Assignment 2: Project
DATA5002 2023T2
Basic information
Weight: 30% of course mark
Key dates:
• 10 July (Monday of Week 7) to 21 July (Friday of Week 8): Submit a proposal
• 4 August (Friday of Week 10): Final submission due, 11:59 PM
Task
In this task, you will create a sophisticated data storytelling narrative and/or an interactive
dashboard.
You will select a real-world dataset and develop either a narrative infographic utilising data
storytelling principles in the form of a web page or similar medium; an interactive dashboard which
enables the user to explore and understand the data; or anything in between.
Some suggested data sources are provided below.
The task will have two stages: the proposal, in which you will select a suitable project and receive
approval; and the final submission.

How many charts should I include in my project?
There is no fixed number of charts that is required to include in your project. If you create a
complex graphic that requires a lot of unique work, your final product could potentially include
only one chart. However, almost all projects will include multiple charts. You will need to make
decisions including: what and how many charts to include, what kind of charts best represent each
message, what order to put charts in or how to arrange them, etc. These decisions are an important
component of data storytelling or dashboard construction, and thus you will be evaluated on these
decisions. If you are concerned about whether you have included enough charts in your project,
make sure to describe your plan in detail in your proposal.

Proposal
In the next two weeks, ideally before 14 July (Friday of Week 7) but definitely before 21 July
(Friday of Week 8), do the following:
1. Select your theme and dataset(s). Some data sources are provided below.
2. Explore them sufficiently to ascertain that the task is feasible (don’t underestimate the time
it takes to clean and understand data).
3. Submit a short (less than 500 words, plus wireframe) proposal describing
◦ the dataset (very briefly),
◦ what you are planning to do,
◦ the story you are planning to tell,
◦ your target audience,
◦ a list of similar visualisations of same or similar data that already exist, if any (doesn’t
count towards the word limit),
◦ the medium in which you plan to develop it (e.g., a web page, a Shiny app, etc.), and
and providing a first draft of a wireframe for your visualisation or dashboard.
I will provide feedback to your proposal within 72 hours of your submission, and I may ask you to
adjust it if the project is too simple or too similar to something that already exists, particularly with
published code.
This component is not marked separately, and there is no penalty for a late submission. However the
project is due on Friday of Week 10 regardless, so the later you obtain approval to proceed, the less
time you will have to complete your project.
Final submission
The medium must be appropriate for the project, and an appropriate form for submitting or posting
it will be provided. At minimum, it should include:
• The infographic or dashboard itself.
• Runnable R code and data to reproduce the data visualisations used and/or to create the
dashboard.
• Any additional instructions needed to do so.
• A short report (1,000 words at most) outlining and justifying the decisions made in the
process of creating the visualisation in terms of design principles discussed in class. Specific
sources, including any code or graphics that you did not create yourself, must cite the
source. (Reference information does not count towards the word limit.)
Assessment criteria
• Analysis:
◦ Level of understanding of the data and its context.
◦ Accuracy of data representation (i.e., not being misleading).
◦ Methodological sophistication.
• Storytelling (for infographics):
◦ Application of storytelling principles and narrative.
◦ Suitability for the target audience.
• Interactivity (for dashboards):
◦ Sophistication and power of the interface.
◦ Usability by the target audience.
• Design:
◦ Application and justification of design principles.
◦ Simplicity and usability.
◦ Aesthetic choices.
Suggested data sources
Note that you can use other sources as well.
• https://data.world/datasets/world
• https://www.healthstats.nsw.gov.au
• https://data.gov.au
• https://opendata.transport.nsw.gov.au
• https://unstats.un.org/home
• https://data.fivethirtyeight.com/
• https://www.reddit.com/r/datasets/
• https://data.nsw.gov.au
• https://data.worldbank.org
• https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx
• https://www.kdnuggets.com/2017/12/big-data-free-sources.html
• https://www.globaldata.com
• https://www.kaggle.com
• https://archive.ics.uci.edu/ml/datasets.php
• https://www.statsci.org/datasets.html
• https://datahub.io/collections
• https://apps.who.int/gho/data/node.home
• https://www.bfi.org.uk/industry-data-insights
• https://www.lib.ncsu.edu/formats/teaching-and-learning-datasets
• https://libguides.lib.rochester.edu/data-stats
• https://www.rforecology.com/post/top-five-ish-sources-of-ecological-data/
• https://careers.uw.edu/blog/2021/10/05/21-places-to-find-free-datasets-for-data-science-
projects-shared-article-from-dataquest/
• https://www.tableau.com/learn/articles/free-public-data-sets
• https://imerit.net/blog/13-best-movie-data-sets-for-machine-learning-projects-all-pbm/
Academic Integrity
Permitted resources
This is an individual assessment. You may not receive help on this assessment from anyone except
for the instructor, and you must not communicate this assessment to anyone.
You may use any static resources, and you must attribute them whenever this use is nontrivial.
Static resources include, but are not limited to, R help files, vignettes, lecture and lab notes, code,
and solutions, published books and manuals, and any web pages available to the public or with a
UNSW subscription.
Unlike Assignment 1, you may ask for help on Q&A sites such as Stack Overflow, but the questions
may only be very low-level technical ones, e.g., “How do I align legends of two ggplot figures so
that their titles are at the same height?” or “I get this error when I run this code. How do I fix it?” In
either case, provide only minimal working examples (MWE) rather than project drafts. Any such
questions must be referenced in your submission.
Just like Assignment 1, you may NOT use generative AI, such as chatGPT, for any part of the
assignment.
If in doubt, ask the instructor first.
Exception: Obtaining data
The above restrictions do not apply to tasks undertaken for obtaining data for your project. In this,
you may solicit, receive, and provide help from your classmates or anyone else. For example, if you
find another interesting source of data, feel free to share it.
Declaration
The University regards plagiarism as a form of academic misconduct, and has very strict rules
regarding plagiarism. See UNSW policies, penalties, and information to help you avoid plagiarism,
as well as the guidelines in the online ELISE tutorials for all new UNSW students. Note, in
particular, the policies on Contract Cheating: sharing your assignment, and, in general, publicly or
privately soliciting or obtaining help with it in ways not expressly authorised by the instructor is not
permitted and will be investigated and punished.
By submitting this assessment item, you declare that this assessment item is your own work, except
where acknowledged, and acknowledge that the assessor of this item may, for the purpose of
assessing this item:
• Reproduce this assessment item and provide a copy to another member of the University;
and/or
• Communicate a copy of this assessment item to a plagiarism checking service (which may
then retain a copy of the assessment item on its database for the purpose of future plagiarism
checking).
You also certify that you have read and understood the University Rules with respect to Student
Conduct.