CDC Vault and Stacks Metadata Extraction
Description
We are attempting to speed up the process of generating a digital metadata record for objects that will be curated and stored into either CDC Public Access Platform (Stacks) or CDC Vault. These two systems are built using the same software stack but one is for public data and the other is for non-public data. To create a metadata record solely with a human, the process takes about an hour per document. We are looking to improve the process to use AI to prepare the metadata record and reduce the human time to under 5 minutes. A secondary objective is to have a non-human process for the non-public data that will go into CDC Vault.
Detailed example
The AI will return up to 41 metadata elements (eg Title, Author, Subject, Description, Funding Source, Geographical Local).
AI / analytics pattern
Agentic AI: AI systems that perform tasks or make decisions autonomously with minimal human intervention.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
There are two primary paths and uses for the AI assisted pre-processing. The first is to improve the speed and effectiveness of human catalogers/librarians. Long term, we need to be able to process more data and require AI to improve this process so that humans are only working on critical steps and validation of the AI. This process is going from 60 minutes per document to <5 minutes per document. The second is to process federal records prior to a record being entered into CDC Vault and copied to NARA. This process will not have a human review as the final disposition is not public but we need to process a large number of files (100s of thousands to millions). This is simply not realistic to do via humans so this is a novel opportunity.
Controls / human review
ATO: Yes; PIA: Not published