NASA has unveiled a powerful new upgrade to its Global Change Master Directory (GCMD) Keyword Recommender (GKR), a tool designed to streamline the process of finding scientific datasets. Built by NASA’s Office of Data Science and Informatics (ODSI) at Marshall Space Flight Center, the upgraded GKR uses cutting-edge AI to tag data more effectively—accelerating discovery for scientists, students, and the public.
The improved tool is powered by INDUS, a large language model trained on 66 billion words from scientific literature. This upgrade represents a leap in AI-assisted metadata curation, growing its keyword vocabulary from 430 to more than 3,200 terms. That complexity means GKR can now more accurately classify datasets with nuanced tags—even when dealing with rarely used or highly technical terms.
“We’re at the frontier of machine learning for science,” said Sajil Awale of the NASA ODSI AI team. “GKR is designed specifically to tackle the challenge of differentiating very similar scientific terms using subtle context clues. That’s crucial for improving data access.”
The AI’s capabilities are especially important in Earth science, where data from instruments such as NASA’s Global Precipitation Measurement (GPM) satellite must be clearly tagged to be useful. With thousands of datasets flooding in, tagging them consistently and accurately has been a monumental task—until now.
To address uneven keyword usage, NASA applied “focal loss” to shift the model’s attention toward rare and important tags. This ensures even specialized researchers can locate the datasets they need without wading through irrelevant results.
Beyond GKR, INDUS is already supporting other initiatives, such as the Science Discovery Engine, by improving metadata quality and accuracy.
In the age of data overload, NASA’s new AI is helping transform how science is found—and shared. By bringing order to complexity, GKR helps scientists turn raw information into real-world insight.
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