Supercharge your research with open science meeting 2: Storing data, methods, and code
Written by: Lauren Wolfe -
Welcome to the second post in a ten-post series inspired by this Nature article on how to transition a lab to better facilitate open science! This series is meant to be used as inspiration for those looking to make open science a core part of the lab. For more information on the motivation behind this series and for links to all the posts in this series please see the introduction post.
Motivating questions:
- How do we store and share our data, methods and code?
Goals to keep in mind:
- Have clear systems for data management, storage and backup, as well as for documentation of methods and code.
Reading:
Discussion prompts:
- What are our data-management systems?
Related work at the Hutch:
Many folks at Fred Hutch are thinking about how to manage and store data, methods, and code!
- See this page from the Fred Hutchinson Biomedical Data Science Wiki for information on different data storage options at the Hutch.
- Check out dataPackageR. This package is for processing raw data into tidy data sets and bundling them into R packages to make analyses easier to share and reproduce.
Up next
- What are our values? How do we build trust and facilitate collaboration?