Renaissance Computing Institute

Responding to feedback from state, tribal, local, and territorial (STLT) partners, the purpose of this specific project is to increase the relevance and utility of modeling outputs to STLTs and other consumers of infectious disease forecasts and scenario projections. Feedback from STLT partners has shown that many feel ill-served by the current “one size fits all” approach to presenting the results of ensemble based projections produced by modeling hubs. In particular, scenario projections contain a lot of information that has been highlighted as particular interest to STLT partners (e.g., peak timing and size, likelihood of overwhelming current healthcare capacity), but this information is not highlighted or easily obtained from current displays on hub websites and in reports.

ROBOKOP (Reasoning Over Biomedical Objects linked in Knowledge-Oriented Pathways) is a biomedical question-answering system based on a knowledge graph, meaning that it expresses data as a collection of nodes—such as genes and diseases—and edges that represent the relationships between the nodes. ROBOKOP uses multiple open biomedical databases to explore links between various biomedical data types and utilizes the BIOLINK model to express those data types. For example, it can be used to examine connections between a disease and a drug and then explore which genes might be involved in that relationship. ROBOKOP’s publicly accessible user interface (UI) allows users to address both relatively simple questions such as “what genes are associated with drug-induced liver injury?” and more complex ones such as “what drugs could be used to treat airborne pollutant–induced asthma exacerbations in patients who are non-responsive to traditional medications?”

Data Matters™ is a week-long series of one and two-day courses aimed at students and professionals in business, research, and government. The short course series gives students the chance to learn about a wide range of topics in data science, analytics, visualization, curation, and more from expert instructors.

Aerial Experimentation Research Platform for Advanced Wireless (AERPAW) is a $24 million grant awarded by the National Science Foundation to develop an advanced wireless research platform, led by North Carolina State University, in partnership with Wireless Research Center of North Carolina, Mississippi State University and Renaissance Computing Institute (RENCI) at the University of North Carolina at Chapel Hill; additional partners include Town of Cary, City of Raleigh, North Carolina Department of Transportation, Purdue University, University of South Carolina, and many other academic, industry and municipal partners. AERPAW, the nation’s first aerial wireless experimentation platform spanning 5G technologies and beyond, will enable cutting-edge research — with the potential to create transformative wireless advances for aerial systems.