28 - If you build, they will come: Establishing a data discovery curriculum across a medical campus

Background: Our library is an academic medical library that services schools of medicine, nursing and public health as well as hospitals. The librarians regularly receive an inquiry on finding statistical information or datasets from diverse patron groups ranging from master’s students, fellows and faculty. Through the reference services, it became clear that patrons needed to learn a broad picture of what kinds of data are available to them and they need to deploy search strategies specific to data, different from journal articles. To fill the gap, the library launched a data discovery curriculum in 2019.

Description: Curriculum implementation was done in two phases. When offered for the first time in 2019, the library started with an introductory class on data search titled " Finding health statistics and datasets: Overview & Search Tips”. The class covered topics such as major producers of health data, data catalogs, and how to use PubMed for data search. Next, classes on specific topics (such as mental health data) were introduced. The classes were offered as a library class which was open to anyone affiliated with the institution. They required registration. They were in-person classes in 2019 when first launched but changed to virtual in 2020 due to the pandemic. The evaluation of the curriculum is measured in terms of interest, using registration data.

Conclusion: A total of 16 classes (9 introductory, 7 on specific topics) have been offered in the past 3 years. The total registration was 100+ in 2019, 200+ in 2020, and 300+ in 2021. The average registration per class was 43. Over 50 people registered for more than one class and over 150 added their names to the waiting list. The registration did not suffer so-called “Zoom fatigue.” The sheer registration numbers proved that the program was needed and successful. The presentation will provide a more detailed look at the registration statistics including registration numbers divided by school, department, and status. The most interesting and unanticipated outcome was that the largest registering group was the faculty at the school of medicine.