Many complex problems cannot be addressed easily from the confines of individual disciplines because they require participation of many experts, each viewing the problem from their distinctive disciplinary perspective, and collaborations around shared data and knowledge. When interdisciplinary efforts involve massive amounts of different types of data, an invaluable approach to understand and analyze data is data visualization. The University of Texas at El Paso (UTEP) is acquiring high resolution, collaborative visualization instrumentation that will be housed in the newly constructed Interdisciplinary Research Building. The instrumentation will be a vital resource for UTEP’s established efforts in convergence research across science and engineering, e.g., through the NSF-funded CREST CyberShARE Center of Excellence and “Innovation through Institutional Integration†initiative. The research impacted by the acquired instrumentation will contribute to NSF’s Big 10 ideas in quantum computing, data revolution, convergence research, and INCLUDES. The expected outcome is increased research productivity resulting from insights afforded by the integration and manipulation of visualizations and examination of multiple perspectives. As such, the visualization instrumentation can contribute to advancement of our nation’s research capabilities in quantum computing and data analytics, as well as areas that are particularly relevant to border regions and in topical areas relevant to a region with a large under-served population (e.g., health and the environment, energy-water issues, and border security), and other areas such as cybersecurity and national defense. The instrumentation will also elevate the education and training of student researchers, in particular Latinx students who comprise 80% of UTEP’s student population, in areas of national need. Research students and those involved in training and associated coursework will graduate with domain expertise and knowledge in interpreting, managing, and visualizing data; experience in working in interdisciplinary teams; and an ability to use state-of-the-art visualization methods to advance discovery and generate new knowledge. PI Gates directs the NSF-funded Computing Alliance of Hispanic-Serving Institutions (CAHSI), the only INCLUDES Alliance focused on achieving parity in representation of Hispanics in computing. The Alliance will be instrumental in disseminating and involving other HSIs in education and research training efforts and facilitating partnerships to build research capacity. The visualization instrumentation also will be an important asset for the community, in particular those impacted by UTEP’s research, and for outreach efforts in exciting middle- and high-school students about studying STEM through engagement in visualization activities.
The comprehensive research instrumentation is composed of integrated subsystems and a visualization wall composed of ultra-high-definition displays with an overall resolution of 124 megapixels that will enable viewing data at unprecedented levels of detail, and, as a result, will support analysis and discovery of new insights from various types of data (structured and unstructured, heterogeneous, and data with varying levels of quality). The windowing subsystem will allow researchers to input and analyze multiple datasets running simultaneously and provide the ability to compare datasets side-by-side in real time while a video conferencing subsystem will support collaboration with remote stakeholders, policymakers, other academics, and political leaders. The instrumentation will create the infrastructure that bridges data, computation, and visualization to grow collaborations across the university and externally. In particular, the infrastructure will provide researchers with the ability to communicate disparate perspectives of information and knowledge; analyze large, integrated data sets; manipulate multi-dimensional models of phenomena (e.g., geological structures, molecules, and advanced material engineering); view simulation models that holistically combine both social and natural system components; view data and models that are useful and usable by stakeholders who may or may not be technically savvy; and support a purposeful participatory research process that facilitates collaborative reasoning among researchers and stakeholders, enabling convergence from different perspectives. With UTEP’s expertise in machine learning, semantic technologies, visualization, team science, and data analytics, researchers will have access to technologies and the requisite training needed to accelerate advances in their research. Indeed, diverse team efforts result in greater scientific impact, innovation, productivity, and reach because of the ability of members to draw on each other’s expertise.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
