Part 1 - Introduction

• Intro: Me and Computational Reproducibility. 20 min (slides)
• Breakout Discussion 1 15 min
  1. Go to notes here
  2. Introduce yourself: Name, Career Stage, why you came today
  3. Assign a note taker
  4. Q1: If you were asked to make your project 100% computational reproducible, what specific challenges would you face?
• Group Insights 3-5 min each group

Part 2 - Principles of Work flow Design

• Principles of Work flow Design 25 min (slides)
• Breakout Discussion 2 15 min
  1. Go to notes here
  2. Assign a note taker
  3. Q2: Describe your research team (career stages, comp. skill levels, type of research). Now, how can you make your team more computational reproducible? What specific challenges would your team face?
  4. Bonus: In the notes on what tools,skills, strategies your discussion group find most important for keeping a project organized and reproducible? We will make a collaborative resource list!
• Group Insights 5 min each group

Resources

• A Quick Guide to Organizing Computational Biology Projects: paper
• Principles of data analysis work flows: preprint
• Getting Started Testing in Data Science: video
• Best Practices in Data Science Series: paper series
• Academic Data Science Alliance (ADSA): community
• The Carpentries Reproducibility Workshop: workshop
• Reproducibility Checklist for projects: checklist