Due November 4, 2019 @ 11:59pm through GitHub Classroom

Projects may be submitted up to 3 days late, with a 10% penalty per day

The challenge is that, while they have a rich set of data, they don't have strong ways of exploring that data beyond basic spreadsheets and descriptive statistics. Your goal is to create a set of visualizations that allows them to engage with their data. The raw data is available at: https://drive.google.com/file/d/0B5UMbl9u1_wQc2l0ZTU0dTdoYnM/view

To do this, create visualizations that illustrate at least two insights into their data. The above blog post has some insights you can use to start thinking about this dataset, but I encourage you to think outside of these ideas as well.

• Include a README.md file that outlines:
  • Information about your visualizations and what they show. Include information about interactions, preprocesses, and design as appropriate. Note what tasks the visualization allows you to accomplish to derive this insight and how your design is tailored to support these tasks.
  • Your design process (e.g., how did you go about designing, building, and refining your system? Why did you choose these representations?)
  • Your team roles for each individual
  • How to run your project
• Include at least two unique visualizations:
  • One visualization must include some quantitative data
  • One visualization must include categorical data
  • Each visualization must be interactive
  • Your visualizations should support at least one meaningful comparison between related data attributes
  • Your visualizations should visualize at least five data attributes total
• Be able to work with any dataset of this format (e.g., the numbers are interchangable but the columns and document titles are fixed).

• Unusual Representations: Draw on some of the examples from class to represent data in ways beyond a typical scatterplot or bar chart.
• Style: Keep the style consistent across all your views, with an eye towards intelligently applying visual design.
• Geography: Incorporate maps or other geospatial data components into your visualization.
• Interesting Tasks: Derive insight into the data beyond that provided in Mozilla's current post. Highlight these insights in your readme and describe how the visualization enables them.
• Perceptually-Informed Design: Integrate perceptual concepts into your visualization design and discuss how you've integrated those concepts in your readme.
• Coordinated Views: Have two or more visualizations that interact with one another as you move through the data.

Some platforms to look at include:

• D3
• R with ggplot
• WebGL or Three.js
• ProcessingJS
• Google Maps API
• Open Street Map API
• Bokeh

If you would like to use a platform that will push you in creative ways but may not support all of the requirements of the project, please come talk to me.

• Your README
• Your code and/or project if using a web-based project

If you choose to submit a physicalization, please submit that artifact by leaving it at my office by close of business on November 4. You will still need to submit a readme explaining your project.

Group 1: Jess Mailhot, Julia Medeiros, Mike Flanigan, & Jack Hessburg

Group 2: Telly Umada, Annebeth Buis, Chandan Naik, & Nishank Sharma

Group 3: Viv Lai, Chao-Chun Hsu, & Yichen Wang

Group 4: Mikhaila Friske, Dianna Radpour, & Abbie Zimmerman-Niefield

Group 5: Lan Sang, Ling Liu, & Ziying Zhang

Group 6 Ahmed Al Hasani, Alex Constinescu, & Pratik Revankar