Get Full Government Meeting Transcripts, Videos, & Alerts Forever!
Get email alerts on the Research Data Services topic
No spam. Unsubscribe anytime.
Libraries broaden research data services to support FAIR, reproducible scholarship
Summary
Presenters from the Network of the National Library of Medicine outlined two main research data services tracks—data management/curation and data science/data literacy—and said libraries play a growing role in ensuring FAIR and reproducible research across the data life cycle.
April Wright, outreach and education librarian for Region 1 of the Network of the National Library of Medicine, opened a webinar on research data services by defining two distinct tracks libraries typically support: data management and curation, and data science and data literacy. Wright said the two tracks require different skill sets but interact: "Reproducibility is an area that encompasses both tracks, the data management side and the data science side."
Wright described data management as work on file naming, metadata, repository deposit, and discovery; the data science track, she said, focuses on programming languages, cleaning, and visualization. She argued that good data management—well-documented and curated files—makes later analyses and reproducibility more efficient. "For example, good data management will result in well documented data which will facilitate more efficient data cleaning," she said.
Presenters emphasized that research data services (RDS) are not a one-size-fits-all function. Libraries new to RDS may offer introductory supports such as LibGuides and workshops, while more mature services provide consultations, partnerships, and specialized staff. The session framed RDS work around FAIR principles (findable, accessible, interoperable, reusable) and placed reproducibility as a central outcome that spans both technical and managerial support.
