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# ProjectDataViz
**Class:** BSc Data Science for Responsible Business -- Year 1 Semester 2
**Date:** February 2025
## Interactive Data Visualization Project
### Year 1 BSc Data Science for Responsible Business
### Project Overview
This project aims at creating an interactive data visualization using `D3.js`. The goal is to explore, analyze, and present data in a visually engaging and informative way. Students will work in teams of two to develop a web-based visualization that addresses one of the following topics:
- Personal Data: You can use your personal data from your personal device
- Mobility and Climate Change.
- Environmental Impact of Digital Technology
The project **MUST** be hosted on GitHub, and the final visualization must be publicly accessible via GitHub Pages or another hosting platform. The project accounts for **55% of the final grade** for this course.
## Key Dates and Deliverables
- Teams constitution and creation of the GitHub repo by **20/02/2025**
- Choice of the dataset by **25/02/2025**
- Exploratory data analysis by **01/03/2025**
- Submission of the scoping document and the peer evaluation on **28/03/2025**
- Final presentation on **31/03/2025**
## Project Requirements
### Data Source
- You can use **your** personal data (e.g., Spotify, Facebook, smartphone usage) or public datasets (e.g.,[ Open Data Grand Lyon ](https://www.data.gouv.fr/fr/organizations/grand-lyon/#/datasets), Data Is Plural, [kaggle](https://www.kaggle.com/datasets/), check out this [Link](https://github.com/awesomedata/awesome-public-datasets?tab=readme-ov-file)).
- If necessary, create simulated data or combine multiple datasets.
- You will need to conduct a data wrangling, cleansing and exploratory data analysis to understand the data set and make a plan for the visulaization phase.
### Technical Stack
- **D3.js is mandatory** for creating the visualization. Other libraries (e.g., Tableau, python libraries such as plotly, matplotlib or seaborn, etc.) are **not allowed**.
- The project must be hosted on GitHub and include a **GitHub Pages** deployment.
### Documentation
- Maintain a **project wiki** or **progress log** on GitHub to track your work. This will account for 20% of the project mark.
- Include **sketches, design iterations, and key decisions** in the documentation.
### Final Deliverables
- A **functional web-based visualization** with clear context and storytelling.
- A **scoping document** outlining the problem, target audience, data sources, and design choices.
- A `README.md` file in the GitHub repository containing:
- Project title and description
- Team members and roles
- Links to the live visualization and documentation
- Credits for data sources and inspirations
## Scoping Document Structure
### Problem Statement
- What problem are you addressing?
### Target Audience
- Who is your primary audience?
- What tasks will they perform using your visualization?
- How your visulaization will be helpful for them?
### Related Work
- Identify **three related projects** or visualizations. Explain how they inspire or differ from your approach.
### Data Sources
- List the dataset(s) you plan to use. Highlight their strengths and limitations.
- What is your backup plan if the data is unavailable or incomplete? Are you planning to simulate data or choose another alternative?
- Which type/format of data have you chosen? Structured (SQL) or not (CSV, Json, etc.)
- Exploratory data analyis
- Data cleansing and wrangling (highlight the issues with your dataset and how did you manage to solve them)
### Team Organization
- How will your team communicate and collaborate? Note that the project grade is not necessarily the same for the team members.
- What roles have you assigned (e.g., design, development, data preprocessing)? Note that this has to be clearly stated in the `README.md`file.
Also note that the push operations will serve to assess the active participations of the team members.
## Presentation Guidelines
The final presentation (10 minutes) should cover:
- **Context and Motivation:** Why did you choose this topic?
- **Target Audience:** Who is your visualization for?
- **Demo:** Showcase your interactive visualization.
- **Design and Technical Choices:** Explain your design decisions and technical implementation.
- **Innovation:** What makes your project unique?
- **Limitations:** What challenges did you face, and how did you address them?
## Evaluation Criteria
The project will be graded based on:
- **Peer evaluation (10%)**
- **Scoping Document and Progress Tracking (20%)**
- **Presentation and Demo (25%)**
- **Technical Implementation (45%)**
## Examples and Inspiration
Here are some examples of past projects and resources for inspiration:
- [MBTA Visualization](http://mbtaviz.github.io)
- [Team Data Hub](http://teamdatahub.github.io)
- [Harvard Visualization Course Examples](https://online.hbs.edu/blog/post/data-visualization-examples)
- Other examples
- [1](https://odsc.medium.com/7-cool-data-visualizations-using-d3-and-vega-3ff082d502cb)
- [2](https://qz.com/296941/interactive-graphic-every-active-satellite-orbiting-earth)
## Submission Instructions
### GitHub Repository
- Name your repository meaningfully (e.g., `MobileData-Visualization`).
- Include a `README.md` file with project details and links.
### Images
- Add a **teaser image** (`teaser.png`) and a **thumbnail** (`thumbnail.png` or `.gif`) to the repository.
### Pull Request
Submit a pull request to the course’s GitHub repository with:
- Two images (`numerogroupe-teaser.png`, `numerogroupe-thumbnail.png`)
- Description files (`numerogroupe-desc-fr.md`, `numerogroupe-desc-en.md`)
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