Genomic Science Program
U.S. Department of Energy | Office of Science | Biological and Environmental Research Program

2024 Abstracts

The Landscape of Data Infrastructure from the National Virtual Biosecurity for Bioenergy Crops Center Perspective

Authors:

Shanetenu Jha* ([email protected], PI), Martin Schoonen

Institutions:

Brookhaven National Laboratory

Abstract

Brookhaven National Laboratory was awarded a pilot project in FY22 under the DOE Office of Science Biopreparedness Research Virtual Environment (BRaVE) initiative to define research priorities, needs, and requirements for a national virtual center devoted to the biosecurity of bioenergy crops. The proposed center’s mission, the National Virtual Biosecurity for Bioenergy Crop Center (NVBBCC), would be to provide the scientific basis and tools to detect, characterize, model, and mitigate biothreats to bioenergy crops. This function will ensure increased U.S. reliance on essential plant-based energy products, e.g., biojet fuel, over the next few decades The NVBBCC is envisioned as a distributed, virtual center with multiple national laboratories at its core to maximize the use of existing unique facilities and expertise across the DOE complex. To underpin this collaborative and distributed effort, a flexible computational platform that supports high-performance computing workflows and data management and allows for efficiently conducting modeling simulations is needed.

This presentation outlines the computing infrastructure capabilities toward these goals, derived from a community requirements workshop:

• Develop an integrated research infrastructure that enables meaningful integration of data, computing, instrumentation, and related resources to allow researchers access to needed computational/data resources from anywhere.

• Employ robust data management systems that can manage diverse data types to ensure quality while adhering to FAIR (findability, accessibility, interoperability, and reusability) principles and supporting better metadata.

• Explore and adopt advanced technologies, such as 5G/6G wireless communication for high-throughput transmission with low latency in poorly connected areas.

• Develop scalable and generalizable models that link model design to downstream decision-making while using tools and techniques to create a unified, integrated modeling approach.