Data Visualisation – Coursework 1

School of Computing, Engineering and Built Environment

Data Visualisation

Module Code: MMI226820

Coursework 1 – Resit (Poster)

Issue date: ________________

This coursework comprises 30% of the overall mark for the module.
Attention is drawn to the university regulations on plagiarism. Whilst discussion of the coursework between individual students is encouraged, the actual work has to be undertaken
individually. Collusion may result in a zero mark being recorded for the coursework for all concerned and may result in further action being taken.

Poster – Data Storytelling

Introduction

The goal of Coursework 1 is to present the work you have done in Coursework 1 in the form of a poster, aimed at a general (non-expert!) audience. This Coursework is open ended: you should create some kind of compelling data story using visualisations of the dataset that you analysed in Coursework 2.

Poster

Your task is to provide a compelling ‘story’ around the findings from your Coursework 2. When we talk about a ‘story’, what we mean is the key takeaway or point. Clearly answering the question “So what?” is the minimum level of the ‘story’ that must exist when we communicate with data for explanatory purposes.

You should not leave it to the audience to figure this out on their own. Never leave your audience wondering “So what?”. You should answer this question clearly for them!

The poster should include the following components:

A compelling title
A clear description of the research question and/or problem to be solved.

iii. At least three different types of data visualisations that are suitable for a general audience. You should base this on some (or all) of the data visualisations from Coursework 2. However, you are welcome to modify these visualisations using R or within PowerPoint, for example by adding annotations.

A conclusion, take home message, and/or call to action.
The design of the poster is entirely up to you. I encourage you to get creative!

Below are some further points to consider:

Choose data visualisation formats that show your data’s best (and most interesting or informative) side.

Simple and clear is often (but not always) better than complex and confusing.

If you want to show complex information, first show a part (or a simplified version) of the visualisation and then build up to the full, complex visualisation.

Eliminate clutter. Identify elements that don’t add informative value and remove them from your poster.

Be consistent, for example by using the same colour scheme for categories of a variable throughout the poster.

Review the marking criteria below and please ask questions if any of the expectations are unclear.

Poster format

Your presentation should take the form of a single presentation slide(A4 size) created with Microsoft PowerPoint software. The layout of the slide can be either portrait (vertical) or landscape (horizontal). More information on how to set the size and layout of the slide can be found here: https://www.teachucomp.com/change-the-size-of-slides-in-powerpoint-instructions/

Please make sure that the poster is clearly readable at a comfortable distance from the monitor in full screen view.

Final deliverable

Upload the following file to Turnitin: a pdf document of the poster.

Please note that only one submission can be made so make sure you are happy with your work before you submit.

Coursework reports should be submitted to GCULearn via Turnitin no later than Wednesday 7th of August 2024 23.59

5. Marking criteria

Coursework 1 is worth 30% of the Data Visualisation module assessment. The Coursework will be awarded a mark out of 100 which will be weighted at 30% within the overall module mark. A separate mark is given for each element in the marking scheme. The way that those marks are allocated within the coursework is outlined in Table 1.