2025 NCDS Fundamentals of Health Data Science Community Expert Application

We invite applicants for the role of Community Experts for the Fundamentals of Health Data Science course, which is a 10-week online course that will take place from January 6, 2025 – March 21, 2025. This class is designed to provide information professionals, working in health sciences, with an introduction to data science. The purpose of Community Experts is to help students progress through the course and expand their understanding of data science. To ensure accessibility, materials created for and used in this course will be compliant with Section 508 of the Rehabilitation Act of 1973.

A maximum of seven (7) Community Experts will be selected from the applicant pool. Applicants must have at least one year of experience working with Python and/or data science, preferably in a library environment. Applicants must fill out all fields in this application, and submit it, to be considered as a Community Expert for this course. All applications must be submitted by Sunday, December 1, 2024 at 11:59 p.m. Eastern Time to be considered. Those selected will receive compensation of $1000 at the successful conclusion of their course responsibilities. Applicants will be evaluated by staff from the NNLM National Center for Data Services based on the three criteria: 1) experience with data services, particularly data education; 2) experience with mentoring; 3) expressed commitment
to course responsibilities.

Time commitment for this is estimated to be 10-15 hours, with the following responsibilities:

Engage in the following with a group of around 6 students during the course (1/6/25–3/21/25):

• Be available to meet with the course director before the class starts and after the class ends (1-hour meetings)
• Introduce yourself to your group in the first week of the course
• Provide weekly support for your group through online meetings and answering learner questions
• Review and grade your group members’ final projects, and provide positive and constructive feedback (grading is based on a rubric provided by the course director)
• Be available to interact with students via class discussion boards, online meetings, and messaging programs (such as Slack)

NIH Acknowledgement

Any work resulting from your role in this course must include an acknowledgement of NIH support and a disclaimer stating the following:

"Developed resources reported in this [publications, press releases, internet sites] are supported by federal funds from the National Library of Medicine, National Institutes of Health, Department of Health and Human Services, under Cooperative Agreement Number UG4LM012347 with NYU Langone Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health."

NIH Public Access Policy

Recipients of NNLM funding are required to deposit any peer-reviewed manuscript upon acceptance for publication in PubMed Central in accordance with the NIH Public Access Policy.

Publication and Copyrighting

Per Section 8.2.1. — Right in Data (Publication and Copyrighting) of the NIH Grants Policy Statement. The NIH must be given a royalty-free, nonexclusive, and irrevocable license for the Federal government to reproduce, publish, or otherwise use any materials developed as a result of funding and to authorize others to do so for Federal purposes, i.e. the ongoing development of the Network of the National Library of Medicine. Data developed by consultants are
also subject to this policy.