Assignment 4: Final Project
The final project should be based on the previous assignments. Your team will implement an interactive visualization tool and deploy it on the web based on the tutorials. The team submitted four deliverables: 1) deployed the project on the web, 2) publish your source code to GitHub, 3) project report, and 4) a presentation video. In case you want to change the project to something more interesting for your team, please inform two teaching assistants to check the feasibility of the project.
Project Implementation
We did not have any constraint on any technology you can use to implement the final project. However, the source code should be pushed in GitHub, and we will grade considering your commits in the repository.
The requirements of your project are:
- At least 3 different views/visualization components (e.g. 3 bar charts only count as 1 component)
- Multiple views coordinated with linked highlighting. A click/hover/selection interaction within one view must trigger a change in a different view. At least 2 views need to be linked. Ideally, these views are linked bidirectionally.
- At least 2 UI widgets that allow users to filter the data or update certain views interactively (e.g. dropdown, radio button, range slider, calendar).
- Interactive tooltips are shown when users hover over marks, at least in one view.
You do not necessarily build backends and only an index.html file should be enough. Your interface should be as self-documenting as possible, with appropriate labels for panels, axes, and widgets, a legend documenting the meaning of visual encodings, and a meaningful title and description.
Here are projects from our previous Visual Analytics class https://www.aviz.fr/TeachingVA2019/Project
Examples of excellent projects from Tamara Munzner's class https://www.cs.ubc.ca/~tmm/courses/436V-20/fame/
Deploy your interactive visualization tool on the web. In case you use Streamlit, you can follow this instruction to deploy your app. This video tutorial shows you how to deploy your Streamlit app to Heroku.
Evaluation criteria for the tool
We will evaluate the tool based on ICE-T visualization evaluation criteria.
Report
Your report should have the following structure:
- A title for your project and the names of all team members.
- Introduction: describe your project. Write one paragraph each about:
- What your project visualizes broadly (do not describe individual features yet), who the users are, and what it allows users to do
- Why you built it - what is the motivation
- How you built the tool (e.g. describe software you wrote, libraries and data you used, etc.)
- Feature Description. Briefly describe the main features of your tool and use screenshots to illustrate them. Give information of why you built the feature in this specific way (e.g. why this type of data encoding is in your opinion better than another you may have considered).
- Interesting findings. Write short descriptions of 2-3 things you learned from the dataset using the tool. Illustrate what you found using screenshots.
- Briefly described what each group member contributes in this project.
You are welcome to reuse text from previous assignments, if it still makes sense.
Video Presentation
The team should prepare a presentation video to describe about your project and demo the tool. The video should be at a maximum of 10 minutes and uploaded to YouTube with public or unlisted visibility.
Your presentation should include:
- A 30s elevator pitch - who and what is your website for
- A short explanation of what the website shows, also mention the source of your data
- A short demo of the possible interactions in the website
- A short demo of some of the most interesting things you found in the data
- Mention a few limitations of your tool and possible future work
Split the presentation so that everyone will take a part in the presentation.
You could find the presentation examples here: a pack of short paper presentations from IEEE VIS 2020
For the 30s elevator pitch, you may find examples from YouTube with the search term "IEEE VIS Fast Forward".
A guide on how to record the video and upload to YouTube.
Submission
What and How to submit
- Provide the URL links to access the deployed tool, your GitHub repository, and the presentation video in this Google Form.
- The report must be in the pdf format and submitted in the “Final_[Your team name].pdf” format to this Dropbox.
When to submit:
Final is due before March 31, 2022, 23:59.
Points for this assignment
50 points
Acknowledgment: We designed the final project based on the Visual Analytics course by Petra Isenberg and Information Visualization course by Tamara Munzner.
