Rapid Automatic & Adaptive Model for Performance Prediction (RAAMP2) Dataset

The Multimodal Objective Sensing to Assess Individuals with Context (MOSAIC) project is an initiative funded by the Intelligence Advanced Research Projects Activity (IARPA) to improve the evaluative process in the workplace. To do so, researchers from Lockheed Martin's Advanced Technology Laboratories (LM ATL) and the University of Arizona (UA) conducted the Rapid Automatic & Adaptive Models for Performance Prediction (RAAMP2) study. Across two data collection studies, over 400 employees from a large company were equipped with a suite of both on-body and environmental sensors and completed daily surveys assessing well-being and job performance. Each study enrolled participants for eight weeks, with 50 individuals participating in both studies.

Data and Resources

Additional Info

Field Value
Author RAAMP2
Last Updated September 10, 2026, 18:02 (UTC)
Published April 8, 2026, 06:56 (UTC)
Citation RAAMP2 2020. Rapid Automatic & Adaptive Model for Performance Prediction (RAAMP2) Dataset. CyVerse Data Commons. DOI 10.25739/vgjr-0a33
de_created_date 2020-06-25T17:55:08Z
de_modified_date 2021-02-15T20:25:46Z
fundingReference Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), 2017-17042800004
publisher CyVerse Data Commons
resourceType multimodal sensor dataset
reuse_or_citation_conditions Data Use Agreement (DUA)