AMP: An Automated Metadata Pipeline
Description
In this work, we combine ontologies and machine learning to auto-generate robust, semantically consistent, variable-level metadata records for large NASA satellite collections, and AMPed metadata supports improved data discovery and the AMP (automated data pipeline) provides API (Application Program Interface) access to subsetted data on demand.
Detailed example
metadata records
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
In this work, we combine ontologies and machine learning to auto-generate robust, semantically consistent, variable-level metadata records for large NASA satellite collections, and AMPed metadata supports improved data discovery and the AMP (automated data pipeline) provides API (Application Program Interface) access to subsetted data on demand.
Controls / human review
ATO: Not reported; PIA: Not published