Part I of this workshop will introduce researchers (from postdocs to undergrads) to the fundamentals of research data management. You’ll learn about the data life cycle: creating, processing, analyzing, preserving, giving access to, and re-using data. We’ll discuss how to identify the current best practices in your field and any funder or publisher mandates that you’ll need to be aware of. Topics will include metadata standards, data documentation, data preservation, and how to access Yale’s many resources for data management help. In addition, we’ll discuss data management guidelines for NIH, NSF, and NEH grants.
Part II will work with the open source data cleaning tool OpenRefine. It will show how this powerful, free software can help normalize, clean, and structure your messy research data. We will use sample messy data for the workshop, but attendees are welcome to bring their own messy data for tips on cleaning.