Needs Assessment for Research Data Management Services at the Medical Campus

Background: Research data management involves methods and tools of the data lifecycle that are associated within the research lifecycle. The Medical Center Library has been receiving requests from faculty, students and research staffs regarding assistance with research data management. Librarians, as experts in information management, should be at the frontline to provide new services to fulfill research data management needs. In order to identify the data management service scope, content, and format, we carried out a needs assessment via survey and focus group interviews. This paper is to share our experience of needs assessment for developing research data management services.

Description: To gather the needs of faculty, students and research staff at the medical campus on research data management, a survey and the focus group were conducted in early 2021. A total of 138 library users responded to the survey. We found:
1. As to data organization, training and services on data management plan, file naming conventions, and bibliometrics were significantly needed.
2. For data storage and preservation, work computer hard drive, web-based storage (e.g., Drop Box, Google Drive), and an external hard drive were used most. Only 11% of respondents stored on a closed repository site, such as organization provided data repository space.
3. In terms of data sharing, cloud-base space (e.g., Dropbox) is used most, followed by the university’s network drive, external drive, and thumb drive. 70% of respondents had guidelines and procedures in place for handling sensitive data.

Conclusion: The needs assessment brought us ideas to plan research data management services. Here are a few ongoing action items:
1. Develop a libguide as an information “portal” with the information of data management knowledge and the related trainings, research, and services.
2. Collaborate with the Office of the Vice President for Research to draft data management plan templates that follow policies of different federal government agencies (e.g., NIH, NSF), and explore data repository tools.
3. Provide basic training and/or consultations on data management resources and tools (e.g., ICPSR, RedCap, R, Dedoose, Covidence); data management process documentation; quality control issues (e.g., file name conventions, file version control, and metadata); laws and regulations on copyright, licensing, data ownership, and legal and ethical concerns and restrictions.