Streamlining the Identification of Emerging Tasks in the O*NET System Using Natural Language Processing (NLP): Technical Summary


February 2021


Jeffrey A. Dahlke, Dan J. Putka
Human Resources Research Organization


The O*NET Program develops and maintains updated task information for all data-level occupations included in the O*NET-SOC Taxonomy. As part of this effort, “write-in” task statements or task suggestions are obtained from job incumbents or occupational experts (OEs) to determine if new tasks should be added. Once a new task is developed, it is included in future O*NET Program data collection efforts to gather relevance, importance, and frequency information from job incumbents and OEs. “Emerging Tasks” are also published within the O*NET Database.

Following a multi-step process, trained occupational analysts review the write-in task information. Where established criteria are met, the analysts identify and develop emerging task statements. As part of continuous improvement efforts within the O*NET System, this paper details the streamlining of the emerging task identification process using Natural Language Processing (NLP).