A Database for a Changing Economy


Book Description

Information about the characteristics of jobs and the individuals who fill them is valuable for career guidance, reemployment counseling, workforce development, human resource management, and other purposes. To meet these needs, the U.S. Department of Labor (DOL) in 1998 launched the Occupational Information Network (O*NET), which consists of a content model-a framework for organizing occupational data-and an electronic database. The O*NET content model includes hundreds of descriptors of work and workers organized into domains, such as skills, knowledge, and work activities. Data are collected using a classification system that organizes job titles into 1,102 occupations. The National Center for O*NET Development (the O*NET Center) continually collects data related to these occupations. In 2008, DOL requested the National Academies to review O*NET and consider its future directions. In response, the present volume inventories and evaluates the uses of O*NET; explores the linkage of O*NET with the Standard Occupational Classification System and other data sets; and identifies ways to improve O*NET, particularly in the areas of cost-effectiveness, efficiency, and currency.










Work, Jobs, and Occupations


Book Description

Various editions of the Dictionary of Occupational Titles have served as the Employment Service's basic tool for matching workers and jobs. The Dictionary of Occupational Titles has also played an important role in establishing skill and training requirements and developing Employment Service testing batteries for specific occupations. However, the role of the Dictionary of Occupational Titles has been called into question as a result of planned changes in the operation of the Employment Service. A plan to automate the operations of Employment Service offices using a descriptive system of occupational keywords rather than occupational titles has led to a claim that a dictionary of occupational titles and the occupational research program that produces it are outmoded. Since the automated keyword system does not rely explicitly on defined occupational titles, it is claimed that the new system would reduce costs by eliminating the need for a research program to supply the occupational definitions. In light of these considerations, the present volume evaluates the future need for the Dictionary of Occupational Titles.