diff --git a/Project/__ProjectDataViz.md b/Project/__ProjectDataViz.md deleted file mode 100644 index cbebbefe7a55d64da8cafc496767b1ba20f467fe..0000000000000000000000000000000000000000 --- a/Project/__ProjectDataViz.md +++ /dev/null @@ -1,124 +0,0 @@ -# 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`)