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 Data

Exploration Project.

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 resulting 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 tutors 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 tutors 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, 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 short 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 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 justifies the final design       choices you made, rather than simply listing the charts you have used.

5.     Implementation

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 implementation, if applicable. You are not required to explain the code in detail. You should also briefly explain the reasons why your implementation was challenging (e.g.,   extensive wrangling, complex user interactions, advanced use of D3, etc. - see Marking          Criteria 4 for more information).

6.     User guide

Instructions for how to view and use your narrative visualisation. This should emphasise any parts of your visualisation that may be easily missed by a reader (e.g., obscure user                interaction, hidden information boxes).

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 University Library's guide). 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. It is 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 design must provide a narrative. Text and visualisation techniques should both be used to tell a data story, which clearly presents and articulates the findings and insights you have chosen to communicate about the topic of interest.

●    Your design must follow the Five Design-Sheet process and provide all the required                information according to the Five Design-Sheet 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.

●    Sheets 2-4 should each communicate the entire narrative independently from each other. In other words, Sheets 2-4 should be complete designs that can each stand on their own.    None of these sheets should respond to only a subset of the intended overall narrative, and should consist of more than just a single visualisation technique (e.g., one graph).

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, but it should resemble the final design in Sheet 5. Small changes to your final design are allowed (e.g., layout position, 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 should be explained and justified.

●    As a rule of thumb, all visualisation packages and libraries that are covered 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.

RMarkdown cannot be used.

○     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., anything other      than the visualisations themselves).

●     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%].

Data Visualisation Project: Report and Source Code [37%]

When grading your submission, all components (i.e., the quality of your narrative visualisation design, technical implementation, and the written report) are taken into account:

1.    Visualisation Design [15%]

a.    Appropriate use of Five Design-Sheet methodology and evaluation of your alternative designs [5%].

b.    Quality of implemented narrative visualisation design : clear signposting of messages and intended narrative, provision of appropriate context for the reader, clean and    appropriate layout, attention to detail, good use of colour, references to data             sources, and appropriateness for the intended audience [7%].

c.    Justification of your final design in terms of the human perceptual system and human communication assumptions [3%].

2.    Visualisation Implementation [5%]

a.    Correctness and robustness, performance and usability [3%].

b.    Code comments and code quality [2%].

3.    Project Continuity [2%]

The degree to which the visualisation and report describes data insights related to the questions proposed in your submitted Project Proposal and explored during your Data Exploration Project. Further exploration or improvements can be done, but need to be described and justified within the report word limit along with the expected data          visualisation components.

4.    Project Difficulty [10%]

The degree to which the visualisation project demonstrates sophistication and complexity in terms of its technical, theoretical and design implementation. Marks for this section will be  allocated for the following:

a.    Sophisticated use of different data sources, in particular non-tabular data [2%].

b.    Dealing with very large datasets [2%].

c.    Advanced implementation of D3 / R (Shiny) [3%]

d.    Sophisticated user interaction (e.g., animation, linked interaction) [3%]

Note: Other technical, theoretical and/or design aspects will be considered for marks in this difficulty section. It is therefore crucial to make the marker aware of the complexity of your project by ensuring you mention and justify all elements in your written report.

5.    Project Report [5%]

a.    Quality of writing, images, logical structure, grammar/spelling, appropriate academic referencing [1.5%].

b.    Completeness (i.e., all the above sections should be submitted and complete) [3.5%].

Check Your Code!

Please be sure to check that your code runs correctly. Check on other computers and operating systems if possible. If you do not have access to another computer you can try checking via the Monash MoVE platform.

If your code requires some steps for it to run, then be sure to make these very clear in readme notes for your marker and describe this in the User Guide section of your report. Your code must run on     your marker’s computer on the first attempt for us to be able to mark your submission. If your           submission does not run correctly, 5% (from the implementation mark) will be instantly deducted

from your grade. If after some troubleshooting your grader is still unable to get the code to run, further deductions will occur as we will not be able to fully grade your interactive narrative         visualisation.

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 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 use different code for your implementation. 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).

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%).