North America

In April 2024, Jefferson Lab streamed and processed raw physics data in real time over 3,000 miles at 100 gigabits per second—a breakthrough for big-data science.

In a virtual exercise, the Energy Sciences Network (ESnet) and partners demonstrated that large-scale renewable energy sources can be introduced into the US energy system without interruptions in power supply.

Seismic data from the Yellowstone national park is turned into music performed live at the 2023 Internet2 Community Exchange

A US collaboration with participation from NREN ESnet has developed a new way to study the structure of molecules.

US researchers were able to simulate an energy system where operators hundreds of kilometers apart work together just like they were sitting side by side in a simulation.

Link Oregon, is partnering with Oregon tribes, along with the Network Startup Resource Center (NSRC), the University of Oregon (UO), and Oregon State University (OSU), to improve internet connectivity for tribal communities in Oregon.

What began as a casual conversation about the importance of libraries being able to provide their communities with reliable, high-speed internet access evolved into a major project.

For the scientists and researchers linked to the Pacific Research Platform, the conduct of science was already at the desk and important discovery and knowledge continued uninterrupted during COVID-19.

Australia, Canada, UK and US collaborate on an automated platform to share intelligence on malware attacks

The collapse of the famous Arecibo Observatory Radio Telescope, Puerto Rico, at December 1, 2020, was a great loss for science. Still, things could have been a lot worse...

Supported by CENIC's 400-gigabit research network, the Pacific Research Platform has not only enabled researchers at UC San Diego and their partners at the University of Haifa in Israel to go ahead with their archeological dig despite the COVID-19 pandemic but also drastically accelerated data analysis times.

The job of the brokers is to create tools and algorithms that allow the automated analysis of data from large scanning telescopes, in order to identify the most interesting astronomical objects.