I neglected to provide context for this list of activities, so the post has been edited to provide background info about the lab pilot.
Effective data management strategies for health and social sciences: Focusing on data integrity and efficiency
Description: This 8-hour introductory lab is designed to provide training on practical data management methods that can be applied to numeric, text, and multimedia data in the health and social sciences. This lab is designed to be the first of three in a series, with more advanced and specialized issues covered in future labs.
Format: Minimal lecture, some discussion, primarily hands-on application of strategies using freely available tools (at IUPUI) such as Box, REDCap, RFS, SDA, etc. The examples and exercises will center on three sample datasets and associated scenarios.
- Build awareness of research data management issues associated with digital data.
- Introduce methods to address common data management issues and facilitate data integrity.
- Introduce institutional resources supporting effective data management methods.
- Build proficiency in applying these methods.
- Build strategic skills that enable attendees to solve new data management problems.
This list will likely be pared down significantly after next week’s meeting, but here’s the initial list of activities as a PDF. The content outline is described in my poster for the Data Information Literacy Symposium, as well as an earlier post.