Description:

Proliferation of scientific data collection will continue as a significant increase in the number of sensors and satellites collect increasing volumes of data to be processed over the next 25 years. The increased complexity of the data requires higher agility in data processing infrastructure to gain insights at reduced costs, including rapid adoption of new technologies like scalable Cloud infrastructure, artificial intelligence (AI) and machine learning (ML), and deep learning (DL). To successfully exploit insights, the rapid application of IT engineering techniques and open-source tools in combination with a demonstrated understanding of secure, open data and open science constructs that enable scientific collaboration, engagement and innovation will be key. This session will explore modern technologies and frameworks that support data ingestion and dissemination, including: 

• Cloud-agnostic, secure infrastructure frameworks that demonstrate scalability for data ingestion and algorithm processing for data product generation 
• Cloud-based scientific collaboration and algorithm development solutions and tools to accelerate Research to Operations for data products 
• Technology solutions, governance policies, and public relations strategies that increase accessibility to scientific data and products in the Cloud