Women in Data Science: Jennie Larkin, Ph.D.

Jennie Larkin, Ph.D. 
Deputy Director
Division of Neuroscience, National Institute on Aging

Co-leads the FAIR Data Repositories Team, which ran the one-year NIH Figshare Instance pilot

Data science and data policy, better together:
Open science and effective data sharing rely on advances in data science (to create new and better ways to advance science) paired with updated data policy (to ensure that expectations and incentives align). Bridging the data science and data policy realms helps ensure a coordinated response at NIH and helps biomedical culture better recognize and reward data science innovators.

Engage and embed data science in different programs:
Ask questions, learn, and engage. We need more bright people who can bring new perspectives, expertise, and energy to data science and embed data science in different research programs.

Working with the community to address the COVID-19 pandemic:
NIH’s greatest data science accomplishment this year is how it has addressed the COVID-19 pandemic with a breadth and depth of data science to highlight resources and approaches to address the pandemic. The increasing breadth and depth of data science expertise across NIH and the larger biomedical enterprise has allowed us to rapidly accomplish much more than was possible just a few years ago. The willingness of the community also highlights the best of our community, coming together to meet the challenge of the COVID-19 pandemic.

What's a fun fact about you?
I train my dogs (a Canaan Dog and two Papillons) as a hobby, and we have earned invitations to multiple national events in obedience and agility.

Dr. Larkin holds a Ph.D. in biological sciences. She was featured in a blog post titled "Women in Tech at NIH: Togetherness Enables Transformation" guest authored by ODSS Director Dr. Susan Gregurick for the NLM's Musings from the Mezzanine in September 2020 and a lecture Gregurick delivered in March 2021 titled "Women Leading the Way: Stories of the Women (and Men) Making an Impact on Data Science at NIH."

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This page last reviewed on March 19, 2021