Modernizing Work Context Information Within the O*NET Content Model

Published:

August 2026

Tags:
AI, Machine Learning, NLP   O*NET Development
Authors:

Harrison J. Kell, Lilang Chen, Amanda Koch, Jiayi Liu, Joy Oliver, Dan Putka HumRRO

Phil Lewis National Center for O*NET Development

Summary:

This project updates the Work Context information within the O*NET System to better reflect how work is performed in today's economy. Drawing on a variety of occupational data sources, scientific literature, historical O*NET development materials, and related O*NET Content Model domains, the report presents a comprehensive framework for modernizing the Work Context domain while maintaining compatibility with the existing O*NET Content Model.

The updated taxonomy expands the number of measurable Work Context elements from 57 to 81, introducing new dimensions that better capture contemporary work properties and environments. New concepts include remote work, digital collaboration, electronic performance monitoring, work-related travel, screen exposure, workload demands, work design characteristics, and other emerging features of modern occupations. The report also recommends updated definitions and measurement approaches that improve conceptual clarity while providing a foundation for future AI-assisted methods of collecting and maintaining occupational information.

These recommendations position the O*NET System to provide a richer, more comprehensive description of occupational work environments across the U.S. economy. An updated Work Context taxonomy will help job seekers, career counselors, employers, educators, researchers, software developers, and policymakers better understand the conditions under which work is performed, supporting more informed career exploration, workforce planning, occupational research, and workforce technology applications.

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