Sensitive Data, Smarter Training: Implementing Asynchronous Canvas Modules for Data Safety Training

At Harvard University, researchers working with sensitive data are required to undergo specialized training. For Harvard Kennedy School Master’s in Public Policy students, this is particularly relevant, since their capstone projects often involve original data collection or managing sensitive information. In the past, librarians conducted multiple in-class training sessions for these projects. However, as the volume of these demands have grown, this model has become unsustainable.

To address these challenges, our team transitioned to asynchronous Canvas modules during the current academic year. These modules cover essential topics, including identifying and classifying sensitive data, understanding global privacy regulations, and applying Harvard’s data security framework. This shift not only ensures consistent, high-quality training but also enables the Library and Research Services team to support larger and more diverse cohorts of students without increasing staffing levels.

This presentation will detail the development, implementation, and preliminary outcomes of these modules, which were piloted with variations across six capstone seminar groups. We will discuss the collaborative process of engaging with faculty seminar leaders and coordinating with university stakeholders, as well as the challenges encountered. Additionally, we will highlight how the transition to asynchronous training has freed librarians to focus on providing individualized support for the most complex data safety issues.