Abstract
This application requests R13 funding support to the National Big Data Health Science Conferences at University
of South Carolina (USC) for five years (2024-2028). This conference is a signature event of the USC Big Data
Health Science Center (BDHSC). BDHSC is an intramurally funded interdisciplinary enterprise established in
April 2019 that promotes and supports Big Data health science research at USC and across the state through
capacity development, academic training, professional development, community engagement, and
methodological advancement. Building on our successful experience with 4 intramurally-supported conferences
(2020-2023), the overall goal of this R13 is to stimulate further advancements in Big Data health science research
through rich interdisciplinary and multidisciplinary collaboration. Consistent with its overarching goal, the
conference will: (1) create a multidisciplinary scientific venue for the exchange of new concepts, methods, and
results to encourage the sharing of theoretical, methodological, and substantive knowledge from Big Data health
science research; (2) identify new issues that are, to date, understudied in this area, and then generate, promote,
and support innovation in BDHS; (3) expand impact and scholarly excellence by producing new and
interdisciplinary publications; and (4) promote inclusive excellence in training and mentoring opportunities by
engaging and supporting underrepresented junior investigators and students in the conference. This proposed
conference aligns with the objectives of the NIH-Wide Strategic Plan for FY 2021-2025 as well as the mission of
the Office of Data Science Strategy, National Library of Medicine, and other NIH Institutes, Centers, and Officers.
The 5-year Big Data Health Science conference series will contribute to NIH’s five pillars described in its Strategic
Plan for Data Science - support a highly efficient and effective data infrastructure; promote modernization of the
data-resources ecosystem; support development and dissemination of advanced data management, analytics,
and visualization tools; enhance workforce development for biomedical data science; and enact appropriate
policies to promote stewardship and sustainability.