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COMP5048 Final Exam (main)
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COMP5048 2021 S1 Final Examination
Question 1 (24 marks)
This section aims to assess your basic understanding of data structure and visualization.
There are many different data structures to store/represent various types of data. “ Arrays” and
“Graphs” are the commonly used data structures in Data Visualization.
An array usually consists of multiple data, each of which has multiple attributes. When a 2D array is
used, each datum corresponds to a row of the array and columns consist of attributes.
A graph consists of nodes and links which connect associated nodes. Edges may have directions
and their own attributes.
There are many different visualization methods that have been developed and some names of those
visualization methods are listed below:
· Histogram
· Parallel Coordinate Plot
· Area graph
· Heat map
· Force Directed Graph
· TreeMap

Your task is to assign each of these six visualization methods to either the “Array” or the “Graph”
group to indicate which data structure is most suited for that particular visualization.
Once you assign each visualization method to one of two groups, provide a sketch to depict a typical
appearance of those six types of visualization and explain what sort of visual variables can typically
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be used in each visualization, and also explain what type(s) of analysis(analyses) each visualization
is suited to.
For each visualization, provide
*) Suited Data Structure (Array or Graph)
*) Image (sketch)
*) Typical visual Variable(s) used,
*) Typical Analysis type(s) suited for the visualization

Question 2 (20 marks)
Q2-a (8 marks)
There are a number of ways to visually represent complex data. As a part of the visualization
pipeline, each domain in the data needs to be mapped onto one of the visual variables. An
appropriate visual variable needs to be carefully selected depending on the type of data. In the
lecture, we have discussed the following data types:
Categorical
Ordinal
Interval
Ratio
Your task is to write a brief description for these four data types and give one example of data for
each data type.

Q2-b (12 marks)
In the lecture, we also discussed various visual variables (also called retinal variables). The following
are some of those visual variables:
Size
Color Hue
Color Value
Color Intensity
Texture
Shape
Each visual variable is suited to represent certain data types (listed in Q2-a). The task for Question
2-b is to indicate which data type would be best to use each of these six visual variables. There
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might be more than one data types one visual variable can accurately represent. For each visual
variable, list appropriate data type(s) to represent and explain why each visual variable is suitable to
represent the nominated data type(s).

Question 3 (10 marks)
This section aims to assess your understanding of the use of visual variables.
The following are two examples of Information Visualization published in the public domain. They
were created for general audiences to consume and read some useful pieces of information from
them. However, these samples present a good example of “BAD” visualization. Your task is to
critically analyse and discuss why and how bad these visualizations are. In particular, discuss *) how
visual variables are misused, *) what sort of misleading reading it might cause, and *) how it can be
rectified (explain it with your sketched visualization).

Visualization 1:
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Visualization 2:
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Question 4 (12 marks)
This section aims to assess your understanding of Gestalt principles with respect to visualization.
Explain each of the six Gestalt principles covered in this unit and explain how is each principle
related to visualisation.

Question 5 (14 marks)
This section aims to assess your knowledge about the evaluation of visualization.
In this unit, you have created the visualization(s) to find the market leader of the mobile devices as a
part of your Assignment. However, it did not have an evaluation process.
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When you create various visualizations, you would like to make sure that your visualizations yield
their anticipated impact on users’ ability to “see” and “understand” the data.
List methods you can use to evaluate visualization and explain them and also describe how you
would apply those methods to evaluate the visualisations you created in your Assignment 2.

Question 6 (20 marks)
This section aims to assess your capability of designing a good visualization.
Analysing users’ activity patterns yields extremely useful information towards developing a strategic
plan to improve a business process. For instance, understanding how Web-service users move
between pages and sites, or how users reached the pages that monetise well would help web site
designers to design/implement the improved service. For example, you could improve the
contents/UI of a page, whose “user leave” rate is high, or a monetizing activity can be embedded in
the page, where many users tend to gather around.
Now, let’s assume that we have access to one particular Web service’s user access log. The log
contains *) Session ID, *) Time of access, and *) File/Folder path to a web page, and looks like:

SessionID: am34G45jk, Time: 1352345123, Path: /shop1/
SessionID: am34G45jk, Time: 1352345163, Path: /shop1/item5
SessionID: am34G45jk, Time: 1352345238, Path: /shop1/item8
SessionID: am34G45jk, Time: 1352345431, Path: /shop1/item7
SessionID: am34G45jk, Time: 1352345553, Path: /shop1/item5
…

Your task is to design a visualization system, which would reveal activity patterns of web service
customers. Hence the Key Global Indicator (KGI) of this task is to understand the customers’ activity
patterns on the web service site. Based on this KGI, you need to:
1. list Key Performance Indicators (KPIs), which would explain the KGI (understanding users web
site visit activities). There is no known set of KPIs, you need to come up with KPIs which you
think are appropriate.
2. list all data you would need and their data types. Some data can be directly extracted from the
access log shown above, but some data might need to be computed from the data available in
the access log.
3. for each data you’ve listed in 2), assign an appropriate visual variable.
4. name which visualization method you would use to visualize this type of data. Provide a sketch
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5. list any interaction function (s), which would help a user to explore the data through your
visualization.

Academic honesty
While the University is aware that the vast majority of students and staff act ethically and honestly, it
is opposed to and will not tolerate academic dishonesty or plagiarism and will treat all allegations of
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Further information on academic honesty, academic dishonesty, and the resources available to all
students can be found on the academic integrity pages on the current students website:
https://sydney.edu.au/students/academic-integrity.html (https://sydney.edu.au/students/academic-
integrity.html) .
Further information for on research integrity and ethics for postgraduate research students and
students undertaking research-focussed coursework such as Honours and capstone research
projects can be also be found on the current students website:
https://sydney.edu.au/students/research-integrity-ethics.html
(https://sydney.edu.au/students/research-integrity-ethics.html) .
Compliance statement
In submitting this work, I acknowledge I have understood the following:
I have read and understood the University of Sydney's Academic Honesty in Coursework
Policy 2015 (https://sydney.edu.au/policies/showdoc.aspx?recnum=PDOC2012/254&RendNum=0) .
The work is substantially my own and where any parts of this work are not my own I have
indicated this by acknowledging the source of those parts of the work and enclosed any quoted
text in quotation marks.
The work has not previously been submitted in part or in full for assessment in another unit unless
I have been given permission by my unit of study coordinator to do so.
The work will be submitted to similarity detection software (Turnitin) and a copy of the work will be
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postgraduate research students for research purposes is not added to Turnitin's paper repository.
Engaging in plagiarism or academic dishonesty in coursework will, if detected, lead to the
University commencing proceedings under the Academic Honesty in Coursework Policy 2015
(https://sydney.edu.au/policies/showdoc.aspx?recnum=PDOC2012/254&RendNum=0) and the
Academic Honesty Procedures 2016 (http://sydney.edu.au/policies/default.aspx?
mode=glossary&word=Academic+honesty) .
Engaging in plagiarism or academic dishonesty in research-focussed work will lead to the
University commencing proceedings under the Research Code of Conduct 2013
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(https://sydney.edu.au/policies/showdoc.aspx?recnum=PDOC2013/321&RendNum=0) and the
Academic Honesty Procedures 2016 (http://sydney.edu.au/policies/default.aspx?
mode=glossary&word=Academic+honesty) .
Engaging another person to complete part or all of the submitted work will, if detected, lead to the
University commencing proceedings against me for potential student misconduct under the
University of Sydney (Student Discipline) Rule 2016
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