Data Cleaning for Data Sharing Using R
NCME 2024 Workshop
📆 April 11, 2024 // 8:45 am - 12:45 pm EDT
🏨 In Person
📝 NCME attendees can register here
🏡 Workshop website
Overview
Before sharing research study data, it should be vetted to ensure that it is interpretable, analyzable, and reliable. This half-day, in-person workshop will provide a foundational understanding of how to organize data for the purpose of data sharing.
Learning objectives
- Understand how to assess a data set for 7 data quality indicators
- Be able to review a data set and apply a list of standardized data cleaning steps as needed
- Feel comfortable using R code to clean a data set
- Understand types of documentation that should be shared alongside data
Is this workshop for me?
This workshop is for any education researcher who could benefit from guidance on how to take a messy raw dataset and organize it into a shareable data product.
This workshop assumes you have some experience working with rectangular data, as well as a basic working knowledge of the R programming language and experience working in RStudio. This course will focus on functions in the {Tidyverse} so familiarity with that package will be helpful, but is not required.
Further Learning
Speaker
Crystal Lewis is an independent research data management consultant, providing recommendations, direct service, and training to education researchers and their teams across the country. She also co-organizes two community groups—R-Ladies St. Louis, an organization focused on promoting gender diversity in the R community, as well as the POWER (providing women opportunities in education research) Data Management Hub, where she facilitates peer data management support in the education research community.