Team Project

Team Project

Overview and project goal

Collecting data via web scraping and APIs requires practice. Together with your team members, you plan and execute an online data collection throughout the course by closely following the recommendations in “Fields of Gold”.

At the end of the course, you will submit a data package, consisting of

For inspiration, explore past team projects. Use these as a starting point, keeping in mind that grading criteria may have changed and these examples are not flawless.

The focus lies on completing an entire data collection project. Keep each stage of your project manageable and feasible. Your project will ultimately be written up as a proper data documentation, following this paper and corresponding template download. Head over to the grading details to find out more!

Getting started

Workplan, deliverables and coaching Grading requirements Past projects Tips and examples

Organization

Coaching sessions

During the course, you will have the opportunity to meet up with the course instructor for coaching sessions. These sessions are meant for you to receive feedback on your ideas and code. Frequently, this also entails problem-solving & debugging.

Structure of Coaching Sessions:

  • Participation: All teams attend the full session. Teams typically collaborate on their projects while the course instructor provides support (in-person by walking around or via Zoom breakout rooms).

  • Session Format:

    • First Half: Each team gets 5–10 minutes to provide a progress update and seek assistance from the coach.
    • Second Half: Time is allocated on a needs basis to address specific issues or questions raised by teams.

Deliverables: Most coaching sessions will help the team work on some deliverables, which are always due before the next coaching session. Please refer to Canvas for exact due dates each week.

How to Prepare for Coaching Sessions?

  1. Complete Weekly Tasks: Work on your project and submit weekly deliverables to receive constructive feedback.
  2. Preparation: Review lecture materials and relevant academic literature (e.g., Boegershausen et al., 2022; Guyt et al., 2024).
  3. Solve Technical Issues:
  4. Set Up Jupyter Notebook:
    • Load scripts and display any issues (e.g., error messages) on your screen for troubleshooting. Screenshots alone are insufficient.
  5. For Online Sessions:
    • Share your screen (Jupyter Notebook) and ensure your microphone is functional.
    • Be ready for the instructor to take over your screen if needed.

Typical issues to discuss in a coaching session

  • How to capture data, and convert it into a proper format for storage (e.g., CSV file, JSON file)?
  • How to verify whether all data that should have been downloaded/captured indeed was captured?
  • How to schedule/run the data collection for extended periods?
  • How to deal with technical hurdles (e.g., authentication, logging in on a site, scrolling)

Team composition

  • 4-5 students per team
  • you need to subscribe to a team yourself (be present in the live streams for that; registration on Canvas!)
  • we recommend teams to have at least one-two students with coding expertise in Python on their team

Deadline and submission

  • Deadline: Monday, 24 March 2025 (23:59)
  • Submission of your data package via Canvas in one zip file.