creating a data story that illustrates interesting

You are tasked with creating a data story that illustrates interesting, novel insights from data using visual means.
Australian Expert Writers
You should produce an HTML page containing three charts or more, and supporting text, tables and/or other appropriate graphics to tell your data story. The data story covers one or more related questions of your choice, which you answer by analysing one or more sources of data. Most stories will benefit from considering a broader range of data sources.
Analysis methods may include anything from merely plotting a cleaned version of your data to predictions generated through statistical or machine learning techniques. No matter what analysis methods you use, keep in mind that your story needs to interpret and contextualise the results of your models. While some data might be numerical, you may also choose to use text, images and video. In these cases, you will have to analyse the data using appropriate means from e.g., natural language processing (NLP) or computer vision.
Marks will be awarded for clear, purposeful charts and graphics that follow the principles outlined in the module. Simply creating charts using pre-existing templates will not be sufficient, especially if these fail to display good design principles (as covered in the lectures), or if they do not support the main findings of your story effectively.
Tableau and D3 will be covered in the tutorials for the course and it is expected that you use them to create your charts. You may choose to use another language to create your charts, but if you do so there will not be any support available.
Regardless of the programming language, library or tool you choose to use to code your visuals, the results must be embedded into one coherent data story (realised as a single HTML page), which should be submitted in a zip file along with the code used to create your visualisations and suitable instructions so that the course team can run your data story when assessing your work.
You will be in control of your data story. You will need to choose a topic that is interesting for the audience (your peers and the lecturers on the module), define questions that the data will answer, collect the datasets you need, process and analyse them, choose and produce visuals and put them, together with explanatory text into one common framework.
While you will choose your topic yourself, we offer some suggestions which should give you an idea of the types of questions we are looking for:
Trends in university enrolment: what are causes and consequences?How does (your) local government spend public money?How will fake news affect the 2020 US election?What types of companies are more likely to win contracts from governments?Trends in global life-expectancy: what are factors and effects?Could we see another AIDS pandemic?Could we eat our way out of climate change?Are female tennis players treated unfairly by umpires?What is the safest car on the road?How many words do you need to speak a language?How much does cloud computing cost the environment?
You should then investigate ways to plot your findings. You might want to use a tool such as Excel or Tableau first to quickly generate example plots and find core insights in your data that you want to focus on. This will help you plan your story and the visualisations that you need to create. Once you know what you want to display, you should design appropriate graphics in D3, and write supporting text to link everything together and describe what you found out.
When creating your visualisations it is important to consider the topics covered throughout the course, including the most appropriate type of chart for the data, the use of colour, and the use of appropriate interactivity.
The submission will consist of two items:an HTML version of your storya PDF report
Your data story should be submitted as a single HTML page containing at least three visualisations and supporting text.
Your report should be presented using the provided template and cannot exceed 2500 words (excluding references, tables and figures). You should discuss the visualisations that you have used in your data story (including screenshots), justify why you have chosen them, and describe the narrative design patterns you have used and why. You should describe the characteristics of your visualisations that are well done, and those than could be improved upon. You should discuss why your chosen charts are suitable for what you are presenting, and outline how you would modify the charts to make them even better suited to their task, and how they could tell your story better.
It is important that you discuss the concepts covered in the Friday lectures within your report and use these to justify your chart choices and design. You should cover how each chart makes a particular piece of evidence readable by your intended audience, how it avoids bias or confusion, how it emphasises the key data, and what theories or narrative patterns you have drawn on with its design.
Final hand-in (80%)The final hand-in consists of the story and the report. Feedback will be provided via email 4 weeks after the submission and will consist of the aggregated marks and comments and suggestions for improvement.
Data story (50%)Clarity of narrative (10)Appropriate choice of visualisations (10)Limited chart junk (4)Key data emphasised (4)Appropriate uses of colour (4)Visualisations titled and captioned (4)Supporting narrative text (3)Grammar, spelling & presentation (3)Clear structure and flow to content(4)Appropriate use of interactivity (4)Report (30%)Discusses why chosen charts are suitable for narrative and data (3)Highlights strengths and weaknesses of visualisations (3)Justifies visualisation choices with regard to concepts covered in the course (8)Describes how each visualisation (8)makes a particular piece of evidence readable by the intended audienceavoids bias or confusionemphasises the key dataIs an interesting, well structured read (8)