Assignments

Introduction to Open Science

Overview

This course uses short reflections, hands-on labs, and a cumulative open project to help you practice open and reproducible research. This page summarizes each assignment, typical deadlines, and grading weights.

Grading Breakdown

  • Participation and engagement: 10%
  • Reflections (4 × 5%): 20%
  • Labs / practical exercises (5 × 6%): 30%
  • Open project (proposal, draft, final, presentation): 40%

Total: 100%

Participation and Engagement (10%)

Participation includes:

  • Regular attendance and preparation (completing readings or short pre-class tasks).
  • Active, respectful engagement in discussions, peer review, and in-class activities.
  • Contributions to collaborative workspaces (e.g., GitHub Discussions, shared notes).

Participation is assessed holistically across the semester rather than on a point-per-day basis.

Reflections (20%)

You will complete four short reflections (about 500 words each). Each reflection asks you to connect course ideas to your own disciplinary context or research interests.

  • Reflection 1 – Reproducibility in your field (Week 2):
    Describe how reproducibility issues show up in your discipline and what reforms you see (or don’t see).

  • Reflection 2 – Collaboration and version control (Week 6):
    Reflect on how Git/GitHub could change the way you collaborate on research or teaching.

  • Reflection 3 – Sharing data and code (Week 9):
    Discuss opportunities and challenges for sharing data/code in your area, including any constraints.

  • Reflection 4 – Ethics, equity, and openness (Week 12):
    Consider ethical and equity implications of open science for the communities and contexts you study.

Each reflection is typically submitted via the course repo (e.g., a Markdown or Quarto file in your student folder) with a short commit message.

Labs / Practical Exercises (30%)

Labs are structured, hands-on activities that build specific skills. Each is designed to be small enough for 1–2 weeks of work.

Lab 1 – Project Skeleton (Week 4)

  • Set up a logically organized project structure (folders for data, code, docs, outputs).
  • Create a README that describes the project purpose, data sources (real or simulated), and basic instructions.
  • Add minimal documentation (e.g., placeholder data dictionary, notes on required software).

Deliverable: A Git-tracked project skeleton in your repository, with initial commit history.

Lab 2 – Git Basics (Week 5)

  • Initialize a local Git repository or connect to an existing remote.
  • Practice staging, committing, viewing history, and creating/merging branches.
  • Demonstrate at least one example of resolving a simple conflict or reverting changes.

Deliverable: Repository with clear commit history that documents your work across multiple commits.

Lab 3 – Reproducible Report with Quarto (Week 7)

  • Create a Quarto document that imports data, performs a simple analysis, and produces at least one figure or table.
  • Include narrative text interpreting results, plus a short “Methods” description.
  • Ensure the document can be rendered from raw data to final output with a single command.

Deliverable: Quarto source file and rendered output (HTML or PDF) in your repository.

Lab 4 – Licensing Plan (Week 10)

  • Identify appropriate licenses for your project’s code and content (e.g., MIT for code, CC BY for materials).
  • Add license information to your repository (e.g., LICENSE and CONTENT-LICENSE files, plus notes in the README).
  • Briefly justify your choices in a short Markdown/Quarto note.

Deliverable: Updated repository with licenses in place and a one-page licensing rationale.

Lab 5 – Project Refinement (Week 13)

  • Conduct a self-audit of your project using a provided checklist (organization, documentation, reproducibility).
  • Address at least three concrete improvements (e.g., clearer file naming, more detailed README, improved comments).
  • Prepare your repository for public sharing and final presentation.

Deliverable: Updated repository and completed checklist summarizing changes made.

Open Project (40%)

The open project is a small, self-contained research or demonstration project that applies the concepts and tools from the course. You may work individually or in pairs (with instructor approval). The final project applies the full open science workflow you’ve learned throughout the course. Working individually or in pairs (with instructor approval), you’ll create a public GitHub repository containing data (or simulated/open data), analysis code, a fully reproducible Quarto report or site, and comprehensive documentation. The project culminates in a 5–10 minute in-class presentation during Week 14. Key milestones include a proposal (Week 6), peer-reviewed draft (Week 11), and final submission (Week 14) worth 40% of your grade.

Components and Timeline

  • Project Idea / Proposal (5%) – around Week 5–6
    • 1–2 pages outlining your research question or demonstration goal, data source(s), planned methods, and openness plan.
  • Project Draft (10%) – around Week 10–11
    • Working repository with initial analysis, draft Quarto report or site, and preliminary documentation.
    • Used for in-class peer review.
  • Final Project (20%) – Week 14
    • Public GitHub repository with:
      • Organized folder structure and clear README.
      • Data (or clear description and access instructions), code, and fully rendered report/site.
      • Licensing and citation information.
      • Evidence that the workflow is reproducible on another machine (within reasonable constraints).
  • Presentation (5%) – Week 14
    • 5–10 minute in-class presentation or lightning talk.
    • Briefly describe the research question, workflow, key findings, and how you implemented open and reproducible practices.

Evaluation Criteria

Projects are evaluated on:

  • Reproducibility: Can others follow your instructions and re-run the analysis?
  • Openness: Are data, code, and materials shared with appropriate licensing and documentation?
  • Rigor and clarity: Are methods and results communicated clearly and accurately?
  • Design and organization: Is the repository easy to navigate and understand?
  • Reflection: Do you thoughtfully discuss limitations, ethical considerations, and next steps?

Submission and Feedback

  • All assignments are submitted via your GitHub repository unless otherwise specified.
  • Feedback is provided through a mix of in-line comments, GitHub issues, and brief summary notes.
  • Late work, extensions, and revision opportunities follow the policies described in the syllabus.

Notes

This assignments page is a working document. Details (due dates, specific datasets, tools, or rubrics) may be updated during the term; any changes will be announced in class and on the course home page.