Pioneering the future of computing research
The Renaissance Computing Institute (RENCI) is a research institute at UNC-Chapel Hill that focuses on data science for the greater good. We are a team of innovators, problem-solvers, and forward-thinking individuals from a diverse range of backgrounds, skill sets, and perspectives coming together to conduct groundbreaking research and enact positive change at the local, state, national, and international levels. Explore our various projects, research groups, collaborations, and operations teams to learn more about our work and the people who make it happen.
About RENCIA core project within the Department of Homeland Security’s Coastal Resilience Center at UNC-Chapel Hill, APSViz disseminates real-time coastal hazards information and enhances research productivity by making it much easier to understand computer simulations and predictions of coastal hazards. Learn more about APSViz.
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NC researchers come together to harness...
In an increasingly interconnected world, the integration of clinical and environmental health data holds immense potential for advancing research, improving patient outcomes, and shaping the future of healthcare. However, to truly make an impact on individuals and communities, institutional and scientific silos that hinder collaboration and resource
Blog
Coastal Hazard and Risk Modeling - Evacuation Modeling
To save lives, it is critical to know the best way to protect people in the path of a hurricane. While emergency managers use models to inform evacuation routes and timing, existing models are based primarily on “clearance time,” or ensuring that evacuees are on the roads for the shortest amount of time. The models do not take into account what populations are at most at risk, potential for injury or loss of life, or other social factors.
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ImPACT
Scientific progress today requires multi-institutional and cross-disciplinary sharing and analysis of data. Many disciplines, such as social and health-related sciences, face a web of policies and technological constraints on data due to privacy concerns over, for example, Personal Health Information (PHI) or Personally Identifiable Information (PII). Issues of privacy, safety, competition, and ownership have led to regulations controlling data location, availability, movement, and access. Compliance poses obstacles to traditional data-processing practices and slows research; yet, increasingly, pressing scientific and societal problems demand collaborative efforts involving data from multiple stakeholders.
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Data Matters short-course series returns in August 2023
Now in its tenth year, Data Matters, a week-long series of one and two-day courses aimed at students and professionals in business, research, and government, will take place August 7 – 11, 2023 virtually via Zoom. This short course series is sponsored by the Odum Institute for Research in Social Science at UNC-Chapel Hill, the National Consortium for Data Science, and RENCI.
Learn moreNews
NC researchers come together to harness...
In an increasingly interconnected world, the integration of clinical and environmental health data holds immense potential for advancing research, improving patient outcomes, and shaping the future of healthcare. However, to truly make an impact on individuals and communities, institutional and scientific silos that hinder collaboration and resource
Blog
Coastal Hazard and Risk Modeling - Evacuation Modeling
To save lives, it is critical to know the best way to protect people in the path of a hurricane. While emergency managers use models to inform evacuation routes and timing, existing models are based primarily on “clearance time,” or ensuring that evacuees are on the roads for the shortest amount of time. The models do not take into account what populations are at most at risk, potential for injury or loss of life, or other social factors.
Learn moreProjects
ImPACT
Scientific progress today requires multi-institutional and cross-disciplinary sharing and analysis of data. Many disciplines, such as social and health-related sciences, face a web of policies and technological constraints on data due to privacy concerns over, for example, Personal Health Information (PHI) or Personally Identifiable Information (PII). Issues of privacy, safety, competition, and ownership have led to regulations controlling data location, availability, movement, and access. Compliance poses obstacles to traditional data-processing practices and slows research; yet, increasingly, pressing scientific and societal problems demand collaborative efforts involving data from multiple stakeholders.
Learn moreNews
Data Matters short-course series returns in August 2023
Now in its tenth year, Data Matters, a week-long series of one and two-day courses aimed at students and professionals in business, research, and government, will take place August 7 – 11, 2023 virtually via Zoom. This short course series is sponsored by the Odum Institute for Research in Social Science at UNC-Chapel Hill, the National Consortium for Data Science, and RENCI.
Learn more
Leading innovation in diverse research fields
RENCI supports several research groups; centered around data science, each domain-specific group offers scientific and technical expertise to advance discovery within their field.
Clinical Informatics
Enhancing health sciences research and clinical practice through advanced data management and analysis, improving patient diagnoses and treatment outcomes. Learn more.
Data Science and Analytics
Transforming sectors like science and industry with big data tools and technologies for improved data access, sharing, analysis, and long-term archiving. Learn more.
Earth Data Science
Utilizing data management, high-performance computing, and visualization to model coastal impacts and support environmental data sharing and sustainability. Learn more.
Network Research and Infrastructure
Advancing high-performance computing and networking to facilitate seamless data access, sharing, and storage for global scientific collaboration Learn more.
Software Architecture
Creating scalable cloud computing data science platforms featuring full-text search, knowledge graphs and machine learning models. Learn more.
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20+ years of excellence
Founded in 2004, RENCI has demonstrated experience and driven innovation across a variety of projects and domains.
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Featured projects
Precision Medicine and PDS
PDS (formerly PDP), developed by RENCI’s Translational Science Team, enables actionable AI integration directly with electronic health records (EHR) and computational phenotyping, while also providing an open framework and API specification for easy integration of new, third-party clinical decision support models. This design will facilitate continuous precision medicine model improvement and validation. For example, this easy-to-use framework will enable integration of new precision dosing tools to facilitate incorporation of published PK/PD/PG models into clinical workflows, as is urgently needed for provision of truly personalized medicine. PDS will also empower the clinician with tools to fight current and future SARS epidemics; these tools include guidance computed from joint modeling of patient history, disease spread, and hospital capacity.
Data Translator CAM/AOP Knowledge Provider
The NCATS Biomedical Data Translator project applies semantic integration strategies to share chemical, genetic, phenotypic, disease, ontological, and other ‘knowledge sources’. Taken together, the >300 knowledge sources form an integrated data ecosystem and technology platform—the Translator system—to support clinical and translational science. RENCI contributes to three Translator Projects, including the Exposures Provider Service. The CAM/AOP Knowledge Provider is a subproject of the Exposures Provider which explores integration of Causal Activity Models (CAMs) into the Translator knowledge graph. CAMs are small knowledge graphs modeled using the OWL Web Ontology Language, pioneered by the Gene Ontology project. An OWL reasoner is used to augment the CAM knowledge graphs with contextual information provided by reference ontologies. The CAM/AOP knowledge provider includes a datasets of CAMs provided by the Gene Ontology and Reactome projects, and we are also exploring publication of Adverse Outcome Pathways (AOPs) using this approach.
BioData Catalyst
NHLBI BioData Catalyst is a cloud-based ecosystem providing tools, applications, and workflows in secure workspaces. By increasing access to NHLBI datasets and data analysis capabilities, BioData Catalyst accelerates biomedical research that drives discovery, leading to novel diagnostic tools, therapeutics and prevention strategies for heart, lung, blood, and sleep disorders.
DataBridge
DataBridge, a collaboration between RENCI and the School of Information and Library Science, develops tools and methods to extract and use knowledge from the millions of data sets created by thousands of scientists worldwide. The ability to discover and use these data sets across disciplines is one way to accelerate progress in science and engineering. DataBridge works as an interface similar to social networking sites that show relationships among data points and enables access to a wide range of research databases and links to data sets. Funded by the NSF, DataBridge received additional NSF support to build a DataBridge for neuroscience research under the title, “EAGER: Data Bridge for Neuroscience.”
PoSeiDon: Platform for Explainable Distributed Infrastructure
PoSeiDon aims to advance the knowledge of how simulation and machine learning (ML) methodologies can be harnessed and amplified to improve DOE’s computational and data science. PosEiDon will provide an integrated platform that helps facility operators and scientists improve the overall end-to-end science workflow by (1) predicting the performance of complex workflows; (2) detecting and classifying infrastructure and workflow anomalies and "explaining" the sources of these anomalies; and (3) suggesting performance optimizations.
Coastal Probabilistic Hazard Analysis (FEMA-BOA)
FEMA has recently conducted new coastal hazard and risk studies to support the mission and goals of the National Flood Insurance Program with new flood maps. These studies are costly and generate large volumes of model-generated data that capture the range of hurricane impacts for a region. The ADCIRC model has been used for all recent FEMA studies of this nature. Beyond the immediate use for mapping activities, these collections of model results can be used for other applications. The key to leveraging these data is to develop “surrogate models” that statistically represent the underlying model dynamics as best as possible, thus allowing for rapid statistical simulations of unmodeled events. This project will implement various surrogate modeling approaches using the flood insurance study for FEMA’s Region 3 (NC/VA border through the Delaware coast), which RENCI conducted. These data include time and spatially varying simulated waves, water levels, wind, atmospheric pressure, and currents, among other variables. These data could be useful for other efforts if they were more easily discoverable and accessible. The surrogate models will be developed and implemented by collaborators at the University of Notre Dame. RENCI will define and implement the needed cyberinfrastructure to make the data externally accessible through a geospatial database. The methods and approach will subsequently be used to develop similar databases for other regional FEMA coastal study datasets.
Distinct: A Distributed Multi-Loop Networked System for Wide-Area Control of Large Power Grids
Distinct aims to improve the robustness and reliability of electric power systems by creating a distributed multi-loop networked system for wide-area control of large power grids.
Forecasting Coastal Impacts from Tropical Cyclones along the US East and Gulf Coasts using the ADCIRC Prediction System
Over the past two decades ADCIRC (http://adcirc.org) has become one of, if not the most widely used community modeling platform for storm surge / coastal flooding predictions across academia, governmental agencies and the private sector. The ADCIRC Prediction System (APS) manages ADCIRC on HPC resources for real-time computation of coastal hazards. This project is expanding the existing APS to incorporate new forcing mechanisms and models (NOAA’s new WaveWatch3, COAMPS-Tropical Cyclone forcing, and XBeach) and new features such as coastal erosion and sediment transport and damage assessment tools.
CCMNet
Cyberinfrastructure (CI) has become ubiquitous in science and engineering research, partly due to the unprecedented acceleration and availability of high-performance computing (HPC) capabilities enabling many breakthrough discoveries. To advance scientific discovery, many researchers are faced with transitioning their work from local machines or departmental servers to large-scale CI, which requires developing new technical skills. Research computing facilitators, research software engineers, and other CI professionals (CIP) are an essential workforce needed to advise researchers on how to reshape the way they perform research, optimize workflows, educate and assist in the use of new technologies, and serve as information resources. However, it is a challenge for this community to keep abreast of the extensive array of tools, techniques, and specialized approaches needed to pursue today’s complex research questions. The CIP community relies on peer-to-peer knowledge sharing; this valuable knowledge is widely dispersed and difficult to find. A strong, collaborative mentor network is critical to successfully sustaining and advancing the CIP workforce to meet future scientific challenges. The Connect.Cl-based Community-wide Mentorship Network (CCMNet) is developing this network of subject matter experts from across the country, leveraging the Connect.Cl portal as the network's central coordination hub. Through these efforts, CCMNet is strengthening researchers’ and CIPs’ confidence in their abilities, enabling the exploration of new questions, and facilitating more rapid scientific discoveries and advancements. The CCMNet program is building a mentor network that spans the broader CIP community by (a) developing a portal for making connections and exchanging knowledge, (b) forming partnerships with other mentor-centric programs in the community to advance support for all CIPs, (c) reaching out to under-served groups to create a more inclusive and diverse CIP community, and (d) developing best practices and guidance on mentorship for the benefit of the entire community. These efforts bring novel structure and consistency to the development of the CIP workforce, enabling a more advanced CIP workforce better able to support today’s research needs, as well as anticipate future needs.
GeneScreen
GeneScreen is a screening program that aims to equip primary care clinics to detect medically actionable genetic mutations in their patients. By altering individuals and their healthcare providers to rare genetic mutations, the program can help care providers treat or even prevent diseases associated with these mutations.
Recent articles
NC researchers reconvene for second Clinical and Environmental Health Data workshop
On Friday, February 23, 2024, RENCI hosted the second workshop in a series on Clinical and Environmental Health Data, themed “Integrating Exposures Data into Clinical Data Assets: Building a Regional Center of Excellence.” The inaugural workshop, themed “Clinical and Environmental Health Data Workshop Series – Exploration,” was also hosted by RENCI in May 2023. The workshop series is being jointly led by experts in clinical and environmental health data and cyberinfrastructure at RENCI, US EPA,
UNC Advances Hurricane-driven Flood Prediction Capabilities for Coastal Communities
On September 14, 2018, Hurricane Florence made landfall in the Wrightsville Beach area of coastal North Carolina. While the storm was a category 1, it caused catastrophic flooding throughout much of the state. The record amount of rain from the system combined with an already saturated soil. Rivers overflowed their banks, storm surge inundated coastal areas, and the water had nowhere to go. It was a rare compound flooding scenario that will be studied and remembered for a long time. It is diffi
IT4Innovations National Supercomputing Center joins the iRODS Consortium
IT4Innovations National Supercomputing Center at VSB – Technical University of Ostrava, which is based in the Czech Republic, has become the newest member of the iRODS Consortium. The consortium brings together businesses, research organizations, universities, and government agencies from around the world to ensure the sustainability of the iRODS software as a solution for distributed storage, transfer, and management of data. Members work with the consortium to guide further development and inn
Exploring the power of distributed intelligence for resilient scientific workflows
Future computational workflows will span distributed research infrastructures that include multiple instruments, resources, and facilities to support and accelerate scientific discovery. However, the diversity and distributed nature of these resources makes harnessing their full potential difficult. To address this challenge, a team of researchers from the University of Southern California (USC), the Renaissance Computing Institute (RENCI) at the University of North Carolina, and Oak Ridge, Lawr
RENCI to showcase latest technological innovations at SC23
Every sector of society is undergoing a historic transformation driven by big data. RENCI is committed to transforming data into discoveries by partnering with leading universities, government, and the private sector to create tools and technologies that facilitate data access, sharing, analysis, management, and archiving. Each year, the Supercomputing conference provides the leading technical program for professionals and students in the HPC community, as measured by impact, at the highest aca
RENCI awarded NSF grant to develop cyberinfrastructure training program for X-ray scientists
RENCI scientists and collaborators from Cornell University and University of Southern California (USC) have been awarded a $1 million, three-year grant from the National Science Foundation (NSF) to develop an innovative training program for scientists who use the Cornell High Energy Synchrotron Source (CHESS) X-ray facility. The program will be designed to help the scientists increase their computing skills, awareness and literacy with an ultimate goal of accelerating scientific innovations in s
NSF FABRIC project announces groundbreaking high-speed network infrastructure expansion
The NSF-funded FABRIC project has completed installation of a unique network infrastructure connection, called the TeraCore—a ring spanning the continental U.S.—which boasts data transmission speeds of 1.2 Terabits per second (Tbps), or one trillion bits per second. FABRIC previously established preeminence with its cross-continental infrastructure, but the project has now hit another milestone as the only testbed capable of transmitting data at these speeds—the highest being twelve times faster
ChatGPT used to streamline medical record analysis in EduHeLx
In the past few months, ChatGPT has risen from relative obscurity to a newsworthy technology for its revolutionary artificial intelligence (AI) capabilities. The natural language processing chatbot was developed by OpenAI and is built on top of families of large language models. This approach enables ChatGPT to return related search results by reasoning over interconnected knowledge networks across these language models, rendering it the most advanced AI chatbot to date. ChatGPT’s innovative AI
Data Matters short-course series returns in August 2023
Now in its tenth year, Data Matters, a week-long series of one and two-day courses aimed at students and professionals in business, research, and government, will take place August 7 – 11, 2023 virtually via Zoom. This short course series is sponsored by the Odum Institute for Research in Social Science at UNC-Chapel Hill, the National Consortium for Data Science, and RENCI. In recent years, employers’ expectations for a data literate workforce have grown significantly. According to a 2022 Forr
What to expect at the iRODS 2023 User Group Meeting
The worldwide iRODS community will gather in Chapel Hill, NC from June 13 – 16 Members of the iRODS user community will meet at UNC-Chapel Hill in North Carolina for the 15th Annual iRODS User Group Meeting to participate in four days of learning, sharing use cases, and discussing new capabilities that have been added to iRODS in the last year. The event, sponsored by RENCI, Omnibond, Globus, and Hays, will provide in-person and virtual options for attendance. An audience of over 100 participan
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