TY - GEN
T1 - Automation and Collaboration in Complex Epidemiological Workflows with OSPREY
AU - Ozik, Jonathan
AU - Collier, Nicholson
AU - Fadikar, Arindam
AU - Wozniak, Justin
AU - Hayot-Sasson, Valerie
AU - Conroy, Kyle
AU - Chard, Kyle
AU - Wentz, Jacqueline
AU - Acquesta, Erin
AU - Ray, Jaideep
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s).
PY - 2025/12/20
Y1 - 2025/12/20
N2 - Epidemiological modeling, a powerful tool for supporting decision-making during a pandemic, is a workflow problem that incorporates data management of real-time data streams, large-scale simulation and analysis, and complex software integrations. The Open Science Platform for Robust Epidemic Analysis (OSPREY) was introduced to address critical gaps in this challenging scientific application. This paper explores the capabilities of OSPREY regarding data ingestion, curation, and management, and the development of a Shared Development Environment (SDE) for rapid collaboration. We present two use cases to demonstrate the implementation and impact of each of these goals. The first use case highlights real-time data ingestion and curation for epidemiologic modeling, while the second focuses on developing efficient global sensitivity analyses for epidemic models. These advancements aim to enhance OSPREY's capabilities for supporting public health decision-making and reproducible science.
AB - Epidemiological modeling, a powerful tool for supporting decision-making during a pandemic, is a workflow problem that incorporates data management of real-time data streams, large-scale simulation and analysis, and complex software integrations. The Open Science Platform for Robust Epidemic Analysis (OSPREY) was introduced to address critical gaps in this challenging scientific application. This paper explores the capabilities of OSPREY regarding data ingestion, curation, and management, and the development of a Shared Development Environment (SDE) for rapid collaboration. We present two use cases to demonstrate the implementation and impact of each of these goals. The first use case highlights real-time data ingestion and curation for epidemiologic modeling, while the second focuses on developing efficient global sensitivity analyses for epidemic models. These advancements aim to enhance OSPREY's capabilities for supporting public health decision-making and reproducible science.
KW - HPC workflows
KW - automation
KW - epidemiological modeling
KW - model exploration
UR - https://www.scopus.com/pages/publications/105026443560
U2 - 10.1145/3750720.3757294
DO - 10.1145/3750720.3757294
M3 - Contribution to conference proceedings
AN - SCOPUS:105026443560
T3 - 54th International Conference on Parallel Processing, ICPP 2025 - Workshops Proceedings
SP - 159
EP - 166
BT - 54th International Conference on Parallel Processing, ICPP 2025 - Workshops Proceedings
PB - Association for Computing Machinery, Inc
T2 - 54th International Conference on Parallel Processing Workshop, ICPP 2025
Y2 - 8 September 2025 through 11 September 2025
ER -