University of South Carolina Big Data Health Science Conference

点击翻译按钮获取中文摘要

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.