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.
NNLM Data Science and Data Management Training Needs Assessment
Call for Feedback
Are you interested in learning about biomedical and health research data management? Is there a specific area of data science/data management that you would like more information on?
The National Network of Libraries of Medicine (NNLM) Data Management Working Group requests feedback on the training needs throughout the country on data science and data management. The field of data science is broad in scope; encompassing a wide variety of areas including the generation, characterization, management, storage, analysis, visualization, integration, use of large data science relevant to biomedical and health research. Participation in this training needs assessment will provide NNLM direction for future educational opportunities. To participate in this assessment, please visit click on the "Take Our Survey" button below. This survey will close November 30, 2017.
The BD2K Guide to the Fundamentals of Data Science Series
9 am PT / 10 am MT/ 11 am CT / 12 pm ET
The BD2K webinar series is back! Join scheduled meetings from your computer, tablet or smartphone or watch the recordings via YouTube.
|10/27||Neuroscience Meta-Data Standards Development
Chris Gorgolewski, Stanford University
|11/03||Big Data Technologies for Biomedical Knowledge Discovery
Ravi Madduri, University of Chicago
|11/10||Principles of Scientific Knowledge Engineering
Gully Burns, University of Southern California
|11/17||Leveling the Playing Field: Applying FAIR Principles to Your Daily Data Tasks
Carl Kesselman, University of Southern California
|12/01||Data Science Needs for Biomedical Research
Ian Foster, University of Chicago
|12/08||Big Brain Data Science & Predictive Health Analytics
Ivo Dinov, University of Michigan
Data Science around the Regions
- NIH Blood Pressure Study Data Supports AHA/ACC Hypertension Guidelines
- Reflections on Big Data in Healthcare: Exploring Emerging Roles
- Call for Participation: NNLM SEA Data Management Program Advisory Committee
- The National Institutes of Health (NIH) Launches a Crowdsourcing Project Called PregSource to Better Understand Pregnancy
- Reflections on: Big Data in Healthcare: Exploring Emerging Roles
October 30th to December 8th
Cool Creative Communications: Dazzling Data Visualization