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GU4243/GR5243 Fall 2017 Applied Data Science

Project 2 Shiny App Development

- for data.gov open data

In this project, working in teams, you will create a R shiny app for exploring and visualizing a topic about United States using open data from data.gov.

Challenge

For this project, I invite you to browse 193,990 datasets available on data.gov (https://www.data.gov/) about United States and choose a topic that interests you. A number of web applications using open data from data.gov can be found at https://www.data.gov/applications. You can recreate, extend and improve some of these applications' functionality or create something entirely from scratch.

For presentation, the team should present their shiny app as a product demo and interesting findings from their experience. All shiny apps are required to be deployed (either on http://www.shinyapps.io/ or your own Shiny server).

All developments need to be carried out in group shared private repo on [https://www.github.com/TZstatsADS/] with clear project management log, taking advantage of GitHub issues.

Each week, we will give a tutorial in class and having live discussion and brainstorm sessions. The instruction team will join team discussions during class and online.

  • week 1: introduction and project description
  • week 2: shiny app development/shiny server setup/spatial visualization
  • week 3: [TBD] depends on topics emerge from online and in-class discussions.

Evaluation criteria

  • Business values of information presented
    • is it of importance?
    • is it interesting?
    • can it be used to answer questions or exploring for interesting trends?
  • Implementation of the apps
    • are the data processed properly?
    • are necessary measures taken to account for data collection issues such as biases, missing values, etc?
  • Visualization
    • Is the information visualized clearly?
    • Is the visualization easy to understand?
  • Presentation and organization
    • Is the presentation convincing about the business value of the apps?
    • Is the GitHub organized and prepared in a way that makes it easier for readers to appreciate the value of the app and understand how to use the app?

(More details will be posted as grading rubrics in courseoworks/canvas)

Suggested team workflow

  1. [wk1] Week 1 is the planning week. Read data description and browse data.
  2. [wk1] Each team is strongly recommended to demonstrate project progress by posting a project plan with task assignments as issues on GitHub by Sep 27th.
  3. [wk1] As a team, read the example blog posts, projects from Spring 2016 and Fall 2016 on NYC open data, or other interesting analyses found online together (not necessarily face-to-face). During the discussion, study a number of analyses carefully on the techniques and computational packages used.
    • "What information is of value or interesting?"
    • "Which analysis/visualization is particularly informative?"
    • Good visualizations do not just look cool. They should be easy to understand and give the correct impression about data.
  4. [wk1] As a team, brainstorm about possible topics
  5. [wk2] Based on outcomes from week 1 brainstorm sessions, identify the dataset(s) to download and start data cleaning (start early on this one!)
  6. [wk2] Week 2 is the design and development week. Start learning and using the shiny library to do simple things. Some team members may know more about shiny than others. Share and learn together.
  7. [wk2] It is ok to have 2-3 leads to explore at the beginning of week 2 but it is better to converge on a single topic by the end of week 2 (10/4).
  8. [wk2] Construction of shiny platform can start early using fake/simulated data.
  9. [wk3] Week 3 is the shiny app implementation/production/testing week. By 10/4 (the beginning of week 3), you should have a cleaned set of data and a project idea.
  10. [wk3] By 10/4, You should layout a to-do list (as a 2nd set of GitHub issues) for the app production and divide up tasks. At the session on 10/4, team members should work together and resolve any ambiguity about which team member should be doing what for the final stage of production of the app.

Working together

  • Setup a GitHub project folder from joining the GitHub classroom link with everyone listed as contributors. Everyone clones the project locally via your GitHub desktop and create a local branch.
  • The team can work in subgroups of 2-3, which might meet more frequently than the entire team. However, everyone should check in regularly on group discussion online and changes in the GitHub folder.
  • Learn to work together is an important learning goal of this course.

Resources

Here the examples are for inspiration. The order is abitrary. I do not endorse any of these analyses to be a model analysis for you to follow. The tools included are those I think might be useful. Please feel free to send me stories and/or tools that you would like to contribute to this list.

Stories

Blogs

News articles:

Examples

A small set of potential tools

*These are not fully tested and more tools can be found.

Paper to read