NSF · 48 · record R0098

NSF AI-Ready Research Performance Progress Reports (RPPR) Data

National Science Foundation · Office of Chief Information Officer (OCIO)

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not reported
Impact justification: Not reported
Start date: 2025 (year precision)
Withheld from public reporting: Not reported

Mission

Topic area: Not reported
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

OCIO is working to provide AI-ready RPPR data – a key component for determining outcomes of NSF investments. Note: Information in the RPPR may be used to identify outputs and be linked to other data sets (e.g., NSF PAR, Patent, etc.) to assess NSF's "broader impacts"; however, it is not currently available in an accessible format. Problem Statement: RPPR data, a critical resource for tracking the outcomes of NSF-funded projects. Data are currently stored in various formats across multiple locations, making it inaccessible for analytic purposes and difficult to reach without impact to current operations. The lack of centralized, accessible data limits NSF's ability to assess impacts, make informed decisions, and fully leverage data for insights. Request approval to use AWS Bedrock, AWS SageMaker, AWS Neptune & AWS Comprehend from AIDG (AI Data Governance).

Expected benefits

Not reported

System outputs

Not reported

Technology

AI classification: Not reported
System name(s): Not reported
Custom-developed code: Not reported
Public source code: Not reported

Sourcing

How it was built: Not reported
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: Not reported
Privacy Impact Assessment: Not reported
Authorization to Operate: Not reported
Demographic features: Not reported
Training and evaluation data: Not reported
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