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.
Better than Best Practices: Inclusive Data Visualization
Webinar: December 10th, 2020
Data visualization design “best practices" often do not prioritize (or outright reject) efforts to be inclusive. Libraries have an opportunity to step into the world of data visualization and empower historically marginalized voices in data creation and sharing. This webinar will explore the intersections of equity, inclusion, accessibility, and data visualization to consider who we’re visualizing for, what we’re visualizing, and how and why we’re visualizing it.
Cool Creative Communications: Dazzling Data Visualization
This class is intended as a quick-start guide to creating effective data visualizations and is geared toward a general audience with no prior experience.
Data Science around the Regions
- Living on the Data Fringe: Vaccines on the Mind
- Reflecting on the 2019 American Medical Informatics Association Meeting, A Year Later
- DataFlash: NIH Issues New Policy for Data Management and Sharing
- Living on the Data Fringe: Through a Library Liaison Lens #1
- NNLM’s Data Thesaurus Provides Key Tools for Data-Driven Exploration
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.
Suggest a Resource
We value the expertise of our network members, and invite you to contribute to this site.
Do you know of a data science, data management, or data literacy resource that you think should be included on the NNLM RD3 website?