HHS · no agency ID · record R0657

Leveraging AI for Metadata Tagging for Enterprise Data Catalog of CDC

Department of Health and Human Services · HHS/CDC

Overview

Development stage: DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2024-06 (month precision)Source: Jun-24
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Administrative Functions
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Manual metadata tagging for datasets in the CDC Enterprise Data Catalog is inconsistent, incomplete, and time-consuming. The AI automates and standardizes metadata tagging, improving catalog usability and reducing manual effort.

Expected benefits

The AI increases the speed and consistency of metadata tagging, making the data catalog more usable for CDC staff. This reduces manual effort, improves the completeness and standardization of metadata, and helps staff more efficiently find and use relevant datasets.

System outputs

The AI generates suggested metadata fields (tags) for each dataset based on existing metadata, which are then used by staff to improve dataset discovery and relevance in the enterprise data catalog.

Technology

AI classification: Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.
System name(s): EDAV (Enterprise Data Analytics and Visualization Platform)
Custom-developed code: Yes
Public source code: Not reported

Sourcing

How it was built: Developed in-houseSource: b) Developed in-house
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: Not reported
Authorization to Operate: Yes
Demographic features: k) None of the above
Training and evaluation data: Enterprise Data Catalog metadata fields
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported