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LandScan Global depicts population distribution estimates across the planet. The darker orange and red colors above indicate higher population density. Credit: ORNL, U.S. Dept. of Energy

It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.

ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.

ORNL Corporate Research Fellow and Geospatial Science and Human Security Division Director Budhu Bhaduri has been elected as a fellow of the American Association of Geographers. The honor recognizes Bhaduri for his “innovation, mentorship and wide-ranging leadership” in geographic sciences. Credit: ORNL, U.S. Dept. of Energy

ORNL’s Budhendra “Budhu” Bhaduri has been elected a fellow of the American Association of Geographers. The honor recognizes Bhaduri as “a world leader in innovation, development and application of research in human dynamics, geographic data science, remote sensing and scalable geocomputation.”

By studying the activity patterns of populations around the world, scientists at ORNL are identifying the communities that are most likely to face extreme climate events and associated national security challenges. Credit: Erik Schmidt/ORNL, U.S. Dept. of Energy

Using novel data sets and computing systems, researchers at ORNL are simulating how climate change affects the safety and security of the country. 

Watermarks, considered the most efficient mechanisms for tracking how complete streaming data processing is, allow new tasks to be processed immediately after prior tasks are completed. Image Credit: Nathan Armistead, ORNL

A team of collaborators from ORNL, Google Inc., Snowflake Inc. and Ververica GmbH has tested a computing concept that could help speed up real-time processing of data that stream on mobile and other electronic devices.

The CrossVis application includes a parallel coordinates plot (left), a tiled image view (right) and other interactive data views. Credit: Chad Steed/Oak Ridge National Laboratory, U.S. Dept. of Energy

From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.

Johannesburg, South Africa 2

Geospatial scientists at Oak Ridge National Laboratory analyzed three cities of varying infrastructures to look for patterns of electricity use and locate “dark spots” where informal neighborhoods may lack access to power.

As part of a preliminary study, ORNL scientists used critical location data collected from Twitter to map the location of certain power outages across the United States.

Gleaning valuable data from social platforms such as Twitter—particularly to map out critical location information during emergencies— has become more effective and efficient thanks to Oak Ridge National Laboratory.