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By NASA
6 min read
Smarter Searching: NASA AI Makes Science Data Easier to Find
Image snapshot taken from NASA Worldview of NASA’s Global Precipitation Measurement (GPM) mission on March 15, 2025 showing heavy rain across the southeastern U.S. with an overlay of the GCMD Keyword Recommender for Earth Science, Atmosphere, Precipitation, Droplet Size. NASA Worldview Imagine shopping for a new pair of running shoes online. If each seller described them differently—one calling them “sneakers,” another “trainers,” and someone else “footwear for exercise”—you’d quickly feel lost in a sea of mismatched terminology. Fortunately, most online stores use standardized categories and filters, so you can click through a simple path: Women’s > Shoes > Running Shoes—and quickly find what you need.
Now, scale that problem to scientific research. Instead of sneakers, think “aerosol optical depth” or “sea surface temperature.” Instead of a handful of retailers, it is thousands of researchers, instruments, and data providers. Without a common language for describing data, finding relevant Earth science datasets would be like trying to locate a needle in a haystack, blindfolded.
That’s why NASA created the Global Change Master Directory (GCMD), a standardized vocabulary that helps scientists tag their datasets in a consistent and searchable way. But as science evolves, so does the challenge of keeping metadata organized and discoverable.
To meet that challenge, NASA’s Office of Data Science and Informatics (ODSI) at the agency’s Marshall Space Flight Center (MSFC) in Huntsville, Alabama, developed the GCMD Keyword Recommender (GKR): a smart tool designed to help data providers and curators assign the right keywords, automatically.
Smarter Tagging, Accelerated Discovery
The upgraded GKR model isn’t just a technical improvement; it’s a leap forward in how we organize and access scientific knowledge. By automatically recommending precise, standardized keywords, the model reduces the burden on human curators while ensuring metadata quality remains high. This makes it easier for researchers, students, and the public to find exactly the datasets they need.
It also sets the stage for broader applications. The techniques used in GKR, like applying focal loss to rare-label classification problems and adapting pre-trained transformers to specialized domains, can benefit fields well beyond Earth science.
Metadata Matchmaker
The newly upgraded GKR model tackles a massive challenge in information science known as extreme multi-label classification. That’s a mouthful, but the concept is straightforward: Instead of predicting just one label, the model must choose many, sometimes dozens, from a set of thousands. Each dataset may need to be tagged with multiple, nuanced descriptors pulled from a controlled vocabulary.
Think of it like trying to identify all the animals in a photograph. If there’s just a dog, it’s easy. But if there’s a dog, a bird, a raccoon hiding behind a bush, and a unicorn that only shows up in 0.1% of your training photos, the task becomes far more difficult. That’s what GKR is up against: tagging complex datasets with precision, even when examples of some keywords are scarce.
And the problem is only growing. The new version of GKR now considers more than 3,200 keywords, up from about 430 in its earlier iteration. That’s a sevenfold increase in vocabulary complexity, and a major leap in what the model needs to learn and predict.
To handle this scale, the GKR team didn’t just add more data; they built a more capable model from the ground up. At the heart of the upgrade is INDUS, an advanced language model trained on a staggering 66 billion words drawn from scientific literature across disciplines—Earth science, biological sciences, astronomy, and more.
NASA ODSI’s GCMD Keyword Recommender AI model automatically tags scientific datasets with the help of INDUS, a large language model trained on NASA scientific publications across the disciplines of astrophysics, biological and physical sciences, Earth science, heliophysics, and planetary science. NASA “We’re at the frontier of cutting-edge artificial intelligence and machine learning for science,” said Sajil Awale, a member of the NASA ODSI AI team at MSFC. “This problem domain is interesting, and challenging, because it’s an extreme classification problem where the model needs to differentiate even very similar keywords/tags based on small variations of context. It’s exciting to see how we have leveraged INDUS to build this GKR model because it is designed and trained for scientific domains. There are opportunities to improve INDUS for future uses.”
This means that the new GKR isn’t just guessing based on word similarities; it understands the context in which keywords appear. It’s the difference between a model knowing that “precipitation” might relate to weather versus recognizing when it means a climate variable in satellite data.
And while the older model was trained on only 2,000 metadata records, the new version had access to a much richer dataset of more than 43,000 records from NASA’s Common Metadata Repository. That increased exposure helps the model make more accurate predictions.
The Common Metadata Repository is the backend behind the following data search and discovery services:
Earthdata Search International Data Network Learning to Love Rare Words
One of the biggest hurdles in a task like this is class imbalance. Some keywords appear frequently; others might show up just a handful of times. Traditional machine learning approaches, like cross-entropy loss, which was used initially to train the model, tend to favor the easy, common labels, and neglect the rare ones.
To solve this, NASA’s team turned to focal loss, a strategy that reduces the model’s attention to obvious examples and shifts focus toward the harder, underrepresented cases.
The result? A model that performs better across the board, especially on the keywords that matter most to specialists searching for niche datasets.
From Metadata to Mission
Ultimately, science depends not only on collecting data, but on making that data usable and discoverable. The updated GKR tool is a quiet but critical part of that mission. By bringing powerful AI to the task of metadata tagging, it helps ensure that the flood of Earth observation data pouring in from satellites and instruments around the globe doesn’t get lost in translation.
In a world awash with data, tools like GKR help researchers find the signal in the noise and turn information into insight.
Beyond powering GKR, the INDUS large language model is also enabling innovation across other NASA SMD projects. For example, INDUS supports the Science Discovery Engine by helping automate metadata curation and improving the relevancy ranking of search results.The diverse applications reflect INDUS’s growing role as a foundational AI capability for SMD.
The INDUS large language model is funded by the Office of the Chief Science Data Officer within NASA’s Science Mission Directorate at NASA Headquarters in Washington. The Office of the Chief Science Data Officer advances scientific discovery through innovative applications and partnerships in data science, advanced analytics, and artificial intelligence.
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Last Updated Jul 09, 2025 Related Terms
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By NASA
2 min read
Polar Tourists Give Positive Reviews to NASA Citizen Science in Antarctica
Citizen science projects result in an overwhelmingly positive impact on the polar tourism experience. That’s according to a new paper analyzing participant experiences in the first two years of FjordPhyto, a NASA Citizen Science project..
The FjordPhyto citizen science project invites travelers onboard expedition cruise vessels to gather data and samples during the polar summer season, helping researchers understand changes in microalgae communities in response to melting glaciers. Travelers in Antarctica from November to March help collect phytoplankton and ocean data from polar regions facilitated by trained expedition guides.
The new research found that ninety-seven percent of respondents reported that participating in citizen science enriched their travel experience. The paper provides a first understanding of the impact of citizen science projects on the tourism experience.
“I was worried that I would feel guilty being a tourist in a place as remote and untouched as Antarctica,” said one anonymous FjordPhyto participant. “But being able to learn and be a part of citizen science, whilst constantly being reminded of our environmental responsibilities, made me feel less like just a visitor and more a part of keeping the science culture that Antarctica is known for alive and well.”
For more information and to sign up, visit the FjordPhyto website.
Travelers in Antarctica participate in collecting phytoplankton and ocean data from polar regions facilitated by trained expedition guides. Credit: Mathew Farrell courtesy of Robert Gilmore Share
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Last Updated Jul 09, 2025 Related Terms
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By USH
NASA astronaut Nichole Ayers captured a stunning image of a rare red lightning phenomenon known as a “sprite” from the International Space Station on July 3. The jellyfish-shaped electrical burst was seen rising above a massive thunderstorm over Mexico and the southern U.S., including parts of California and Texas.
Sprites are large-scale electrical discharges that occur high in the mesosphere, triggered by positive lightning strikes.
Part of a group of upper-atmosphere events called Transient Luminous Events (TLEs), sprites are still not fully understood, despite decades of research.View the full article
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By NASA
5 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
The Swept Wing Flow Test model, known as SWiFT, with pressure sensitive paint applied, sports a pink glow under ultraviolet lights while tested during 2023 in a NASA wind tunnel at Langley Research Center in Virginia.NASA / Dave Bowman Many of us grew up using paint-by-number sets to create beautiful color pictures.
For years now, NASA engineers studying aircraft and rocket designs in wind tunnels have flipped that childhood pastime, using computers to generate images from “numbers-by-paint” – pressure sensitive paint (PSP), that is.
Now, advances in the use of high-speed cameras, supercomputers, and even more sensitive PSP have made this numbers-by-paint process 10,000 times faster while creating engineering visuals with 1,000 times higher resolution.
So, what’s the big difference exactly between the “old” capability in use at NASA for more than a decade and the “new?”
“The key is found by adding a single word in front of PSP, namely ‘unsteady’ pressure sensitive paint, or uPSP,” said E. Lara Lash, an aerospace engineer from NASA’s Ames Research Center in California’s Silicon Valley.
With PSP, NASA researchers study the large-scale effects of relatively smooth air flowing over the wings and body of aircraft. Now with uPSP, they are able to see in finer detail what happens when more turbulent air is present – faster and better than ever before.
In some cases with the new capability, researchers can get their hands on the wind tunnel data they’re looking for within 20 minutes. That’s quick enough to allow engineers to adjust their testing in real time.
Usually, researchers record wind tunnel data and then take it back to their labs to decipher days or weeks later. If they find they need more data, it can take additional weeks or even months to wait in line for another turn in the wind tunnel.
“The result of these improvements provides a data product that is immediately useful to aerodynamic engineers, structural engineers, or engineers from other disciplines,” Lash said.
Robert Pearce, NASA’s associate administrator for aeronautics, who recently saw a demonstration of uPSP-generated data displayed at Ames, hailed the new tool as a national asset that will be available to researchers all over the country.
“It’s a unique NASA innovation that isn’t offered anywhere else,” Pearce said. “It will help us maintain NASA’s world leadership in wind tunnel capabilities.”
A technician sprays unsteady pressure sensitive paint onto the surface of a small model of the Space Launch System in preparation for testing in a NASA wind tunnel.NASA / Dave Bowman How it Works
With both PSP and uPSP, a unique paint is applied to scale models of aircraft or rockets, which are mounted in wind tunnels equipped with specific types of lights and cameras.
When illuminated during tests, the paint’s color brightness changes depending on the levels of pressure the model experiences as currents of air rush by. Darker shades mean higher pressure; lighter shades mean lower pressure.
Cameras capture the brightness intensity and a supercomputer turns that information into a set of numbers representing pressure values, which are made available to engineers to study and glean what truths they can about the vehicle design’s structural integrity.
“Aerodynamic forces can vibrate different parts of the vehicle to different degrees,” Lash said. “Vibrations could damage what the vehicle is carrying or can even lead to the vehicle tearing itself apart. The data we get through this process can help us prevent that.”
Traditionally, pressure readings are taken using sensors connected to little plastic tubes strung through a model’s interior and poking up through small holes in key places, such as along the surface of a wing or the fuselage.
Each point provides a single pressure reading. Engineers must use mathematical models to estimate the pressure values between the individual sensors.
With PSP, there is no need to estimate the numbers. Because the paint covers the entire model, its brightness as seen by the cameras reveals the pressure values over the whole surface.
A four-percent scale model of the Space Launch System rocket is tested in 2017 using unsteady Pressure Sensitive Paint inside the 11-foot by 11-foot Unitary Plan Wind Tunnel at NASA’s Ames Research Center in California.NASA / Dominic Hart Making it Better
The introduction, testing, and availability of uPSP is the result of a successful five-year-long effort, begun in 2019, in which researchers challenged themselves to significantly improve the PSP’s capability with its associated cameras and computers.
The NASA team’s desire was to develop and demonstrate a better process of acquiring, processing, and visualizing data using a properly equipped wind tunnel and supercomputer, then make the tool available at NASA wind tunnels across the country.
The focus during a capability challenge was on NASA’s Unitary Plan Facility’s 11-foot transonic wind tunnel, which the team connected to the nearby NASA Advanced Supercomputing Facility, both located at Ames.
Inside the wind tunnel, a scale model of NASA’s Space Launch System rocket served as the primary test subject during the challenge period.
Now that the agency has completed its Artemis I uncrewed lunar flight test mission, researchers can match the flight-recorded data with the wind tunnel data to see how well reality and predictions compare.
With the capability challenge officially completed at the end of 2024, the uPSP team is planning to deploy it to other wind tunnels and engage with potential users with interests in aeronautics or spaceflight.
“This is a NASA capability that we have, not only for use within the agency, but one that we can offer industry, academia, and other government agencies to come in and do research using these new tools,” Lash said.
NASA’s Aerosciences Evaluation and Test Capabilities portfolio office, an organization managed under the agency’s Aeronautics Research Mission Directorate, oversaw the development of the uPSP capability.
Watch this uPSP Video
About the Author
Jim Banke
Managing Editor/Senior WriterJim Banke is a veteran aviation and aerospace communicator with more than 40 years of experience as a writer, producer, consultant, and project manager based at Cape Canaveral, Florida. He is part of NASA Aeronautics' Strategic Communications Team and is Managing Editor for the Aeronautics topic on the NASA website.
Facebook logo @NASA@NASAaero@NASA_es @NASA@NASAaero@NASA_es Instagram logo @NASA@NASAaero@NASA_es Linkedin logo @NASA Explore More
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Last Updated Jul 03, 2025 EditorJim BankeContactJim Bankejim.banke@nasa.gov Related Terms
Aeronautics Aeronautics Research Mission Directorate Aerosciences Evaluation Test Capabilities Ames Research Center Flight Innovation Glenn Research Center Langley Research Center Transformational Tools Technologies
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By NASA
The four crew members of NASA’s SpaceX Crew-11 mission to the International Space Station train inside a SpaceX Dragon spacecraft in Hawthorne, California. From left to right: Roscosmos cosmonaut Oleg Platonov, NASA astronauts Mike Fincke and Zena Cardman, and JAXA astronaut Kimiya Yui.Credit: SpaceX NASA and its partners will discuss the upcoming crew rotation to the International Space Station during a pair of news conferences on Thursday, July 10, from the agency’s Johnson Space Center in Houston.
First is an overview news conference at 12 p.m. EDT with mission leadership discussing final launch and mission preparations on the agency’s YouTube channel.
Next, crew will participate in a news conference at 2 p.m. on NASA’s YouTube channel, followed by individual astronaut interviews at 3 p.m. This is the final media opportunity with Crew-11 before they travel to NASA’s Kennedy Space Center in Florida for launch.
The Crew-11 mission, targeted to launch in late July/early August, will carry NASA astronauts Zena Cardman and Mike Fincke, JAXA (Japan Aerospace Exploration Agency) astronaut Kimiya Yui, and Roscosmos cosmonaut Oleg Platonov to the orbiting laboratory. The crew will launch aboard a SpaceX Dragon spacecraft on the company’s Falcon 9 rocket from Launch Complex 39A.
United States-based media seeking to attend in person must contact the NASA Johnson newsroom no later than 5 p.m. on Monday, July 7, at 281-483-5111 or jsccommu@mail.nasa.gov. A copy of NASA’s media accreditation policy is available online.
Any media interested in participating in the news conferences by phone must contact the Johnson newsroom by 9:45 a.m. the day of the event. Media seeking virtual interviews with the crew must submit requests to the Johnson newsroom by 5 p.m. on Monday, July 7.
Briefing participants are as follows (all times Eastern and subject to change based on real-time operations):
12 p.m.: Mission Overview News Conference
Steve Stich, manager, Commercial Crew Program, NASA Kennedy Bill Spetch, operations integration manager, International Space Station Program, NASA Johnson NASA’s Space Operations Mission Directorate representative Sarah Walker, director, Dragon Mission Management, SpaceX Mayumi Matsuura, vice president and director general, Human Spaceflight Technology Directorate, JAXA 2 p.m.: Crew News Conference
Zena Cardman, Crew-11 commander, NASA Mike Fincke, Crew-11 pilot, NASA Kimiya Yui, Crew-11 mission specialist, JAXA Oleg Platonov, Crew-11 mission specialist, Roscosmos 3 p.m.: Crew Individual Interview Opportunities
Crew-11 members available for a limited number of interviews
Selected as a NASA astronaut in 2017, Cardman will conduct her first spaceflight. The Williamsburg, Virginia, native holds a bachelor’s degree in Biology and a master’s in Marine Sciences from the University of North Carolina at Chapel Hill. At the time of selection, she was pursuing a doctorate in geosciences. Cardman’s geobiology and geochemical cycling research focused on subsurface environments, from caves to deep sea sediments. Since completing initial training, Cardman has supported real-time station operations and lunar surface exploration planning. Follow @zenanaut on X and @zenanaut on Instagram.
This will be Fincke’s fourth trip to the space station, having logged 382 days in space and nine spacewalks during Expedition 9 in 2004, Expedition 18 in 2008, and STS-134 in 2011, the final flight of space shuttle Endeavour. Throughout the past decade, Fincke has applied his expertise to NASA’s Commercial Crew Program, advancing the development and testing of the SpaceX Dragon spacecraft and Boeing Starliner spacecraft toward operational certification. The Emsworth, Pennsylvania, native is a graduate of the United States Air Force Test Pilot School and holds bachelors’ degrees from the Massachusetts Institute of Technology, Cambridge, in both aeronautics and astronautics, as well as Earth, atmospheric and planetary sciences. He also has a master’s degree in aeronautics and astronautics from Stanford University in California. Fincke is a retired U.S. Air Force colonel with more than 2,000 flight hours in over 30 different aircraft. Follow @AstroIronMike on X and Instagram.
With 142 days in space, this will be Yui’s second trip to the space station. After his selection as a JAXA astronaut in 2009, Yui flew as a flight engineer for Expedition 44/45 and became the first Japanese astronaut to capture JAXA’s H-II Transfer Vehicle using the station’s robotic arm. In addition to constructing a new experimental environment aboard Kibo, he conducted a total of 21 experiments for JAXA. In November 2016, Yui was assigned as chief of the JAXA Astronaut Group. He graduated from the School of Science and Engineering at the National Defense Academy of Japan in 1992. He later joined the Air Self-Defense Force at the Japan Defense Agency (currently the Ministry of Defense). In 2008, Yui joined the Air Staff Office at the Ministry of Defense as a lieutenant colonel. Follow @astro_kimiya on X.
The Crew-11 mission also will be Platonov’s first spaceflight. Before his selection as a cosmonaut in 2018, Platonov earned a degree in engineering from Krasnodar Air Force Academy in aircraft operations and air traffic management. He also earned a bachelor’s degree in state and municipal management in 2016 from the Far Eastern Federal University in Vladivostok, Russia. Assigned as a test cosmonaut in 2021, he has experience in piloting aircraft, zero gravity training, scuba diving, and wilderness survival.
For more information about the mission, visit:
https://www.nasa.gov/commercialcrew
-end-
Claire O’Shea / Joshua Finch
Headquarters, Washington
202-358-1100
claire.a.o’shea@nasa.gov / joshua.a.finch@nasa.gov
Sandra Jones / Joseph Zakrzewski
Johnson Space Center, Houston
281-483-5111
sandra.p.jones@nasa.gov / Joseph.a.zakrzewski@nasa.gov
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Last Updated Jul 02, 2025 LocationNASA Headquarters Related Terms
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