lntegrated Platform for Multimodal Data Capture, Exploration and Discovery Driven by Al Tools
Description
This project will enable and accelerate scientific discovery by leveraging large complex multimodal datasets generated at BES user facilities, develop shared transferrable infrastructure to store, curate, analyze and disseminate the data. Additional
Detailed example
This project will enable and accelerate scientific discovery by leveraging large complex multimodal datasets generated at BES user facilities, develop shared transferrable infrastructure to store, curate, analyze and disseminate the data. Additionally, we will build data analysis tools that reveal correlations in multimodal data and apply Machine Learning (ML) methods and train artificial Intelligence (AI) models that efficiently extract synergistic physical information and embed such models in new workflows for rapid scientific discovery.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
This project will enable and accelerate scientific discovery by leveraging large complex multimodal datasets generated at BES user facilities, develop shared transferrable infrastructure to store, curate, analyze and disseminate the data. Additionally, we will build data analysis tools that reveal correlations in multimodal data and apply Machine Learning (ML) methods and train artificial Intelligence (AI) models that efficiently extract synergistic physical information and embed such models in new workflows for rapid scientific discovery.
Audit / financial statement impact
Does not meet definition
Controls / human review
ATO: Not reported; PIA: Not published