FP3: Final Deliverables

Table of contents

Final Deliverables

The specific final deliverables include:

  1. A bug-free, polished, deployed implementation of your final project available at a publicly accessible URL. Make sure your ultimate project includes the following:
    • The names of all members of your team
    • Acknowledgements for all appropriate sources (both for your datasets, and also any example visualizations, code, etc. that you might have adapted for your purposes). Check the metadata for your datasets to understand which sources need to be acknowledged.
    • The embedding code to your YouTube video.

  2. A final project report, in PDF format. A critical part of the data analysis and design process is being able to describe, communicate, and reflect on the choices you made. Thus, your final project report should summarize and justify 3 key results from your data analysis that motivated or grounded your data story, and 3 important design decisions you made to effectively communicate with and engage your audience. We expect roughly a paragraph of writing per point, which provides a well-reasoned analysis (you may include screenshots and images if they are helpful in conveying a point). Finally, wrap your report up with a paragraph reflecting on your project: how was the work split between group members, and how/why did this differ from the plan you put together for the proposal; looking back, what might you have done differently; and looking ahead, what lessons might you apply to future data visualization and data storytelling projects you work on?

  3. A presentation video (not to exceed 5 minutes in length) that introduces and explains your project. Please upload the video on Canvas and YouTube in high resolution (e.g., 1080p). Your video can take the form of a narrated demo of your project, and may include additional content as you see fit. We expect most videos will use a mixture of static slides and interactive screen capture with overlaid narration. You might consider showing your web page as published on the web. Alternatively, you might create a stripped down version that removes extraneous text in favor of spoken narration, bringing more focus and screen space to your visualizations. The initial frame of your video should include your project name and your team members’ names, and a QR code linking to your project’s publicly accessible URL (if available). Be sure that your video communicates how your visualization designs or results enable a better understanding of your chosen topic. For example, do not simply enumerate various features you’ve implemented: focus on what viewers can learn from your visualization(s). We will post videos online, so we encourage you to put your best face forward to the world!

Submit your final project deliverables on Canvas. Extensions will not be offered as the teaching staff needs sufficient time to grade your projects and submit final grades to the registrar.

Grading

Together, your final deliverables and participation in the exhibition is worth 50 points allocated like so:

  • Final Project Quality (30 points): we will be assessing the effectiveness of the design of your data visualization project in communicating to your target audience. We will not only pay attention to low-level features (e.g., titles, labels, marks, visual encodings, and use of interaction and animation) but higher-level characteristics (e.g., how easy is the story to follow, how clearly does it communicate the insight(s)/message(s), how well do design choices match with your intended audience, etc.). We will also be on the lookout for, and award, especially creative or original approaches!

  • Depth of Writeup (10 points): we will be assessing the degree to which your writeup characterizes and contextualizes your data analysis, provides well-reasoned justification for your design choices, and thoughtfully reflects on lessons learned. Note, we expect writeups to be roughly 7 paragraphs long; excessively long writeups (e.g., that ramble) will be penalized.

  • Video presentation (10 points): we will base your point allocation on how clearly you were able to articulate your data analysis and your implementation of your interactive visualization.