Onboarding Package for Undergraduate Research Assistants

Welcome to BITSS! As a URAP, your tasks will mainly be related to two of our main projects:

1. Open Policy Analysis (OPA)
2. Accelerating Computational Reproducibility in Economics (ACRE).

Within the OPA project you will be part of one of three tracks:

1. Data Visualization for Public Policy (DVPP) – develop interactive data visualizations in the form of web apps using R Shiny;

2. Data Science for Public Policy (DSPP) – translate econometric and policy analyses into R code; or

3. Public Policy Research and Outreach (PPRO) – identify policy analyses for potential application of OPA principles and support the development of common standards for OPA.

Each track will meet weekly to present their progress and discuss next steps. Regardless of your track each week all URAPs must follow the same logistics/workflow.

Logistics/workflow

• Task assignment: At the beginning of the week, you will be assigned tasks via a task list in a GitHub issue. When beginning to work on a task, move it to the 'Work in progress' section, then later move it to the 'Completed' section and mark the task as complete after reviewing it in the weekly meeting.

• Tracking your progress: Each week, you are expected to complete/attempt your assigned tasks and update your report of progress, located in a folder at this repository (See folders 05 and after for format examples). The deadline for submitting your weekly report of progress is Friday 5pm. Reports will be reviewed during the weekend to assign further tasks. If a report is submitted after the deadline, it will be reviewed for the week after. Reports should be summited as a pull request.
  As a minimum requirement to obtain a pass grade, URAPs must submit at least 8 good reports during a semester. A good report must contain three elements: (1) list of assigned tasks, (2) list of progress and questions in each task, (3) number of hours worked during the week. The following are some examples of good and bad:

  • Good examples: learned git, learned R, learned about PA, summarized # reports, pushed # commits, clean shiny app code, support a fellow URAP, etc.
  • Bad examples: apologies, promises, comments, etc. Will be counted as not submitted.

• Unavailability due to midterm overload: each URAP is allowed up to 2 tokens per semester to excuse themselves from working on a given week. You are only required to announce the use of that token one week in advance (in your weekly report).

Fall Calendar

• Week 1 (9/21): Introductory materials for OPA and ACRE.
• Week 2 (9/28): Introductory tasks for each track.
• Week 3 - 10 (23/30): Track-specific tasks.
• Week 11 (11/30): Wrap-up report (summary, tutorials, next steps).

Content

Policy Analysis and Open Policy Analysis

• Learn about examples of policy analyses:
  • Saez & Zucman letter to Senator Elizabeth Warren
  • Section 5 of 2016 deworming paper by Baird et al.
  • Summary of Congressional Budget Office (CBO) report on minimum wage
• Learn about OPA:
  • Click here for the BITSS page on the Wealth tax OPA
    • Link to app
    • Link to dynamic document
    • Link to repository
  • Click here for the BITSS page on the Deworming OPA (forthcoming)

Tools for Open Materials (Computational reproducibility)

• Git Tutorials
  • Pull request basics
  • Understanding the differences between forking and cloning
  • Updating a forked repo
  • Working with branches - step-by-step tutorial for creating a new branch, committing new changes, and merging the branch after making changes
• ACRE Guidelines

Tools for Open Analysis

• Learn about R Markdown:
  • Getting started with R Markdown - a comprehensive introduction to R Markdown
  • R Markdown tutorials from Spring 2020 - contains a cheatsheet, slides from the R Markdown introduction, and demo code
• Learn about Jupyter Notebooks:
  • Explore Project Jupyter
    • View publicly shared Jupyter Notebooks
    • Read about the basics of Jupyter Notebooks for Open Science
  • Jupyter Notebook tutorial - a tutorial on how to set up Jupyter Notebooks on your local machine, and a basic walkthrough (uses Python)
  • Jupyter Notebook quick tips and shortcuts

Tools for Open Output

• Shiny tutorials: includes a demo and online resources, copied below for convenience
  • Shiny tutorial for conceptual understanding
  • Shiny tutorial slides - looking up specific notes
  • Shiny user showcase and demos - review code and apps of other Shiny developers
• DiagrammeR resources (DiagrammeR is an R package that enables you to create graph diagrams using text)
• Plotly resources (Plotly is an R package that allows you to create interactive web-based graphs)
• Voila : Voila is a new Python package that allows you to convert a Jupyter Notebook to an app or dashboard
  • Voila Gallery - explore examples of apps and dashboards
  • Deploy a Jupyter Notebook online

Other Resources

• Click here to visit a URAP-created repository of useful tutorials and summaries for completing your work.