Research Awards/Grants (Past)

Matthew Lease

Micron Technology Inc.

08/01/2019 to 07/31/2022

The award is $150,000 over the project period. 

Tackling Misinformation through Socially-Responsible AI

While the broad goals of socially responsible artificial intelligence (AI) appear clear in the abstract, how can we translate such goals into practice for a real problem facing our society today? We consider the following challenge: How can we design responsible AI technologies to curb the digital spread of misinformation? 

Exploring real use cases and interface designs, we develop prototype AI applications and user-centered evaluations to remedy situations in which misinformation circulates online.

Matthew Lease

Daniel Stanzione, William Barth, Niall Gaffney, Tommy Minyard, and Paul Navratil 

National Science Foundation (NSF)

06/01/2016 to 03/31/2024

The collaborative award is $30,000,000 over the project period. The School of Information portion of the award is $172,281. 

Stampede 2: The Next Generation of Petascale Computing for Science and Engineering

The Texas Advanced Computing Center (TACC) at the University of Texas at Austin will acquire and deploy Stampede 2, a new, nearly 20 petaflop High Performance Computing (HPC) system. This system will be available to and accessed by thousands of researchers across the country. It will enable new computational and data-driven scientific and engineering, research and educational discoveries and advances. As a national resource, Stampede 2 will replace and surpass the current highly successful Stampede system. The new system will deliver over twice the overall performance as the current system in many dimensions most important to scientific computing, including computing capability, storage capacity, and network bandwidth. TACC and its academic partners will team with Dell, Inc. and Intel Corp. to procure and provide this system. 

HPC is intrinsic to discovery across the science and engineering disciplines served by the NSF. This resource allows researchers to explore those scientific and engineer frontiers that require very large scale computations not otherwise possible. Over the life of Stampede 2, the system is expected to serve many thousands of researchers spanning all NSF-supported disciplines, as the current system has done. In addition to being an immediately productive resource for a large community of computational engineers and scientists, Stampede 2 will also continue the community on an evolutionary path to future "many core" computing technologies. 

Stampede 2 will employ upcoming generations of Intel's Xeon and Xeon Phi processors, as well as the Intel Omni-Path network fabric. The system will maintain a familiar Linux-based software environment to insure a smooth migration of the large existing user base to the new system. The system and its software stack will be designed to support traditional large scale simulation users, users performing data intensive computations, as well as emerging classes of new and non-traditional users to high performance computing. Stampede 2 will support breakthrough discoveries and advances across a wide range of research topics.

Soo Young Rieh

Dania Bilal (University of Tennessee, Knoxville) and Clara M. Chu (University of Illinois at Urbana-Champaign) 

Institute of Museum & Library Services (IMLS)

09/01/2020 to 08/31/2023

The award is $208,142 over the project period.

IDEA (Innovation, Disruption, Enquiry, Access) Institute on Artificial Intelligence

The University of Tennessee at Knoxville; The University of Illinois, Urbana-Champaign; and the University of Texas, Austin are collaborating on the IDEA (Innovation, Disruption, Enquiry, Access) Institute on Artificial Intelligence (AI). This institute will address a gap in education and training for AI leaders in the library and information field through a one-week intensive, interactive, evidence-based, and applications-oriented professional development program for library and information professionals. The Institute will create two cohorts of leaders in knowledge and skills in AI to evaluate and implement in library and information environments. The curriculum will incorporate conceptual, technical, social, and applied aspects, including ethical issues of AI. The project will have national impact by sparking future innovation, collaboration, and dissemination of AI in library and information environments. It is supported by the ALA Center for the Future of Libraries and sustained through the Association of Information Science and Technology.

Amelia Acker

National Science Foundation (NSF)

10/01/2020 to 01/31/2024

$461,085 was awarded over the project period. Of the total funding, $303,031 was awarded to UT Austin iSchool.

Collaborative Research: Data Afterlives: The long-term impact of NSF Data Management Plans on data archiving and sharing for increased access

In 2011, the National Science Foundation began requiring that all funded projects provide data management plans (DMPs) to ensure that project data, computer codes, and methodological procedures were available to other scientists for future use. However, the extent to which these data management requirements have resulted in more and better use of project data remains an open question. This project thus investigates the National Science Foundation's DMP mandate as a national science policy and examines the broad impacts of this policy across a strategic sample of five disciplines funded by the National Science Foundation. It considers the organization and structure of DMPs across fields, the institutions involved in data sharing, data preservation practices, the extent to which DMPs enable others to use secondary project data, and the kinds of data governance and preservation practices that ensure that data are sustained and accessible. Systematic investigation of the impact of DMPs and data sharing cultures across fields will assist funding agencies and research scientists working to produce reproducible and open science by identifying barriers to data archiving, sharing, and access. The principal investigators will use project findings to develop data governance guidelines for information professionals working with scientific data and to articulate best practices for scientific communities using DMPs for data management.  
 
This project aims to enhance understanding of the role data management plans (DMPs) play in shaping data life-cycles. It does so by examining DMPs across five fields funded by the National Science Foundation to understand data practices, archiving and access issues, the infrastructures that support data sharing and reuse, and the extent to which project data are later used by other researchers. In phase I, the investigators will gather a strategic sample of DMPs representing a wide range of data types and data retention practices from different scientific fields. Phase II consists of forensic data analysis of a subset of DMPs to discover what has become of project data. Phase III develops detailed case studies of research project data life-cycles and data afterlives with qualitative interviews and archival documentary analysis to help develop best practices for sustainable data preservation, access, and sharing. Phase IV will translate findings into data governance recommendations for stakeholders. The project thus contributes to research about contemporary studies of scientific data production and circulation while assessing the effect of DMPs as a national science policy initiative affecting data management practices in different scientific communities. The comparative research design and mixed methods enables theory building about cross-disciplinary data practices and data cultures across fields and advances knowledge within data studies, information management studies, and science and technology studies.

Amelia Acker

Institute of Museum and Library Services (IMLS)

06/01/2018 to 01/31/2024

 The collaborative award is $199,811 over the project period. The School of Information portion of the award is $38,932.

Investigating Platform Development for Mobile and Social Media Data Preservation

The information we generate on social media sites and in mobile device apps represents the fastest form of data creation and collection in the United States. However, these data traces are complicated to work with because they are varied, inter-dependent, and vulnerable to loss. In this Early Career Development project, Dr. Amelia Acker at the University of Texas at Austin, will conduct a three-year, qualitative investigation into the activities of engineers and designers at five institutions where social media software is being developed. This project to better understand developer cultures will aid archives, libraries, and museums as they develop and implement best practices for gathering and preserving social media collections.