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 Visualization: Theory to Practice
NNLM's Research Data Management Webinar series
Join us for a presentation from Negeen Aghassibake, the Data Visualization Librarian at University of Washington Libraries, to take data visualization instruction to the next level and start creating your own visualizations.
When: December 6th, 2019 from 10 - 11 AM (Pacific) | 11 AM - Noon (Mountain) | 12 - 1 PM (Central) | 1-2 PM (Eastern)
Data Science around the Regions
- DataFlash: NIH Requests Public Comment on a Draft Policy for Data Management and Sharing and Supplemental Draft Guidance
- NIH Requests Public Comment on a Draft Policy for Data Management and Sharing and Supplemental Draft Guidance
- UC Libraries and IT@UC Partner to Bring Renowned NLM Data Scientist to Campus
- National Medical Librarians Month: Sara Mannheimer
- Register Today! Finding Clinically Relevant Genetic Information
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.