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OMB Individually Reported

Natural Language query processor for Common Metadata Repository

Low riskExact public inventory row

Description

A chatgpt-like prompt query interface that uses large language models to extract intent from chat query to determine spatial, temporal and science variable filters. These filters are then applied to the Common Metadata Repository (CMR) online catalog API to return relevant earth science datasets. For example: Water temperature of Lake Michigan since 2021 would extract the spatial constraint associated with Lake Michigan, the temporal constraint associated with 'since 2021' (2021 -> present) and the remaining variable constraint of 'Water temperature' and apply those constraints to CMR. This functionality is now in our user acceptance testing environment at https://cmr.uat.earthdata.nasa.gov/search/nlp/

Detailed example

Recommendations of earth science datasets via search and discovery

AI / analytics pattern

Natural Language Processing: AI that processes, interprets, and shares information in human language.

Automation level / stage

a) Pre-deployment – The use case is in a development or acquisition status.

Expected benefit

Intuitive user experience through prompt-based interface Improved accuracy of search results

Controls / human review

ATO: Not reported; PIA: Not published

Source

OMB 2025 Federal Agency AI Use Case Inventory

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