-come,
first-served basis, so do not delay, as another student may ‘claim’ the dataset first! Data
selection should be completed by 27th April at 5PM. Any data redistribution as part of your
submission must abide by the licence under which the data was obtained.

Dataset Selection form:
https://forms.office.com/Pages/ResponsePage.aspx?id=MEu3vWiVVki9vwZ1l3j8vBOfLE1pik
VOra_03FfJWJhUQVJRMFdVMEk0NkRPVlFHNkxBTVFJV1dZWi4u


Learning Outcomes Assessed
1. Examine and explore data to find the best way it can be visually represented
2. Create static, animated and interactive visualisations of data
3. Critically reflect upon and discuss the merits and shortcomings of their own visualisation
work
Criteria for assessment

Credit will be awarded against the following criteria.

Component &
Contribution
Fail (<50) Pass (50-59) Merit (60-69) Distinction (70+)
Dataset selection
and analysis
(10%)
No real data
used, or dataset
‘fake’
No/basic analysis
of data
Real-world data
selected
Cursory high-level
analysis of data
Real-world data
selected
Data analysed in
detail
Multiple real-
world datasets on
similar theme
selected
Visualisation and
Data Presentation
(60%)
None/poor
visualisation of
data
Poor data
presentation
No story
conveyed to user,
story/findings
unclear
Rudimentary or
basic visualisation
of data
Message/story
clear to end user
Appropriate
visualisations
End user able to
explore/interpret
data and affect
display
Message/story
clear
Appropriate
visualisations
with interaction
and/or
appropriate
animation
End user able to
explore/interpret
data and/or
affect display
Message/story
clear
Visualisation
Evaluation
(30%)
Little to no
evaluation

Some effort at
evaluation
Reasonable
evaluation
Insightful
evaluation
Feedback and suggestion for future learning

Feedback on your coursework will address the above criteria. Individual feedback and marks
will be returned on 21st June 2021 via email, with further cohort feedback given by video.

Feedback from this assignment will be useful your dissertation.
Questions

Questions about the assignment can be posted to the COMSC StackOverflow site:
https://stackoverflow.com/c/comsc using the tag cmt218-cw

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