In this project, you are asked to create an interactive narrative visualisation that communicates some of your findings from the Data Exploration Project.

It is an individual assignment and worth 40% of your total mark for FIT5147.

Relevant Learning Outcomes

●    Choose appropriate data visualisations.

●    Implement interactive data visualisations using R (Shiny) or JavaScript (D3).

Overview of the Tasks

1.    Identify which findings from the Data Exploration Project you wish to communicate. You can  be selective, and you do not need to share everything you have found. The visualisations and accompanying narration should reflect the answers to the questions in your Project Proposal.

2.    Clearly define your intended audience. The audience might be your classmates, the general public, politicians or whoever you like. The interactive narrative visualisation should be designed for the intended audience.

3.    Design an interactive narrative visualisation using the Five Design Sheet methodology.

4.    Prepare a short presentation based on your five design sheets (one sheet per slide).

5.    Submit the slides for your presentation in Week 11.

6.    Present your presentation to your tutorial in Week 11 or 12.

7.    Implement your visualisation using R (Shiny) or JavaScript (D3). The use of other visualisation libraries and packages is subject to approval by your tutor (see the section “Notes on Implementation”). Note that you are not allowed to use R Markdown.

8.    Write a report and export it to PDF.

9.    Submit your report and your source code (see the section “How to Submit”) at the start of the exam period.

Presentation Details

The presentation is an opportunity to gain feedback on your designs from your tutor and peers.   Prepare a three minute presentation based on your five design sheets.  Your presentation should consist of 6 slides covering:

1.   An Introduction: Name, project title, aims and motivation (one slide)

2.    Each of your Five Design Sheets (i.e., one sheet per slide).

The design slides you present must match those submitted on Moodle. If you do not manage your presentation and go overtime, your tutor may stop your presentation, which may restrict the feedback you get on elements of your design.

Report Structure

Write a 15-page (excluding cover page, table of contents, bibliography, and appendix) report that consists of the following sections:

1.    Project title

Title of your narrative visualisation. This can be included in the cover page.

2.    Your identity

Your full name, student ID, tutorial number, and tutor name. This can be included in the cover page.

3.    Introduction

A precise and succinct description of what findings and messages you wanted your narrative visualisation to convey, and who the intended audience is.

4.    Design

A description and justification of your narrative visualisation design process. This should     briefly refer to each of your five design sheets (you must provide the 5 design sheets in the Appendix), and justify your design choices based on the theoretical content of the unit     (throughout Weeks 1-12), for instance: describing consistency in design and interaction; reasons for a particular colour palette; referring to aspects of the human visual system or   genres of narration style; etc. It is important that this section is not simply a description of which charts you chose, but must also justify your final design choices.

5.    Implementation

This section contains a high-level description of your implementation, including libraries        used, references to external code sources such as templates, and reasons for any differences between your final design and the implementation, if applicable. You are not required to       explain the code in detail.  You should also briefly explain the reasons why your project was  challenging (e.g., extensive wrangling was required, advanced use of D3, etc. - see Marking   Criteria 4 for more information).

6.    User guide

This section contains instructions for viewing and exploring your narrative visualisation. This should emphasise any parts of your visualisation that may be easily missed by a reader (e.g., some interaction you have implemented that might not be immediately visible).

7.    Conclusion

Summarise your findings and what you have achieved with your narrative visualisation.     Reflect on what you have learnt in this project, including what in hindsight you might have done differently to improve the result and any future work that you would like to do.

8.    Bibliography

Appropriate references of all resources that have influenced your work in IEEE or APA style (refer to the Monash Uni library's guide page for Monash citing and reference style). This   should include any code templates, design influences and sources on theory, as well as       references which influence any data insights.

9.   Appendix

Include your five design sheets in the Appendix. Make sure you provide clear images and any handwriting is understandable.

Your report should contain high-quality images of your narrative visualisation and five design sheets. If possible, avoid using a single screenshot of the entire page since the resolution might be low; instead, crop and explain individual sections of the page. It is also recommended that you export your PDF using a local word processor (e.g., Microsoft Word), as exporting your document as a PDF  directly from Google Docs will result in low-quality images. Make sure you can read and understand  the PDF document and its images at A4 size without requiring further enlargement.

Notes on the Design

●   The visualisation must be a narrative. Elements of the design must tell the data story, using text and visualisation techniques to narrate how the data and the findings of the exploration process enable the questions about the topic of interest to be answered.

●   Your design must follow the Five Design Sheet process and provide all the required information according to the 5dS template. The designs for Sheets 2-4 must be distinct from  each other. The final design on Sheet 5 is expected to be a refinement of one of those sheets.

●   Each design for Sheets 2-4 is expected to complete the narrative independently of the    other designs. No design sheet should just respond to one of the questions or findings      narrated by the visualisation. No design sheet should consist of a single visualisation          technique, e.g., one graph. Every design should resemble a complete solution with a clear layout that follows a particular narration style.

Notes on the Implementation

●   Your implemented narrative visualisation should be based on the result of your Five Design Sheet process. It does not need to follow it exactly, however it should resemble the final design in Sheet 5. Small changes to your final design are allowed (e.g., layout, visualisation  choices, navigation method, colour) but any such differences between your design and how it was implemented must be explained and justified in the Implementation section of your  report. Likewise, any differences between the final design in your presentation and that in   your report in light of feedback to your presentation must be explained and justified.

●   As a rule of thumb, all visualisation packages and libraries that are included in this unit are allowed for your implementation. This includes, but is not limited to:

○    For R Shiny: ggplot2, ggmap, ggraph, Leaflet, Plotly, igraph, wordcloud, etc.

○    For D3: D3 itself, Leaflet, MapBox, etc. Libraries which act as high-level wrappers for D3 are NOT allowed (e.g., C3.js, dimple).

If you are unsure if a particular visualisation package or library is allowed, please discuss it with your tutor.

●   Tools or packages used for data wrangling, data cleaning, Shiny theming, HTML5 templating, CSS styling, etc. are not subject to these rules and can be used freely (i.e., for anything other than the visualisations themselves). However, you should not use server-side code, like Django or node.js, when implementing your design. Any data used for your DVP must be       read from the files submitted with your code.

●    For performance reasons, it is recommended that you pre-format all of your data files before loading them into R Shiny or D3. In other words, all data wrangling and cleaning steps (if any) should be performed outside of your narrative visualisation code. You are not required to      include the code for data wrangling and cleaning as part of your submission. However, if you have done considerable work since your Data Exploration Project, then you should describe   these steps in your DVP report (see Marking Criteria 3).

Marking Criteria

Data Visualisation Project: Presentation [3%]

●   Quality of oral presentation (confidence, speed, voice) and quality of slides (legibility, design, images) [1%].

●    Logical structure [1%].

●    Choice of content (completeness, appropriate level, discussion of design and implementation alternatives) [1%].

Your code must also contain meaningful comments and be formatted and designed in such a way that it is easily readable and understandable.

Originality

As this is academic work, it must be original and must clearly indicate what elements were your work and what are based on someone-else’s work. If you are including facts, data, opinions or any other     written or graphical information from another source, you must cite the source and reference the      bibliographic details for the source, using the APA or IEEE style guide. This includes any third-party     programming code or software you use in your data exploration and analysis. If you directly quote or replicate any material from a reference, you must do so in a manner appropriate to the APA or IEEE   style guide. Be sure to acknowledge sources that influence your code through your code comments and references in your bibliography. Do not copy complete designs from any external sources.

If you are retaking this unit from a previous semester, please ensure you choose a completely new     design and new visualisation code. The text, design and code cannot have been used in any other      unit. Likewise, you cannot reuse any code or written content that you have used in any previous         assessment tasks for any units. The only self-plagiarism that is allowed is the questions you set in       your Project Proposal this semester and reusing some R code from your Data Exploration Project this semester (if you wish). Any other written content from your Proposal or DEP may not be reused. It must be rewritten for your DVP.

Generative Artificial Intelligence (Generative AI) software or systems like ChatGPT or Midjourney       cannot be used for any part of this assessment task, including (but not limited to) generating written or visual components of your submitted work.

If your work is believed to not be original, due to potential instances of plagiarism, collusion with       other students or contract cheating, your academic integrity will be reviewed. If any breaches of the  academic integrity are confirmed, penalties may be applied to your assignment, the unit and/or even your enrolment in your course.

Submission Due Dates

●   Submit your presentation slides to Moodle, due Monday Week 11 (see Moodle for date and time). Presentations will take place during Week 11 & 12 in your tutorial. Attendance for       both weeks is mandatory.

●   Submit a PDF report and a zip file containing your code and the data to Moodle, due the first Monday of exam period (see Moodle for date and time).

NOTE: All submission times are in Melbourne, Australia local time.

How to Submit

Presentation

1.    Prepare a PDF file containing all five of your design sheets.

2.    Name the file StudentName_StudentID_Presentation.pdf

3.    Submit it via Moodle under Assessments/Presentation (3%).