Operation of the Hub will include four primary tasks:
Enhance and integrate existing data services and establish cyberinfrastructure with a distributed architecture that links existing data facilities and services, including HydroShare, EarthChem, SESAR, OpenTopography, and eventually other systems via a central Hub that provides services for easy data submission, integrated data discovery and access, and computational resources for data analysis and visualization.
Support discovery through community synthesis activities and via access to community data and modeling cyberinfrastructure.
Broaden the CZ community through outreach and education activities.
Enhance collaboration among the CZ Thematic Clusters through coordination, sharing, community meetings, and outreach. The nine CZ Thematic Clusters across the US conducting basic research into the structure, function, and processes of the critical zone are:
CINet: Critical Interface Network in Intensively Managed Landscapes
The Coastal Critical Zone: Processes that transform landscapes and fluxes between land and sea
Bedrock controls on the deep critical zone, landscapes, and ecosystems
Dynamic Water Storage — Quantifying controls and feedbacks of dynamic storage on critical zone processes in western montane watersheds
Urban Critical Zone processes along the Piedmont-Coastal Plain transition
Patterns and controls of ecohydrology, CO2 fluxes, and nutrient availability in pedogenic carbonate-dominated dryland critical zones
Dust in the Critical Zone from the Great Basin to the Rocky Mountains
Using Big Data approaches to assess ecohydrological resilience across scales
Geomicrobiology and Biogeochemistry in the Critical Zone
RENCI’s role in the Hub will be to host the cyberinfrastructure for the CZ Hub data submission portal.
Led by the University of Massachusetts Amherst, scientists from RENCI, the Information Sciences Institute (ISI) at the University of Southern California (USC), and the University of Missouri, will collaborate on FlyNet, a project that will utilize edge, cloud, and in-network computing to generate crucial data that will help them address a variety of pressing issues presented by drones.
Sharing big data requires big networks. Systems like AtlanticWave-SDX, which connects networks in the U.S., Chile, Brazil, and South Africa, provide specialized infrastructure needed to send vast amounts of scientific data across long distances, helping scientists make the most of powerful data collections.
RENCI scientists contributed to the development of AtlanticWave-SDX, a distributed experimental software-defined exchange (SDX) that uses cutting-edge network technology to facilitate the exchange of data between research and education networks in the U.S. with networks on other continents.
As scientists around the world urgently work to understand the best ways to diagnose and treat COVID-19, quick and easy access to the latest research findings and rapid exploration of emerging data have become critical. RENCI scientists have developed new tools and approaches that can help researchers make important discoveries and answer key questions about COVID-19 in record time.
“These new approaches allow scientists to blend together novel observations and information from recent papers with previously known information that can be used to inform, contextualize, and test new COVID-19 information,” said Chris Bizon, director of analytics and data science at RENCI.
Data analysis and visualization are helping answer a variety of questions about COVID-19 such as who is most at risk, how is the disease spreading, and what approaches might work best for treatments. However, setting up a computer environment to analyze the large amounts of data needed to answer such questions is no easy task. It requires selecting data libraries, software, and hardware and estimating how much memory and computing power will be needed. This process is time consuming and few individuals have the complex skill set needed to accomplish it.
RENCI scientists have developed a new digital data science laboratory called Blackbalsam that can help significantly shorten the planning stage for these efforts with a standardized environment housing computational and data sets for COVID-19 analytics.
“As COVID-19 progressed, I saw that researchers were conducting analyses and visualization on an increasingly varied set of COVID-19 data,” said Blackbalsam co-author Steven Cox, assistant director of software systems architecture at RENCI. “I realized that it would be very helpful to have an environment that overcomes well-known technological and skill barriers by providing an interface that researchers with statistical, analytical, and visualization skills could use.”
When UNC students left for spring break on March 9, the COVID-19 public health crisis was just heating up. Soon after, UNC administrators made the decision to move to remote teaching and extended the break by a week to give instructors time to prepare. RENCI Deputy Director Ashok Krishnamurthy was one of many UNC professors who made the quick transition to teaching via video conferencing on Zoom.
What course were you teaching when you received notice that classes would all be moved online?
I was teaching a computer science course called Introduction to Scientific Programming that is designed for non-computer science majors. Most of the students take the class to learn programming skills for their day-to-day work or research. My section of the course had about 160 students enrolled.
How easily were you able to convert this class to a virtual format?
Fortunately, the course was relatively easy to adapt to virtual teaching. The UNC Computer Science department, and my colleague John Majikes who was teaching another section of the same course, have set up this course in such a way that taking it online was quite straightforward.
When COVID-19 cases began to appear across the country, many RENCI employees felt a call to action. While several took it upon themselves to develop new data science technologies or to adapt existing ones to process COVID-19 data, others have contributed to communities in need by creating face masks, assisting food banks, connecting researchers to projects, and supporting foster youth.
Creating Face Masks
Like many across the nation, some RENCI employees have started sewing face masks to donate to medical workers, neighbors, and people in need.
Due to the current COVID-19 situation, many previously scheduled in-person events are moving to virtual spaces. Events associated with RENCI projects and with consortium and partner institutions are making decisions daily about whether to postpone, transition to virtual, or potentially proceed in the late summer and fall. We will keep our events calendar updated, so check back regularly for announcements.
Two major events that have made the choice to transition to virtual are the FABRIC Community Workshop and the iRODS User Group Meeting. Although this change is unprecedented, both teams are adjusting their sessions to accommodate the virtual atmosphere and provide a memorable experience for attendees.
The past few weeks have presented unique challenges to how we work, how we enjoy ourselves, and how we live our everyday lives. We are all worried about the uncertainties and about how this will affect us and our loved ones in the coming weeks.
That being said, I am proud to work at RENCI and UNC-Chapel Hill, and blessed to be confronting the current challenges in a region where we are so fortunate to have skilled personnel and resources to bring to bear.
We can gather data and compute. We can volunteer. We can serve. We can encourage each other. We can broadcast. With relatively limited risk through working remotely, we can use our brains, our team spirit, our good will, our tools, and our machines to do science and serve.
Data Commons Pilot Phase teams plan how a rising tide of data and tools can float all research boats
Last November the National Institutes of Health announced $9 million in pilot funding to explore feasibility and best practices for a new approach to advancing biomedical research. The initiative, known as Data Commons, is focused on making digital objects—that is, the data, models, and analytical tools that constitute the engine behind the modern research enterprise—available through collaborative platforms.
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RENCI (Renaissance Computing Institute) develops and deploys advanced technologies to enable research discoveries and practical innovations. RENCI partners with researchers, government, and industry to engage and solve the problems that affect North Carolina, our nation, and the world. An institute of the University of North Carolina at Chapel Hill, RENCI was launched in 2004 as a collaboration involving UNC Chapel Hill, Duke University, and North Carolina State University.