NNLM RD3: Resources for Data-Driven Discovery
The NNLM supports access to biomedical and health information with the goal of making data discoverable, accessible, and citable. NNLM RD3: Resources for Data-Driven Discovery has been developed to foster learning and collaboration in data science. In order to support sharing, curating, and annotating biomedical data, NNLM RD3 serves as a resource for librarians, library students, information professionals, and interested individuals to learn about and discuss: library roles in data science; fundamentals of domain sciences; emerging trends in supporting biomedical research.
Data Management Education Needs: Identifying Signposts for Graduate Student Researchers
A MidContinental Region Webinar
Join us for a webinar by Dr. Judy Pasek, STEM Liaison Librarian with the University of Wyoming Libraries, to learn about research conducted at the Universities of Wyoming and Northern Colorado about the data management needs of graduate students!
When: Jul 17, 2019 from 1 - 2PM (Pacific) | 2 - 3PM (Mountain) | 3 - 4PM (Central) | 4-5 PM (Eastern)
Data Science around the Regions
- National Medical Librarians Month: Sara Mannheimer
- Register Today! Finding Clinically Relevant Genetic Information
- NNLM’s RD3 Website: RDM 101 Course Material Available for Non-Course Registrants
- Upcoming Research Data Management Webinar: If You Share It, Will They Come? Quantifying and Characterizing Reuse of Biomedical Research Data
- DataFlash: Stephen Few’s “The Data Loom” – A Book Review
Data Catalog Collaboration Project (DCCP)
Follow the DCCP Blog!
The Data Catalog Collaboration Project (DCCP) helps researchers make their own data discoverable, and locate usable biomedical data that is not readily accessible elsewhere online. The DCCP is a collaboration of academic libraries working to highlight institutional biomedical research data using an open source catalog.
Announcing Data Thesaurus 2.0 !
Welcome to the Data Thesaurus, a resource connecting and defining concepts, services, and tools relevant to librarians working in data-driven discovery. A definition, relevant literature, and web resources accompany each term along with links to related terms.