Reproducibility Colloquium
The final session of this workshop series is our ✨Reproducibility Colloquium✨, where you all get a chance to share what you’ve learned with each other and anyone you’d like to invite to attend. You are invited to give a short (about 5min) talk with slides (about 5). To make this as low stakes as possible, here is an outline you may follow when putting together your presentation.
For each slide, you don’t need to address all of the bullet points—focus on what is relevant for the specific aspects of your project you focused on!
Feel free to adapt this outline—add or remove slides as fits your project.
- Slide 1: Super short description of your project for a general audience.1
- Slide 2: Describe the data and code components of your project.
- What data types/sources do you work with?
- Hand-collected field data? A data compilation? Instrument data?
- Data type (e.g., numeric, survey responses, DNA sequences, geospatial)?
- File types and sizes?
- What computational tools are you using, and what are you using them for?
- e.g. Excel for data entry; R for data cleaning and analysis; Illustrator for polishing figures
- What data types/sources do you work with?
- Slide 3: Which aspects of the project did you focus on improving? What was the state of the project before the “makeover”?
- e.g. “I focused on transitioning to using git for version control; previously, I was saving my scripts with a new name each time I worked on them.”
- Screen shots of the “before” are encouraged as visuals
- Slide 4: What changes did you make as part of the “makeover”?
- Why did you focus on these?
- How did you implement the changes?
- Screen shots of the “after” are encouraged as visuals
- Slide 5: Reflections
- What are you most proud of about this?
- Did you run into any challenges?
- What do you see as the next steps?
Footnotes
This is a good opportunity to practice an elevator pitch! Try to keep it to just a couple sentences—just enough background to give some context to your data and code. The goal of the presentation is to focus on your project organization and reproducibility, not the details of your research topic.↩︎
Citation
@online{scott2024,
author = {Scott, Eric and Diaz, Renata and Guo, Jessica and Riemer,
Kristina},
title = {Reproducibility {Colloquium}},
date = {2024},
url = {https://cct-datascience.github.io/repro-data-sci/lessons/12-colloquium/guidelines.html},
doi = {10.5281/zenodo.8411612},
langid = {en}
}