May 15th, 2020 - April 30th, 2025
Categories: Data Mining, Software, User Groups, Tele-Collaboration, Remote Collaboration, Deep Learning, Machine Learning, Cybersecurity, Data Science
Maxine Brown (UIC PI), Andrew Johnson (UIC co-PI), Luc Renambot (UIC co-PI)
Jason Leigh (University of Hawaii Manoa PI)
Christopher North (Virginia Polytechnic PI)
NSF Award Number: 2003800
Award Period of Performance: 05/15/2020 - 04/30/2025
Total Amount Obligated: $2,250,000
UIC Computer Science Electronic Visualization Lab (EVL) Director Maxine Brown, PI, co-PIs UIC CS Professor Andy Johnson and UIC CS Research Associate Professor Luc Renambot, and Senior Personnel EVL Senior Research Programmer Lance Long are awarded a $2.25 million dollar National Science Foundation grant entitled “Collaborative Research: CSSI Frameworks: SAGE3: Smart Amplified Group Environment for Harnessing the Data Revolution.” The grant runs from May 2020 to April 2025. It’s part of an overall $5 million project, that also includes a team from University of Hawaii Manoa led by Jason Leigh and a team from Virginia Polytechnic led by Christopher North.
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.