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SAGE3: Smart Amplified Group Environment for Harnessing the Data Revolution
Researchers: Andrew Burks, Andrew Johnson, Ashwini Naik, Eseroghene Omene, Krishna Bharadwaj, Lance Long, Luc Renambot, Maxine Brown, Oli Kosiacki
UIC PI: Andrew Johnson, co-PI: Luc Renambot University of Hawaii Manoa PI: Jason Leigh Virginia Polytechnic PI: Chirstopher North NSF Award Number: 2003800 Award Period of Performance: 05/15/2020 - 04/30/2025 Total Amount Obligated: $2,250,000 The Big Data revolution necessitates the use of sophisticated tools such as Artificial Intelligence (AI) and Data Visualization to harness the sheer volume, velocity and variety of datasets that are becoming the norm. However, it is the research community that must make sense of the data being amassed, so cyberinfrastructure must extend to people. SAGE3 (Smart Amplified Group Environment) puts the “human in the loop” by providing scientists with an intuitive framework that integrates state-of-the-art AI technologies with applications, workflows, smart visualizations and collaboration services to help them access, share, explore and analyze their data, come to conclusions, and make decisions with greater speed, accuracy, comprehension and confidence. SAGE3 builds upon the NSF-funded first-generation SAGE (Scalable Adaptive Graphics Environment) and second-generation SAGE2 (Scalable Amplified Group Environment), which are today’s de facto operating systems to manage Big Data on tiled display walls. Its development focuses on two fundamental components: AI-enhanced “smart” services and advanced computing resource orchestration to support reproducible work models for secure collaborative work. SAGE3 amplifies user productivity, providing them with commercially available and open-source AI solutions, which autonomously and transparently analyze data while continually learning and improving through user interactions. SAGE3 makes AI technologies broadly accessible, not just a privilege for the technically savvy. SAGE3 further democratizes AI by using Data Visualization to help interpret and explain AI models so users better understand how AI came to its decisions, which engenders user trust and can help identify potentially prejudiced or biased models. SAGE3 augments every step of the scientific discovery enterprise - from quickly summarizing large data, to finding trends and similarities or anomalies among one or more linked datasets, to communicating findings to scientists, public policy and government officials, and the general public, to educating the next-generation workforce. Ultimately, it is the scientists and future scientists who must Harness the Big Data revolution to solve the nation’s grand challenge problems that will benefit society as a whole - from studying the diversity of life on Earth, to understanding the Earth and its systems from satellite imagery of its poles, to developing response scenarios for natural disasters such as landslides and pandemics that impact the citizens and economies of the world. View a video of SAGE3 being demonstrated on EVL’s YouTube channel. Date: May 15, 2020 - April 30, 2025 |
