This is a train-the-trainer project on FAIR Findable, Accessible, Interoperable, Reusable data basics for data novices. The overall concept is to meet data novices at their comfort levels, in order to increase workforce awareness of open science and FAIR data. We propose to hold a workshop on FAIR data habits for librarians new to thinking about data. Librarians will then pilot small conversation starters with patrons new to FAIR data, and share back insights on whether that appears to have benefitted their patrons. Workshop content will be edited based on feedback, and shared as an open educational resource. The workshop will focus on spreadsheet data for assessment and quality improvement studies. Workshop students will be librarians in non-data-specialist roles. Workshop lessons will use examples from library assessment to illustrate how FAIR practices apply to their own data. By using these familiar examples, the workshop will train librarians to understand how spreadsheet-based data can become FAIR and open. The workshop will then explain how library assessment examples can transfer to understanding health data collection such as quality improvement and basic clinical studies. The familiar library data will serve as a bridge for understanding health assessment and health research data. From there, the librarian students will reach out to their patrons to start conversations about one aspect of FAIR data. Discussion groups with the project PIs will support the librarians in their efforts. This train-the-trainer pilot will support and assess the concept of non-data librarians building basic FAIR habits among patrons. This approach will build open science literacy and fundamental awareness of FAIR across a wide range of the base of the health data workforce.
George Mason University Libraries